energy risk management notes based on the garp erp program
TRANSCRIPT
Energy risk management notes
based on the GARP ERP program
Joao Pedro PereiraISCTE-IUL Business School - Lisbon
www.iscte.pt/∼jpsp
May 20, 2012
These notes follow the “2012 Energy Risk Profes-sional (ERP) Examination AIM Statements”. The++,+, or - next to the reference number in the sec-tion title denote how clear and correct the paper isoverall, and in particular how clearly it answers theERP’s learning goals. A paper gets a “+” if it isgood overall, but either has some fuzzy parts ordoes not meet some of the goals. “inc” means thatI did not finish all learning goals. My own com-ments and additions are [like this].
Contents
1 Hydrocarbon resources (25%) 21.1 Exploration and production . . . . . 21.2 Crude Oil and Refining . . . . . . . 31.3 Synthetics . . . . . . . . . . . . . . . 61.4 Natural Gas, LNG and Shale Gas . . 81.5 Coal . . . . . . . . . . . . . . . . . . 15
2 Electricity Production and Distribu-tion (10%) 162.1 Electricity Generation . . . . . . . . 162.2 Hydroelectric and Nuclear Power . . 192.3 Fundamentals of Electricity Distri-
bution and Trading . . . . . . . . . . 222.4 Load Forecasting . . . . . . . . . . . 27
3 Renewable Energy Sources and Car-bon Emissions (10%) 283.1 Economics and Financing of Global
Investment in Renewable Energy . . 283.2 Sustainable Energy and Biofuels . . 31
3.3 Current Trends in the Carbon Market 323.4 Emissions Trading Models in the Eu-
ropean Union . . . . . . . . . . . . . 32
4 Financial Products and Valuation(20%) 334.1 Forward Contracts and Exchange
Traded Futures . . . . . . . . . . . . 334.2 Energy Swaps . . . . . . . . . . . . . 364.3 Energy Options . . . . . . . . . . . . 374.4 Exotic Options . . . . . . . . . . . . 384.5 Option Valuation and Risk Manage-
ment . . . . . . . . . . . . . . . . . . 384.6 Real Option Valuation . . . . . . . . 394.7 Speculation and Spread Trading . . 394.8 Hedging Energy Commodity Risks . 404.9 Weather Derivatives . . . . . . . . . 40
5 Modeling Energy Price Behavior(10%) 405.1 Introduction to Energy Modeling . . 405.2 Data Analysis and Essential Statistics 415.3 Spot Price Behavior . . . . . . . . . 415.4 Forward Curve Modeling . . . . . . . 425.5 Estimating Price Volatility . . . . . 43
6 Risk Evaluation and Management(15%) 446.1 Value-at-Risk and Stress Testing . . 446.2 Credit and Counterparty Risk . . . . 456.3 Enterprise Risk Management . . . . 466.4 Case Studies in Risk Management . 47
7 Current Issues in Energy (10%) 47
1
1 Hydrocarbon resources(25%)
1.1 Exploration and production
1.1.1 Hydrocarbon reserves [25, ch3,++]
Reserves are smaller than Resources due totechnical and economic constraints.
Reserve probabilities are denoted as P90,P50, P10, etc. Example: P90 = 265 Mbblmeans that Prob[reserves>265] = 0.9. Alter-native notations for reserves:• 1P = proven = P90 or P95
• 2P = proven + probable = P50
• 3P = proven + probable + possible = P10or P5
Nonconventional hydrocarbons are difficultand costly to produce. Main families are:• Deep offshore. Major reserves in Gulf of
Mexico, Brazil, West Africa, North Sea.
• Heavy and extra-heavy oils (< 22◦API).Aka tar sands. Major reserves in Canada,Russia, Venezuela, US and Indonesia. Theglobal resources may be four times as largeas the world’s proven reserves of conven-tional oils. However, today only 5% ofthese resources appear to be economicallyviable.
• Oil shales. Oils that remain in a typicallyclayey sedimentary source rock. This rockneeds to be mined, pulverized and pro-cessed to release oil. The process produceslarge volumes of solid waste and CO2 andrequires enormous quantities of water. Lo-cated throughout the world; large resourcein the U.S.
• Synthetic oils. Oil converted from coal orgas.
• Non-conventional gas. Gas in coal de-posits (coalbed methane), shales with lowpermeability (tight sands), or in solution
in aquifers and zones of geopressure [TheIEA classifies unconventional gas as: tightgas; coalbed methane; shale gas]. Havelow recovery rates.
• Polar zones. Large resources in Artic.Technical progress may lead to more reserves
or accelerated extraction in a oil well.Location of major oil proven reserves (in
Gbbl):1. Middle East (743)
2. Former USSR (123)
3. Africa (114)
4. North America (60)
5. South America (104), mostly Venezuela.
1.1.2 Upstream oil and gas operations[43, ++, inc]
Upstream activities are exploration and pro-duction; Downstream activities are refiningand distribution. An integrated oil company isinvolved in both, whereas an independent com-pany is involved only in upstream.
To be commercially productive, a petroleumreservoir must have adequate permeability andporosity. Porosity is the measure of the open-ings in a rock in which petroleum can ex-ist. Permeability measures the connectabilityof the pores, which determines the ability ofthe petroleum to flow through the rock. If areservoir has low permeability, there are pro-cedures to increase it, such as, fracturing andacidizing.
Mineral rights refer to the ownership of anymineral beneath the surface. These can be sep-arate from ownership of surface rights. Whenthe owner enters into a lease with an oil com-pany, mineral interests are created for bothsides:• Royalty interest (RI). The owner receives
a fraction (typically 1/8) of the produc-tion, free of any operating costs. He is re-sponsible for his share of production taxes
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and postproduction costs (transportation,etc). The RI is also referred to as nonop-erating or nonworking interest.
• Working interest (WI). It is responsiblefor the exploration, development, and op-eration of a property. The company pays100% of the operating costs and keeps allrevenues after deducting the royalty inter-est (typically 7/8).
When there are multiple companies, theworking interest can be [does not makeany sense]:
– Undivided. Ex: company A sells50% of its WI on the entire propertyto company B.
– Divided. Ex: company A sells 100%of its WI on 50% of the property tocompany B.
In the US mineral interests are typically ac-quired via leasing. Most leases contain thefollowing provisions: lease bonus, royalty pay-ments (as defined in RI above), primary term(time to begin drilling), shut-in payments (if acapable well is not producing, the lessee mayhold the lease by making shut-in payments tothe lessor), offset clause (requires drilling anoffset well if a neighbor finds a common oilreservoir).
1.1.3 Accounting for InternationalPetroleum Operations [43]
The fiscal system is the set of payments thatthe oil company must make to the foreign coun-try that owns the mineral rights. Major typesof fiscal systems (distinction not really clear inpractice):
• Concessionary systems. Typical in theUS, UK, Norway, and others. Paymentsare royalties and taxes.
• Contractual systems. Add more pay-ments. Subtypes:
– Production sharing contracts (mostpopular). Profit oil (revenues - roy-alties - production taxes - costs) isshared between the parties.
– Service contracts. The governmentallows the contractor to recover costsand earn a fee. Popular in SouthAmerica.
When two or more international parties areinvolved in a joint operation they must executea joint operating agreement detailing how costsand revenues are to be shared. This can be oneof the contracts above or can be a separateagreement.
1.2 Crude Oil and Refining
1.2.1 Nature of oil and gas [24, ch1,++]
Petroleum = Petro (rock) + oleum (oil). Akacrude oil. Hydrocarbons include crude oil(mixture of HC molecules with 5 to 60 carbonatoms) and natural gas (molecules with 1 to 4carbon atoms).
English units. Crude oil is measured in bar-rels (b or bbl). 1 kb = 1 Mbbl = 1 000 bbl,1 MMbbl = 1 000 000 bbl (M is from the latin“mille”), 1 Gb = 1 Gbbl = 109 bbl. Naturalgas is measured in cubic feet (cf). A standardcubic feet (scf) is a cubic feet at 60◦F and 14.65psi.
The density of crude oil is measured withthe American Petroleum Institute (API) scale(API decreases with specific gravity; water has10 ◦API):• Light oils are 35 to 45. Most valuable, rich
in gasoline. Tend to be sweet (less than1% sulfur). [Examples: Louisiana Sweet,WTI, Brent.]
• (Medium?) [Examples: West Texas Sour,Arab Light.]
• Heavy oils are below 25. Less valuable,contain considerable asphalt. Tend to be
3
sour (above 1% sulfur). [Examples: ArabHeavy, Venezuelan]
Benchmark crude oils:
• West Texas Intermediate (WTI), 38 to 40◦API, 0.3% sulfur, US.
• Brent, 38 ◦API, 0.3% sulfur, North Sea.
• Dubai, 31 ◦API, 2% sulfur, Middle East.
Refining separates crude oil into several“cuts” (from low to high boiling points):
• gasoline
• naphtha
• kerosene [and jet fuels]
• light fuel oils [or diesel fuel oils, heatingoil, gasoil, or distillate grades]
• heavy fuel oils or heavy gasoil
Since gasoline is most valuable, cracking isused to make gasoline from other cuts. Re-fining also produces pure chemicals (3%) thatare used to make plastics, synthetic fibers, fer-tilizers, etc.
Natural gas composition:
• Methane, 70-98%, (CH4)
• ethane, 1-10%, (C2H6)
• propane, 0-5%, (C3H8, LPG)
• butane, 0-2%, (C4H10)
Pipeline natural gas ranges from 900 to 1 200Btu/cf and is is commonly 1 000 Btu/cf.
The producing gas-oil ratio of a well is thenumber of cubic feet of gas the well producesper barrel of oil. [Note the mixed units: cf perbbl].
Condensate. In some subsurface reservoirs,at high temperatures, shorter-chain liquid hy-drocarbons occur as a gas. When this gascomes to the surface, the temperature de-creases and the liquid hydrocarbons conden-sate out of the gas. This condensate is almostpure (low octane) gasoline and costs almost asmuch as crude oil. The condensate along with
butane, propane, and ethane that can be re-moved from natural gas is called natural gasliquids (NGL).
Reservoir hydrocarbons are classified into:
• Black oil. Has heavy, nonvolatilemolecules, ◦API below 45.
• Volatile oil. More intermediate sizemolecules, ◦API is 40 or above.
• Retrograde gas. Is a gas in the reservoirunder original pressure but liquid conden-sate forms in the reservoir as pressure de-creases with production.
• Wet gas. Contains less than 95% methaneand more than 5% of heavier molecules(ethane, propane, and butane). Entirelyas gas in the reservoir, but produces liquidcondensate on the surface.
• Dry gas. It is pure methane (or more than95% methane in other definitions). Doesnot produce condensate either in the reser-voir or on the surface.
1.2.2 Investment Decisions [31]
When large quantities of fluids require long-distance transportation across land, pipelinesare normally the best option based on eco-nomics, safety, environmental consideration,and reliability.
Pipeline stakeholders: owners, customersand shippers, consumers, regulators, landown-ers, etc.
Decision process for building a pipeline: se-lect origins and destinations, estimate volumes,estimate construction costs, estimates rates,estimate operating costs, calculate economics,preliminary decision.
The need for a pipeline can be:
• Demand driven: consumers need morefuels or are currently receiving fuelsthrough more costly alternatives (truck,rail, barge, or tanker).
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• Supply driven: new oil fields, refineries, ortanker terminals.
• Market driven: new resources are discov-ered (typically natural gas), and new dis-tant markets and connecting pipelines aredeveloped simultaneously.
The revenue of a pipeline depends on the vol-ume transported and on the rate (the amountshippers pay per unit). Common ways to es-tablish pipeline rates include:
• Cost of alternative transportation. Rateset slightly below competition from ship,barge, rail, or truck. Can be very favor-able for pipeline owner.
• Location differentials. Rate set at differ-ence between the price of the commodityat the origin and the destination. Dependon the factors that cause the price differ-ence (supply/demand, transportation al-ternatives) and can thus swing wildly.
A Master Limited Partnership (MLP) is aUS legal entity, sold publicly as units of owner-ship. A general partner owns part of the com-pany and manages the pipelines. The rest ofthe MLP units are often traded on exchangesand the owners receive periodical cash distri-butions.
Possible valuation methods for pipelines:
• Economic value: NPV or Cash Flow mul-tiple.
• Comparable sales: does not work well asother pipelines are not directly compara-ble.
• Highest and best use: not normally used.
• Reconstruction cost new or replacementcost: ceiling price for buyers.
• Book value: tells sellers whether they needto record a financial gain or loss.
1.2.3 Engineering and Design —Pipelines and Storage [31]
Important aspects of pipeline design:
• Safety considerations.
• Route selection.
• Number and location of stations (com-pressor or pump stations, delivery sta-tions, storage stations, or interconnectingstations).
Storage:
• Oil, gasoline, diesel, etc, are normallystored in aboveground steel tanks, locatedat receipt and delivery points.
• Natural gas - section 1.4.3.
Storage must be sized to account for de-mand/supply imbalances during the year andduring the day.
1.2.4 The Role of WTI as a Crude OilBenchmark [36, -, inc]
Cushing, OK, is the physical delivery point ofthe NYMEX Sweet Crude contract.
Parity pricing : crudes are in parity at agiven location if the prices of each producesthe same margin for a refiner who purchasesthem. The parity conditions for WTI varythrough time due to supply/demand in differ-ent regions. Examples:
• US Golf Coast (USGC) parity. WestTexas crudes moved south to USGC. WTIprices reflected transportation costs andUSGC market prices. (Mostly before1986)
• Chicago Parity. When Chicago demandsmore than the available WTI, WTI pricesbecome related to other crudes deliveredto Chicago by other routes.
• Cushing parity. When there are notenough domestic sweets, need to importoffshore crudes. Cushing prices are based
5
on the USGC price for sweet crude de-livered directly to Cushing. Prices atother locations would then be based onthe Cushing parity price plus transporta-tion to those other locations.
New pipelines from Canada are likely to createnew parity conditions in the future. Never-theless, Cushing is still likely to maintain itsstatus as a key gathering and distribution hubin the Midcontinent market.
Relation between WTI futures prices and in-ventories:
• Contango (prices increase with maturity)induces inventory buildup.
• Backwardation induces inventory de-crease.
1.2.5 Simple and Complex Refineries[28]
Refining margin = total revenue (gasoline, jetfuel, distillate fuel, residual fuel, refinery fuel)- crude cost - operating cost. The margin mustcompensate the owner for capital investment.The margin sets the price in the market.
Types of refineries:
• Simple. Crude distillation, cat reforming,and hydrotreating distillates. Have lowerrefining margin. Tend to do better re-fining (more expensive) light or mediumcrudes.
• Complex. Simple refinery plus a vacuumflasher, cat cracker, alky plant, and gasprocessing.
• Very complex. Complex refinery plus acoker, which eliminates residual fuel pro-duction. Have higher refining margin.Tend to do better refining (cheaper) heavycrudes because can turn the heavy part ofthe crude into light products.
As complexity increases, gasoline yield goes up(30%, 50%, 60%) and residual fuel yield goesdown.
1.2.6 D2 and No.2 Diesel Fuel [6]
Under the ASTM standard, there are 6 typesof fuel oils. No.1–3 fuel oils are all called dieselfuel oils. “D2” is the same as “No.2 diesel”.
Price quotes can be:
• Free on board (FOB). Seller provides acommodity at a specified loading pointwithin a specified period; buyer arrangesfor transportation and insurance.
• Cost, insurance, freight (CIF). Price in-cludes FOB value at port of origin plus allcosts of insurance and transportation.
“Bunker fuel” is a fuel used in the marine in-dustry. No.2 diesel produced in North Americaand Europe for inland use in trucks and trainsis also used as marine gasoil.
Refined petroleum products are traded in“cargo” markets, such as, Rotterdam, Singa-pore, New York, and the US Gulf. Bunkerfuels come from blending fuel oils bought incargo markets.
1.3 Synthetics
1.3.1 Oil Sands and Synthetic CrudeOil [41]
Bitumen is a mixture of hydrocarbons that, atnormal temperatures and pressures, is a solidor semisolid, tarlike substance. Oil sands aredeposits of bitumen in sand or porous rock.Since bitumen does not flow under ambientconditions, it is more difficult to recover thanconventional crude oil is and requires signifi-cant subsequent upgrading to become a sub-stitute for conventional crude oil.
Bitumen can be processed into:
• Synthetic Crude Oil (SCO). Bitumen isupgraded to either Light, Medium, orHeavy SCO and then sold to refinerieswith corresponding processing capabili-ties.
• Synbit: mixture of bitumen and light SCO
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(becomes fluid). Sent directly to medium-crude refineries by pipeline.
• Dilbit: mixture of bitumen and a con-densate, such as naphtha (becomes fluid).Sent directly to heavy-crude refineries bypipeline.
Bitumen reserves:
• Canada: established reserves of 173 billionbarrels, mostly in Alberta. Productionmay reach 3 million bbl/d around 2015.
• U.S.: 54 billion bbl (22 billion measured,32 billion speculative), mostly in Utah.
Bitumen extraction methods:
• Mining. More common today (60% ofCanadian production).
• In-situ. Preferred for deeper deposits.Most of the oil-sand reserves (80%) willrequire in-situ methods.
Potential constraints on oil-sand production:
• Environmental impacts: footprint of ex-traction sites (in-situ is less disruptivethan mining), roads, pipelines, often inpristine environments.
• Water resources. Extraction requiresmuch more water than conventional oil(in-situ requires much less than mining).
• Natural gas prices. Both extraction meth-ods rely heavily on natural gas: in-situmethods burn natural gas to generatesteam; mining uses the same amount[don’t know for what]. By 2015, around2 Gcf/d will be required, represent-ing around 10% of Canada’s production.However, if natural gas prices increase,conventional oil prices are also likely torise, potentially keeping SCO attractive.
• CO2 emissions: life-cycle emissions forSCO are 20% higher than for sweet lightcrude oils. CO2 regulation could influencethe relative economics of the two prod-ucts.
1.3.2 Coal-to-Liquids Technologies [2,ch3, ++]
Fischer-Tropsch (F-T) steps for convertingcoal to liquids (CTL):
1. Gasification of coal. Reacting coal withsteam and oxygen to produce synthesisgas (hydrogen and carbon monoxide) andcarbon dioxide.
2. Gas cleaning and preparation. Removesgaseous molecules that derive from the im-purities found in coal (sulfur, mercury)and CO2.
3. FT synthesis. FT reactors convert thesynthesis gas to a mixture of hydrocar-bons: methane and propane; gasoline,diesel, and jet fuel; waxes.
4. Product separation. Results in two prod-uct streams: middle distillates (retail-ready diesel and jet fuel) and naphtha.
5. Product upgrade. Naphtha is a very low-octane gasoline that must be extensivelyupgraded before it can be used as an au-tomotive fuel. Alternatively, naphtha canbe converted to chemical feedstocks.
The energy efficiency of FT is close to 50%(including cogenerated electricity sold to thegrid).
Note that synthesis gas can be producedfrom different feeds: coal (CTL), natural gas(GTL), petroleum coke, and biomass (BTL).Over the last 15 years, commercial interest hascentered on stranded deposits of natural gas.Commercial-scale experience with coal is ex-tremely limited.
Transportation fuels produced in an FTCTL plant have well-to-wheel greenhouse gasemissions around 2 times higher than fuelsproduced by refining conventional petroleum.This will likely prevent growth of CTL in theU.S. unless CO2 emissions are managed. Pos-sible solutions are carbon capture and seques-tration (CCS) and alternative methods (get-
7
ting hydrogen from renewables; averaging CTLwith BTL [sounds like cheating]).
Methanol-to-gasoline (MTG) is an alterna-tive process to FT. One MTG plant is underconstruction in China.
CTL is ready for commercial development inthe US. However, the limited commercial expe-rience creates uncertainty at many levels: per-formance and operational issues, investmentand operating costs, carbon dioxide manage-ment costs. Competitiveness also depends oncrude oil prices staying at least in a $55–$65range. It is not clear how CTL will develop,but in the U.S. probably not very fast.
1.3.3 Critical Policy Issues for Coal-to-Liquids Development [2, ch6,++]
Investment in CTL production has been de-layed due to market and technical uncertain-ties. It has also been affected by uncertaintyabout environmental regulations.
Environmental impacts of CTL production:• Greenhouse-gas emissions. CTL emits a
lot of CO2 and the viability of large-scaleCCS has not yet been established.
• Air quality. Presumably, CTL would besubject to regulatory controls on pollu-tants emissions, like existing coal miningand coal-fired generation plants.
• Land use, ecological impacts, and waterquality. There are impacts both at theplant and mining sites.
• Water requirements. High water con-sumption may be a limiting factor in lo-cating CTL plants in arid areas.
1.4 Natural Gas, LNG and ShaleGas
1.4.1 Natural Gas [15, ch2.1, ++]
Because the composition of natural gas varies,it is commonly traded in units of energy, like
Btu or therms for consumers (1 therm =100 000 Btu). In North America, natural gassold to consumers needs to be in the range of1 000 Btu±5% per cf at standard temperatureand pressure.
A natural gas hub is the location where twoor more pipelines connect. A citygate is a spe-cial type of hub where interstate pipelines con-nect to local distribution networks. Most trad-ing occurs at either hubs or citygates. Themost important natural gas hub is Henry Hubin the Gulf Coast. The price at Henry Hub isused as the benchmark for the whole US. HenryHub is the delivery location for the NYMEXnatural gas futures contract.
Terminology for natural gas trading (differ-ent from other financial markets):
• Index price: price at Henry Hub. (ex:$8.52)
• Basis price: spread between the index andthe actual price at a specified location.(ex: $0.18 for Waha Hub)
• All-in price: price of physical natural gasat a specified location. (ex: $8.70 forWaha Hub)
To trade natural gas, traders usually enterinto two trades:
1. a futures trade at the Henry Hub (very liq-uid, allows bulk of trading done quickly).
2. a basis swap that exchanges the HenryHub exposure for an exposure at someother location.
A spread trade bets on price differences bygoing long in one security and short in other.Examples:
• Location spreads. Speculate on price dif-ference between two locations. Simulta-neous buy/sell at different locations withthe same maturity.
• Heat rates. Speculate on the relationshipbetween natural gas prices and electric-ity prices. Simultaneous buy/sell of power
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and gas matching either the spread trad-ing in the market or the underlying heatrate of a physical plant. This is related toTolling Agreements.
• Time spreads. Speculate on the pricedifference between periods of high andlow demand. Example: buy winter gasand sell spring gas to speculate on acolder than normal winter causing highgas prices. Done through simultaneousbuy/sell of future, forward, or swap con-tracts with differing maturity dates.
• Swing trades. Pick up inexpensive natu-ral gas when demand is low (ex: Satur-day night) and resell it when demand ishigh (ex: Monday morning). Relies onthe physical ability of the trader to storenatural gas for short periods of time.
Spot and forward markets are separate be-cause natural gas is hard to store. For exam-ple, traders might buy gas in the summer tosell during the next winter, but they aren’t go-ing to buy gas and hold it for several years asa long-term investment.
Forward prices:
• Determined by seasonal expectations ofdemand: highest in winter (for heating),lowest in spring and fall, increases in sum-mer (for electricity generation for AC).
• Follow a very regular pattern, generallythe same every year.
• Volatility decreases with maturity of theforward contract (from 1 to 4 months toexpiration)
• Correlated across locations when it is pos-sible to move gas from one location to an-other.
Hence, forward prices are highly predictable.
Spot prices:
• Determined by the demand and supplythat is on hand right now.
• Substantially more volatile than forwardprices.
• Price movements in the spot market donot have a large effect on future prices.
• There is no correlation across locations.
1.4.2 The Basics [9]
Natural gas consists of hydrocarbons that re-main in the gas phase at 20◦C and atmosphericpressure (standard temperature and pressure,STP).1 See composition in section 1.2.1.
Liquefied natural gas (LNG) is produced bycooling methane to −161.5◦C. This allows forefficient transport by ships.
Liquefied petroleum gas (LPG) refers topropane and butane in pressurized containers.They liquefy at 0◦C at 90 psi to 110 psi.
Natural gas liquids (NGL) include compo-nents that exist with the gas in the reservoirbut become liquid on the surface. Condensatesare low-density liquid mixtures of pentanes andother heavier hydrocarbons.
In addition to hydrocarbon components(methane, ethane, propane, butane, pentane),natural gas also contains non-hydrocarboncomponents: nitrogen (N2), Hydrogen sulfide(H2S), and carbon dioxide (CO2). Gases withhigh/low levels of H2S are called sour/sweet.
Barrel of oil equivalent (boe) for natural gas.The calorific values are:
• Crude oil: 1 bbl oil = 5 800 MBtu
• Nat gas: 1 cf gas = 1 MBtu or 1 m3 gas= 35.3 MBtu
Hence,
• 1 boe ≈ 5 800 cf gas ≈ 164 m3 gas
[If prices per energy were the same, 1 bbl ofoil would cost 5.8 times 1 thousand cf of gas.]
Associated gas occurs in the same reservoirand coexists with crude oil.
1Though in section 1.2.1 a standard cubic feet ofnatural gas is defined at 60◦F = 15.6◦C.
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Reserves are classified as 1P, 2P, or 3P, likeoil. Proved (1P) gas reserves worldwide are6 300 tcf, implying a reserves/production ratioof 66 years.
An oil and gas reservoir may initially pro-duce high volumes of oil relative to gas, but asthe oil production and reservoir pressure de-cline, the gas/oil ratio of the produced hydro-carbons may increase.
Coal bed methane is methane containedwithin coal seams. This is an unconventionalsource: though easy to find because coal oc-curs close to the surface, it is relatively diffi-cult to produce. Nevertheless, in the US it is asignificant portion of domestic gas productionvolumes.
1.4.3 Transport and Storage [9, +]
The cost of transporting 1 energy unit of nat-ural gas via onshore pipeline is 3 to 5 timeshigher than oil. This ratio increases to 20 ormore for longer distances.
Liquified Natural Gas (LNG) is a trans-portation alternative. Though less than 10%of gas is transported as LNG, it is growingrapidly [section 1.4.9 says it is not growingdue to shale gas]. Methane gas is cooled to−161.5 ◦C (−260◦F), shrinking 600 ft3 of gasto around 1 ft3 of LNG. One ton of LNG con-tains the energy equivalent of 1 380 m3 of nat-ural gas.
LNG is transported by ship over long dis-tances where pipelines are neither economicnor feasible. LNG could be a viable optionversus pipeline when many of the following aretrue:
• Gas market is more than 2 000 km fromthe field.
• Production costs are $1/MMBtu or less.
• Gas contains minimal impurities, such asCO2 or sulfur.
• A marine port where a liquefaction plant
could be built is relatively close to thefield.
• The political situation in the country sup-ports large-scale, long-term investments.
• The pipeline would have to cross othercountries and the buyer is concernedabout security of supply.
The LNG chain is (cost range in $/MMBtu)(measurement units):• Upstream production. (0.50–0.75) (Vol-
ume, cf or cubic meters). Similar to tra-ditional gas. Byproducts removed frommethane (such as ethane, LPG, and con-densate) are sold at market prices andcontribute to overall LNG project eco-nomics. (LPG sales are also important forsome shale gas projects.)
• Midstream processing and liquefaction.(1.3–1.8) (Mass, tons. The LNG industryuses MT, not MMT, to represent milliontons). Special care must be taken to re-move all impurities (CO2 and sulfur) andespecially water.
• Shipping. (0.4–1.0) (Cargo volume, cubicmeters)
• Storage and regasification. (1.0–1.5)
• Distribution. () (Btu)Gas storage ensures that excess supply pro-
duced during low-demand months or hours isavailable to supplement the insufficient supplyduring high-demand months or hours. Other-wise, production and infrastructure would haveto be over-sized to meet the highest demand.
Base load requirements refer to the seasonalmonthly swings, while Peak load requirementsrefer to the hourly swings. Base load storageneeds to be large, but can have low deliveryrates; peak load storage have high deliverabil-ity for short periods of time.
Structures for storing:• Pipeline itself. Simplest form of peak load
storage.
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• Depleted gas reservoirs. For base load.Most common; account for 86% of storagecapacity in North America. Cheaper, wellknown, smaller amount of cushion gas (in-jected gas that remains in the reservoir).
• Acquifers. Least desirable and most ex-pensive. Require whole new infrastruc-ture, high cushion gas.
• Salt caverns. For peak load. High deliv-erability with minimal leakage. Small ca-pacity. Cushion gas requirements are thelowest.
1.4.4 Gas Usage [9]
Electricity generation accounts for 25% of allgas consumption in Europe. In a conventionalpower plant, natural gas powers a gas turbine(or coal or oil power a steam turbine) to gener-ate electricity with an efficiency around 34%.In a Combined Cycle gas power plant, the firstcycle is a gas turbine, and the second cyclerecovers the heat from the exhaust gases topower a second steam turbine, with an over-all efficiency around 55%.
Replacing a coal generating unit with aCCGT plant virtually eliminates SO2 emis-sions, reduces CO2 by 2/3, and reduces NOxby 95%. Gas CC plants are cheaper to build,less noisy, less polluting, and easier to switchon and off. Can be built in modules and are ef-ficient at smaller sizes. Most new power plantsin North America and Europe are expected tobe gas fired.
Gas has become the fuel of choice for bothintermediate and peak load plants. As efficien-cies improve and in areas where gas prices arecompetitive to other fuels, gas may even re-place other fuels in base load.
A modern CCGT plant can be built at a costaround $500/kW to $700/kW in about 2 years(roughly 1/2 the time and cost of coal).
Gas-to-liquids (GTL) processes convert nat-
ural gas to liquid fuel. Methane is reacted withpressurized hot steam to produce syngas (syn-thesis gas, CO + 3H2). Then, syngas is con-verted to longer-chained hydrocarbons throughthe Fischer-Tropsch process. GTL produces:
• Diesel. Represents 60%–85% of the prod-ucts. Does not contain impurities, thusbeing much cleaner burning than conven-tional diesel.
• Naphtha. Feedstock for petrochemicals.
• Lube oils.
• LPGs.
Despite efforts, it remains an energy inten-sive process and the number of GTL plants re-mains limited. For GTL projects to be prof-itable we need sustained high crude prices andinexpensive gas. A 2005 study concludes thatGTL has more technical risk, complexity, andsusceptibility to short-term price fluctuationsthan LNG.
Transport fuel. Natural gas in the formof compressed natural gas (CNG), which ismethane pressured to 200 bar to 250 bar, isa good alternative for spark ignition engines.It has much smaller emissions than gasoline.It holds the greatest promise for fleet vehiclesthat refuel at a central location. Note: LNGcan also be used. However, the growth of nat-ural gas in the transportation sector has beenslow, due in part to the lack of infrastructure.
A Local distribution company (LDC) sup-plies residential gas to the end user. Thoughthey may not face direct competition due totheir exclusive mandate, their end-user energyprices have to be competitive with electricity,heating oil, coal, etc, to maintain their cus-tomer base. Deregulation in North Americaand Europe has forced LDC to become morecompetitive and has brought lower prices forconsumers.
11
1.4.5 Contracts and Project Develop-ment [9]
The pipeline gas sales agreement (GSA) is alsoknow as gas purchase agreement or a gas salesand purchase agreement. The contract coversa number of provisions, including:
• Term. Can be from 1 day to 20 or 30years.
• Price terms:
– Fixed price. Typically in shorter-term contracts.
– Fixed price with an escalator:changes every year by a percentagedetermined by an index. The in-dex may be linked to: inflation; apublished price on the NYMEX; acombination of substitute fuels, suchas crude oil (most gas contracts inEurope) or coal. Indexing ensuregas price competitiveness to alter-nate fuels and avoids renegotiatinglong-term contracts.
– Floating price. Varies every weekor month according to some marketprice.
• Delivery obligation. Flexible delivery con-tracts may be cheaper than firm deliverybecause gas supply is interruptible by theseller.
• Take-or-pay obligations. The buyer isobliged to pay for a percentage (60–95%)of the contracted quantity, even if he failsto take the gas.
• Nominations. The buyer communicatesits weekly (or other period) gas volumerequirements to the seller.
• Force majeure. Events outside the party’scontrol. Obligations of all parties must beclearly stated.
A sales and purchase agreement (SPA) forLNG is similar to a GSA for natural gas. How-
ever, the LNG SPA is more complex due tothe large capital expenditures, internationalnature, and discrete value chain. Importantfeatures of the contract.
• Price. During the first SPAs, Japanesepower plants were able to use either oilor gas to generate electricity, so the priceof LNG was indexed to a Japan CrudeCocktail (JCC) price. Since the index-ing was calculated on a monthly basis,this made LNG prices less volatile thancrude prices. Today, particularly in NorthAmerica, prices are more commonly linkedto natural gas prices (NYMEX or HenryHub).
• Take-or-pay.
• Shipping terms. Deliveries can be on afree-on-board or cost-insurance-freight ba-sis. Many buyers prefer FOB.
The phases of a gas project development are:
1. Concept and identification. Is the projectrealistic and achievable?
2. Feasibility and option selection. Financialand commercial models are created (esti-mate NPV and IRR), engineers are en-gaged, risks are identified, and preferredtechnical options are highlighted. Signmemorandum of understanding or headsof agreement letters with the resourceholder and the potential customers.
3. Project definition. Critical go/no-gostage. Key contracts to be secured: GSA,transportation agreements, environmentalimpact studies, permits. Partners shouldfinalize a joint operating agreement.
4. Project execution. An engineering com-pany is typically engaged in a engineering,procurement, construction (EPC) con-tract or an EPCM contract (adds man-agement to EPC).
5. Commission and operation.
12
1.4.6 The Natural Gas Market in theUnited Kingdom [17, ch36, -, inc]
Physical and financial gas is traded at the na-tional balancing point (NBP). NBP does nothave a specific location and gas is neither pro-duced nor consumed at the NBP. The Interna-tional Commodity Exchange acts as the mainexchange for NBP gas.
Consumption:
• Power generation. 30% of demand. Allnew generation plants are gas-fired.
• Industrial and commercial consumption.Follows diurnal, working day, and seasonalcycles but is not particularly weather sen-sitive.
• Domestic consumption. 35% of demand.Very sensitive to weather.
In the event of a supply shortage, power sta-tions and large users are required to self in-terrupt; domestic users receive priority (due tolack of relevant safety mechanisms in domes-tic cookers, making gas disruptions potentiallydangerous).
Relationship to other commodities:
• Oil. Long-term gas contracts are com-monly indexed to oil prices. This improveshedgeability, cost reflectivity, and reducecontract frustration risk.
• Electricity. The electricity price at thegate (1 hour ahead of delivery) is relatedto the cost of the marginal plant. Gas andpower prices are closely related when gasplant is at the margin. As CCGT has alsobeen designed to run baseload, long-termbaseload power price has also been set bygas.
• Power prices in the UK are closely con-nected to ETS CO2 prices. Medium CO2prices make CCGT better than coal, butvery high CO2 prices make renewable andnuclear better than CCGT.
• Coal. There is little price influence. How-ever there can be fairly high correlationdue to common dependence on oil prices.
1.4.7 Liquefied Natural Gas: Under-standing the Basic Facts [14, ++]
In the US, natural gas represents 1/4 of pri-mary energy. About 90% is produced in theUS, the balance is imported by pipeline fromCanada. Natural gas demand is expected torise, but production in major mature provincesin North America is beginning to decline [thissounds biased...]. Hence, imports of LNG byship are expected to increase. One shipload(around 3 bcf) provides 5% of US daily de-mand.
The international LNG business connectsnatural gas that is stranded — far from anymarket — with the people, factories, andpower plants that require the energy.
International LNG trade centers:
• Atlantic Basin: Europe, Africa, US.
– Importers: 33% of global imports.
– Exporters: 32% of global exports.Algeria is world’s second-largest ex-porter.
• Asia/Pacific Basin: South Asia, India,Russia, Alaska.
– Importers: Japan, South Korea, andTaiwan account for 67% of global im-ports (Japan close to 50%).
– Exporters: 50% of global exports.Indonesia (21%), Malaysia.
Additionally, Middle Eastern countries shipmostly to Asian countries, but also to Europeand US.
Peak shaving. The US has more than 100small plants that store LNG. This is used toprovide extra supply when natural gas demandpeaks during extremely cold spells or otheremergencies.
13
LNG value chain. See section 1.4.3. Lique-faction is the largest cost: capital costs around$200 per ton of capacity. Total investment forfull LNG chain is very large: $7–10 billion.Risk is thus minimized with long-term supplycontracts, with take or pay clause. However,about 70% of LNG in the US is traded in aspot market; worldwide, spot market accountsfor 12% of trade.
Units: see table in paper to convert fromtons of LNG to cubic feet of natural gas, andcorresponding Btu values.
A LNG train consists of the series of linkedequipment elements used in the liquefactionprocess. A typical plant includes 3 to 4 trains.
1.4.8 Today’s LNG Market Dynamics[35, +]
The geographical mismatch between produc-ers (Middle East, West Africa, Indonesia, Aus-tralia) and consumers (Japan, Europe, NorthAmerica) of LNG has maintained large pricedifferences between markets (often exceedingseveral hundred percent of the source price).However, these gaps may reduce in the futuredue to:
• Global growth in the number of liquefac-tion and regasification plants.
• Development of unconventional gas sup-plies, such as coal seam methane.
• New ships are able to liquefy and regasifyonboard, obviating the need for onshoreplants and making smaller stranded gassites and smaller consumer markets eco-nomically viable.
• Modular liquefaction plants make infras-tructure less costly.
Contract term. The number of short-termcontracts (≤ 1 yr) is growing. These contractstend to cover small volumes. They allow sup-pliers to take advantage of regional price differ-ences. However, the market is still dominated
by longer term contracts, as projects with toomuch uncontracted volume have difficulty se-curing project finance.
LNG prices are typically indexed :
• In East Asia, contracts are indexed tocrude oil through JCC index. Example:LNG price = (gas/oil energy ratio) x JCC+ transport costs.
• In Europe, are indexed to various com-modities.
• In the US and UK, are indexed to naturalgas through National Balancing Point andHenry Hub indexes.
This has results in arbitrage spreads betweenregions, that have widened in recent years dueto index divergence.
The current development of standardizedcontracts may help to create a more efficientglobal market for LNG, help the developmentof a spot market, and ultimately reduce pricedifferentials.
1.4.9 Impact of Shale Gas Develop-ment on Global Gas Markets [30,+]
During the early 2000s, the LNG import capac-ity to North America was expanded. However,much of that capacity now sits idle, as shalegas developments have changed expectationsabout future prices and LNG import require-ments.
The estimates of shale gas resources havebeen increasing through time. Current esti-mates point to a North America recoverableresource around 700 trillion cubic feet.
Implications of this large domestic resourcebase:
• Domestic gas prices should remain rel-atively stable, toward the long-runmarginal cost of supply (around $6 perthousand cf at Henry Hub). [An MIT(2010) study estimates that the breakeven
14
price for the exploration of shale gas is inthe range of $4 to $8 per thousand cf (2007prices)]
• A more elastic supply curve will makeit harder to price above marginal cost,meaning that oil indexation is likely toloose some prominence. [Due to shale gassupply, since 2005 gas has decoupled andbecome cheaper than oil (per Btu). Thisshows that gas and oil are not good substi-tutes in many applications, such as trans-ports.]
• Since Henry Hub prices are at a discountrelative to other locations (such as theNBP in the UK), LNG supply has beenredirected from the US to Europe andAsia, increasing physical liquidity, arbi-trage opportunities, and reducing the de-mand for pipeline supplies.
• Growth in LNG import reliance is shiftedby two decades, yielding security benefits.If shale gas also grows globally, Europeand Asia will reduce their dependence ongeopolitically risky sources of supply fromthe Middle East, North Africa, and Rus-sia.
However, rapid development of shale gas isnot certain:
• Use and contamination of water resourcesremains a major concern.
• Separation of pipeline capacity rights fromfacility ownership allows entry by smallproducers. This market structure was cru-cial for shale gas development in the U.S.In other countries, pipeline transportationmonopolies may hamper shale gas growth.
1.5 Coal
1.5.1 Coal Analysis [39, ch1, +]
Global coal reserves exceed 1 trillion tons.The largest reserves are in the U.S. (23% of
world’s reserves), former Soviet Union (23%),and China (11%). Approximately 40% of theEarth’s current electricity production is pow-ered by coal, and the total known deposits re-coverable by current technologies are sufficientfor at least 300 years of use.
Coal types (from highest to lowest rank):
1. Anthracite (or hard coal). Primarily forresidential and commercial space heating.High percentage of fixed carbon and lowpercentage of volatile matter. Moisture:less than 15%. Heat content: 22–28 mil-lion Btu/ton.
2. Bituminous coal. Primarily for power gen-eration, heat and power in manufactur-ing, and to make coke. Moisture: lessthan 20%. Heat content: 21–30 millionBtu/ton.
3. Subbituminous coal. Primarily for powergeneration. Moisture: 20–30%. Heat con-tent: 17–24 million Btu/ton.
4. Lignite (or brown coal). Exclusively forpower generation. Moisture: sometimesas high as 45%. Heat content: 9–17 mil-lion Btu/ton.
Important concepts in coal sampling:
• Accuracy: closeness between an experi-mental result and the true value. Affectedby bias.
• Precision: agreement among individualtest results obtained under similar condi-tions. Not affected by bias, hence data canbe very precise without being accurate.
• Bias: systematic error that is of practicalimportance.
There are several coal classification systemsacross the world. In the U.S., coal is classi-fied according to calorific value and fixed car-bon (which requires a “proximate” analysis todetermine moisture, ash, volatile matter, andfixed carbon by difference). The classificationlist goes from several types of anthracite (high
15
rank) to several types of lignite (low rank)
1.5.2 Sampling and Sample Prepara-tion [39, ch2, -, inc]
The heterogeneous nature of coal complicatessampling procedures. There is substantial vari-ation in coal quality and composition acrossand unmined bed.
Sampling by increments consists of extract-ing from different parts of a lot a series ofsmall portions or increments that are combinedinto one gross sample without prior analysis.The precision of sampling improves with thenumber of increments (though the size of eachshould not be so small as to cause selective re-jection of the largest particles).
Coal washing is a process to remove mineralmatter to leave the coal as mineral-free as re-quired by the buyer or legislation.
2 Electricity Production andDistribution (10%)
2.1 Electricity Generation
2.1.1 Electricity [15, ch2.2, ++]
The U.S. is split into several regional markets.Each is coordinated by its own TransmissionService Operator, which can function as a:
• Government-sponsored monopoly.
• Independent Service Operator (ISO).Serve a single state and are exempt fromfederal jurisdiction.
• Regional Transmission Organization(RTO). Operate across several states andfall under federal jurisdiction. As ISOsgrow to become RTOs, many still keepISO as part of their name.
The main RTO/ISO are:
• PJM interconnection.
• NY ISO
• New England ISO
• SPP RTO
• ERCOT ISO
• California ISO
These are integrated into 3 regional powergrids: Texas, Western, and Eastern Intercon-nect.
A deregulated market is one where anRTO/ISO coordinates generation and trans-mission. Important characteristics:
• Daily power auctions where power produc-ers submit their supply schedules. It isa non-discriminatory auction: all winningbidders get paid the same clearing price.
• Power plants are activated by merit or-der — from lowest to highest bid — un-til the demand is met. The last is the“marginal producer” and its “marginalprice of power” sets the “clearing price.”
Electricity trading markets:
• Spot market. Trading of power in arbitrar-ily small sizes for immediate use anywherein the country. Types of auctions coordi-nated by the RTO/ISO:
– Day-ahead auction: sets the price forthe following day in one-hour incre-ments.
– Real-time auction: is run continu-ously throughout the actual deliveryday. It is typically bid in five-minuteincrements.
Only power plants participate in the dailyauctions.
• Foward market. Trading of large blocksof power at about 20 locations around thecountry. Forward contracts are commonlybroken up into day and night power bymonth. They are commonly described inweekdays-by-hours shorthand. Examples:
– 7×24, power 7 days a week, 24 hoursa day.
16
– 5× 16, weekdays, peak power (7am–11pm).
– 7 × 8, nighttime off-peak (11pm–7am).
Standardization makes the contract moreliquid. The forward market doesn’t re-quire any ability to generate power at all— it is possible to trade both physical con-tracts (requiring delivery of power) and fi-nancial contracts (which settle in cash). Itis where the bulk of speculative tradingoccurs.
Elements of the Standard Market Design(SMD) recommended by the Federal EnergyRegulatory Commission:
• The costs of line congestion are paid onlyby the affected parties rather than be-ing shared across the entire grid. This isachieved by two mechanisms:
1. The primary way to solve congestionis to activate an out-of-merit orderplant close to the demand area. Thehigher cost of this producer is paidonly by the local consumers.
2. Producers pay a charge for routingpower into a high load area overcongested power lines, and receive acredit for producing power that by-passes the congestion.
• There is a penalty for remote generation,i.e, producers are only paid for deliverablepower, not power placed onto the grid.This compensates for line losses.
Hence, implementing SMD requires assign-ing different prices to different locations ona power grid. The price is called LocationalMarginal Price. It has 3 parts: a clearing price,a congestion charge, and a line loss charge.
Prices are calculated for 3 types of locations:
• Node price: price at the interface (akaelectrical bus) where power enters orleaves the grid. Producers are paid the
nodal price of the electrical bus where theydeliver power.
• Zone price: average of all nodal prices ina given area. Customers pay this price.
• Hub price: (or clearing price) average ofselected nodal prices across several zones.It is the benchmark price for the grid andit is used in the forward market.
A Financial Transmission Right (FTR) isa tradable contract between two parties thatpays the difference in price between two nodes.It helps to manage the risk of price differencesbetween a major hub and a specific node dueto congestion. Can be structured as a forwardor an option.
The Heat Rate of a given plant is the effi-ciency at which it converts fuel into electricity:
Heat Rate :=Fuel used (MMBtu)
Power produced (MWh)(1)
Typical values range from 7 MMBtu/MWh(extremely efficient plants) to 10MMBtu/MWh (less efficient). [CCGTwith 55% efficiency should be closer to 6]
Market Implied Heat Rate (MIHR):
MI Heat Rate :=Power price ($/MWh)
Fuel price ($/MMBtu)
It is profitable to produce when MIHR ≥ HR.Spark Spread is a profit estimate for a given
plant from buying gas and selling power at cur-rent market prices, excluding operating [andinvestment] costs:
Spark Spread ($/MWh) :=
Power price− (Gas price×Heat Rate) (2)
Dark spread refers to coal-based generation.
2.1.2 Location [20, ch7, -, inc]
[This chapter is written in some incomprehen-sible alien language.]
Location [whatever that means] is importantbecause of:
17
• Commercial complexity of networks dueto the interconnection of markets and thewheeling of power.
• Barriers and constraints.
• Distance between fossil fuel sourcing, largescale production, and consumption.
• Small scale renewable generation.
Requirements for locational charging [verba-tim from the book; nothing makes sense]:
• Location signals to generators.
• Medium term incentives to build networkinfrastructure for base case (transmission,generation, etc) and for variable (capacityand redundancy) requirements.
• Economic treatment of interconnection.
• Cost recovery and optimization of spendby the transmission and system operator.
Loss costs are applied separately to thetransmission and distribution sectors. Trans-mission losses are of the order of 2%–4%and are relatively low compared to distribu-tion losses. Losses are handled commerciallythrough one of the following market model forlosses:
• Marginal losses included in locationmarginal prices (eg, New York).
• Average marginal loss factors applied togenerators and loads.
• Average losses netted against load at gridsupply point.
• System administrator buys losses from themarket.
Pricing models. There are alternative meth-ods for designating the electrical location ofa point on the network, for the purposes ofcharging:
• Postage stamp: prices are the same at allpoints.
• Zonal: postage stamp pricing within azone, where a zone is a group of nodes.
• Postage stamp with market splitting:there are several zones, but they all havethe same price, unless there is a constraintbetween them. If there is a constraint, thezone that is a net exporter of electricity re-ceives the clearing price of the zone thatimports from it. This method is used inGermany and Nordpool.
• Nodal: finer grid, each node (or bus) hasits own price.
Financial Transmission Rights or Responsi-bilities? FTRs are called FT-“Rights” whenstructured as options; FT-“Responsibilities”when structured as forwards (“obligations” inPJM market).
2.1.3 The Essential Aspects of Electric-ity [23, ch2, ++]
Functions of the electricity industry:• Generation or Production. Accounts for
35%–50% of the final cost of delivered elec-tricity. The development of CCGT in the1980s showed that economies of scale werenot an inevitable part of electricity pro-duction and opened the door to competi-tion in generation.
• Transmission. Electricity is transmittedfrom the generators to local distributionsystems. Accounts for 5%–15% of the finalcost of electricity.
The transmission system is quite fragile —if it overloads it becomes unstable and cancause widespread blackouts. Hence, thetransmission system requires the constantattention of a system operator to matchthe generation to the load (demand).
• Distribution. Electricity is transportedfrom the transmission system to cus-tomers. Accounts for 30%–50% of the fi-nal cost of electricity. While transmissionworks with generation (through the sys-tem operator), distribution works with the
18
customer.
Commercial functions:
– Retailing: sales to final consumers.
– Wholesale power procurement: whenthe company chooses which producerto buy from. In the U.S., a “whole-sale sales” means sales for resale.Wholesale sales are regulated by thefederal government, while sales to fi-nal customers are regulated by thestates.
For many years the industry was organizedas a vertically integrated monopoly for the fol-lowing reasons:
• Natural monopolies (economies of scale)in transmission and distribution. Andeven in generation before smaller plantsbecome economically viable.
• The coordination of generation and trans-mission is more efficient when both ac-tivities are in the same firm. Separat-ing the two incurs into transaction costs,which are the costs of negotiating, exe-cuting, and litigating naturally incompletecontracts.
• Long-term planning of transmission andgeneration benefited from vertical integra-tion.
Monopolies have to be regulated to protectconsumers. There are two basic models: USand UK. They both: (1) base prices on costand fix them for a period of time; (2) by un-hooking prices from actual costs during thiswindow, they provide incentives for efficientoperations.
The main risks are:
• Market demand and prices.
• Technology change rendering plants un-competitive.
• Management decisions about mainte-nance, manning, and investment.
• Credit risk.Under regulation, customers take most of therisks; under competition, producers take therisks.
Important technical facts that make electric-ity different from other commodities:
1. Electricity cannot be economically stored.Hence, wholesale price varies tremen-dously with the demand/supply balance.The daily load curve is a curve showing de-mand across the day. The peak is usuallyin the afternoon. In hot(cold) areas, sum-mer(winter) is the peak season. Wholesalehourly prices in competitive markets com-monly vary by about 2:1 over the course ofa day in the off-season and by as much as10:1 in the high season (with some spikesabove this as well).
2. Electricity takes the path of least resis-tance. Hence, there is no such thing asa defined path for delivery.
3. There is a complex series of physical in-teractions in a transmission network.
4. Electricity travels at the speed of light.Each second, output has to be preciselymatched to use.
To cope with these facts in a competitive set-ting trading arrangements should be incentive-compatible, so that generators will want toobey the system operator. However, note thatthere is no physical difference between inte-grated and competitive systems: electricity ishomogenous throughout the grid and there isno direct connection between a given consumerand a given producer.
2.2 Hydroelectric and NuclearPower
2.2.1 Hydroelectric [8, ch6, +]
Worldwide, hydropower plants have a capacityaround 700 GW and generate around 25% ofthe electricity.
19
Top hydroelectric generating countries, fromhighest to lowest (capacity, hydro’s % ofnational total capacity): Canada (67 GW,60%), USA (92 GW, 7%), Brazil (?, 90%),China, Russia, Norway, Japan, India, Sweden,France. [The ordering is for generated electric-ity (GWh) in some nonspecified year, whichapparently does not match the ordering on in-stalled capacity (GW). The numbers for theUS are inconsistent throughout the paper.]
Some major plants are: 18.2 GW ThreeGorges Dam in China, 13 GW in Brazil, 7.6GW Grand Coulee in Washington State.
The amount of power generated is deter-mined by the volume of waterflow and theamount of head (the height from the turbinesto the water’s surface).
Conventional hydropower plants only useone-way water flow. They can be run-of-river(do not store water) or storage plants (havea dam and reservoir). Pumped storage plantsreuse water.
Brazil case study. Brazil had a severedrought in 2001, which led to an energy cri-sis and exposed the risk of a high level of de-pendence on hydroelectric power (although in-sufficient growth in supply and transmission inprevious years also contributed to the crisis).Measures had to be imposed to reduce electric-ity consumption.
Environmental issues: current researchon new turbine technology could potentiallyachieve a reduction in turbine-passage fishmortality and maintain a downstream level ofdissolved oxygen consistent with water qualitystandards.
There is a huge amount of regulation appli-cable to the licensing and relicensing of hydroprojects. Some of the main legislation:• National Environmental Policy Act of
1969: requires assessing the effect of op-erations on historic structures, water dis-charge into streams, habitat for plants andanimals.
• Clean Water Act of 1997: water qualitymust be certified.
• Wild and Scenic Rivers Act of 1968:project cannot affect a wild and scenicriver.
• Endangered Species Act of 1973: requiresassessing of whether relicensing is likely tojeopardize endangered species.
Licenses are issued for a period of 30 to 50years, typically enough to recover investment.
Hawaii case study. Hawaii has several hydroplants in 3 islands, but they only supply a smallfraction of electricity (from 1.4% to 10%). Im-ported oil provides 90% of energy. Hawaii isdeveloping a mix of renewable resources includ-ing hydropower, among others.
2.2.2 Nuclear and Hydropower [33,ch8, +]
A) Nuclear Power
The typical large-sized nuclear power andcoal-fired plants have an output between 1–1.5GW. In the US, there are 66 plants of this size(out of 16 755 units) and they represent 8% ofthe 1 031 GW total country nameplate capac-ity. A 1 GW plant can handle the base-loadneeds of a US city of 600 000 people (1 millionpeople if using world average consumption).
The weight of nuclear power in generat-ing electricity is [in 2005?]: Europe 28%,N.America 19%, Russia and Ukraine 18%, Asia9%. The countries with the highest percent-age are France and Lithuania (78%), [... listgoes on...], Germany (28%), US and UK (20%),Canada (15%). The country with more reac-tors is the US (around 100, of total 439 world-wide).
Types of commercial nuclear reactors (num-ber of operating reactors worldwide):
• Boiling water reactor (BWR) (92). Thefirst reactor was a BWR built for a nuclearsubmarine in 1954. A BWR feeds steam
20
directly from the reactor to the turbines.
• Pressurized water reactor (PWR) (263).The first commercial reactor was a PWRbuilt in 1957. A PWR operates underhigher pressure and temperature makingit more thermally efficient than a BWR.
• Gas-cooled reactors (26).
• Pressurized heavy-water reactors (19).Popular in Canada.
• Light-water graphite reactors (17). Onlyin Russia and Ukraine.
• Fast breeder reactors (3). In Japan,France, and Russia.
• Pebble-bed modular reactor (PBMR) (?).New technology developed in South Africathat is attracting attention. Small reactorof only 110 MW. Has a simple design andoperation, low cost of construction, andinherent safety (core meltdown is physi-cally impossible).
Many of the new reactors under constructionare PWRs, while others are pressurized heavy-water reactors or advanced BWRs.
B) Hydropower
Advantages of hydropower:
• Renewable source of energy.
• No fuel cost and low operating cost.
• Does not pollute.
• Provides a way to store energy throughpumped storage plants.
Disadvantages of hydropower:
• Are not built where they are needed. In-stead, require ample supplies of water plusfavorable geological conditions.
• High capital cost.
• Environmental concerns (eg, impact onfish and wildlife) and social issues (eg,resettlement of people living upstream,flooding of historical sites).
• Potential of catastrophic structural fail-ure.
The world’s largest hydropower producers(% of total world output) are: Canada (12%),China and Brazil (little less than 12%), U.S.(9%), Russia (6%). [Guess the ranking is basedon generated electricity in some non-specifiedyear.]
The nations with the greatest reliance on hy-dropower are (% of total electricity genera-tion): Norway (almost 100%); Brazil, Iceland,and Columbia (over 80%); Venezuela and NewZealand (65%), Canada (60%). [Year is notspecified.]
2.2.3 Nuclear Power Plant Construc-tion Costs [38, +]
Current [2008] estimates of total constructioncosts (including escalation and financing) fornew nuclear plants are between 5 500–8 100$/kW, or 6–9 billion $ per 1 100 MW plant.
Construction costs have increased signifi-cantly in recent years. This is due to increasesin commodity prices and skilled labor short-age. Furthermore, there are only two compa-nies in the world (in France and Japan) thathave the heavy forging capacity to create thelargest components in nuclear plants. Also, thenumber of suppliers of nuclear components inthe U.S. has reduced a lot over the last twodecades.
Cost estimates are very uncertain. The all-incosts can be much higher than the initially esti-mated overnight costs once you factor in own-ers’s costs such as land, cooling towers, etc.,interest during construction and cost escala-tion due to inflation and cost overruns. For asample of plants that began construction be-tween 1966 and 1977, the actual average costwas 3 times higher than the initially estimatedcost.
Construction firms are unwilling to committo fixed price contracts, which means that cost
21
overruns are paid by the owners of the plantsand their customers.
Consequences of cost overruns:
• Only one-half of projects were actuallybuilt and ratepayers frequently had to paythe sunk costs for abandoned projects.
• Cost of power from completed plants be-came much more expensive that initiallyexpected.
• Some utilities got into severe financialproblems and some went bankrupt.
Two new reactor designs have been pre-approved in the US — the Advanced BoilingWater Reactor and the Westinghouse AP 1000— but there is absolutely no construction oroperating experience with these designs any-where in the world.
The nuclear renaissance is heavily depen-dent on obtaining federal loan guarantees thatwould shift the risks of rising plant costs fromplant owners onto the federal government.
2.2.4 The Prospect for Safe Nuclear[13, +]
Passive safety features rely on physics insteadof active interventions. The best passive safetymeasures require no signal inputs, no externalpower sources or forces, no moving mechani-cal parts, and no moving working fluid. Forexample, thick concrete walls.
Examples of safer, next-generation reactors:
• Westinghouse AP1000. (AP stands forAdvanced Passive). Has an emergencywater reservoir above the reactor that’sheld back by valves. If the cooling sys-tem fails, the valves open and water poursdown to cool the vessel. The water isenough to last for 3 days. Westinghousesays the AP1000 is 100 times safer thancurrent plants.
• Areva’s EPR has four redundant safetysystems.
• Pebble bed reactor. Has been under de-velopment for decades in Germany, thenSouth Africa, and now China and US. Theradioactive fission products are absorbedin the coatings of the fuel pebbles, and thefuel doesn’t get hot enough to melt downeven if there is no coolant. China alreadyhas a 10 MW experimental reactor in op-eration and is building a 200 MW plant.However, pebble bed reactors do not scaleup well: above 600 MW they loose theirsafety advantage.
• Traveling wave reactor. Under develop-ment by TerraPower, a Microsoft spinoff.
There is some conflict about promoting thesenew reactors because utilities and manufactur-ers do not want to imply that the older designsnow in service are unsafe.
The failure of Tepco’s Fukushima reactorwas in part due to bad management deci-sions. In particular, officials underestimatedthe risk that a huge tsunami would overwhelmFukushima’s defenses. However, it is humannature to lower the probability of catastrophicevents when you have no idea about how todeal with them.
2.3 Fundamentals of Electricity Dis-tribution and Trading
2.3.1 Trading Arrangements [23, ch7,+]
Trading arrangements are the legal agree-ments between traders and the system oper-ator and/or the transmission owners.
The 4 facts that make electricity differentfrom other commodities (section 2.1.3) lead,respectively, to the 4 pillars of market design:
1. Imbalances between contracted supply inforward markets and actual demand mustbe corrected by the system operator in realtime.
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2. Congestion management. The system op-erator has to distribute generation to en-sure that total electricity flows will notoverload any line.
3. Ancillary services such as operating re-serves, reactive power, etc, are necessaryto make the transmission system work,but these other outputs are dependent onalso producing energy.
4. Scheduling (in advance) and dispatch (inreal time) done by the system operator re-quires incentive-compatible rules.
Alternative models of trading agreementsdiffer on the degree to which operation andcommercial arrangements for imbalances, con-gestion, ancillary services, and scheduling areintegrated with spot markets. From low tohigh integration:
1. Wheeling model. Used in many areas ofthe US as a first step toward competi-tion. Prices are regulated and there is nospot market. A vertically integrated util-ity with its own generation runs the trans-mission and system operation. Providesaccess to other traders after it has sched-uled its own resources, ie, native load getspriority, and the spare transmission capac-ity can be used for wheeling. Large loadssuch as municipalities arrange for inde-pendent generators to supply large blocksof their electricity needs instead of pur-chasing from the local utility.
2. Decentralized model. Used in Californiaand Texas. The system operator is inde-pendent of the generators but its commer-cial responsibilities are deliberately min-imized — the aim is to let traders runthe market. Generators and consumerstrade in bilateral contracts. The systemoperator must take the physical origin anddestination of contracts specifically intoaccount when scheduling. However, thisphysical matching is a fiction, and leads
to inefficiencies and arbitrage opportuni-ties. Typically preferred by marketers andtraders.
3. Integrated model. Used in 3 regions of theUS (eg, PJM, New York) and most mar-kets abroad. The system operator sched-ules forward contracts at the request oftraders, but also takes bids from tradersto modify scheduled contracts and to pro-vide imbalances, congestion management,and ancillary services. The system oper-ator runs the spot market using a largecomputer optimization program.
This model is typically preferred by utilityengineers, whose concern is the stabilityof the transmission system. [23] stronglyprefers this model: it “runs smoothly,incorporating the necessary complexitiesof the transmission system and providingincentive-compatible rules. A major bene-fit is that independent generators can findan outlet for their power without having tofind specific customers, [... which fosters]real competition in the production mar-kets.”
The essential feature of the integrated modelis that the system operator administers a spotmarket integrated with the pricing of imbal-ances, congestion management, and the ancil-lary services. The following mechanisms makethis work:• The system operator runs an optimiza-
tion program (every 10 minutes) that min-imizes costs, subject to transmission con-straints. The output is a merit orderlist of generators and the market clearingprice. It is a nondiscriminatory auction:all plants that bid below the spot pricewill be generating and they will all be paidthat same spot price.
The incentives are for traders to bid closeto their marginal cost; most of the timethey will be paid more than this, making a
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contribution to the investment costs, butbecause the software sets the spot priceat the highest bid selected, they do notneed to add in the overhead when makingtheir bids, and if they do they will not beselected to run as often.
[They will receive “a contribution to theinvestments costs” only if the price isgreater than average variable costs: pq −V C − FC ≥ −FC ⇒ p ≥ V C/q =: AV C.(This is a short-run analysis because somefactors are fixed and must be paid even ifoutput is zero). Unless the AVC is alwayszero (like in wind), there is a set of lowquantities where it is better not to pro-duce than to receive MC. Graphically, thismeans that the clearing price must inter-sect the MC curve above the AVC curve.See p. 217 in Varian, Microeconomic anal-ysis.]
• The optimization process outputs a set oflocational prices that differ by the cost oftransport.
• All imbalances are traded at the marketspot prices that result from the optimiza-tion process.
• Congestion management: traders whoschedule contracts across valuable trans-mission lines are charged a transmissionusage charge (a bottleneck fee) beingequal to the energy price difference be-tween the two ends of the transaction.
Main ancillary services:• Reactive supply.
• Operating reserves: available capacitythat is able to run on short notice. Needsto be about 7%–10% of load.
• Frequency response (or regulation re-serve): capacity that continually adjustsoutput to exactly match demand.
The total cost of ancillary services is 1%–3%of total costs.
2.3.2 Details of the Integrated TradingModel [23, ch8, +]
Given that spot prices are set in a nondiscrimi-natory auction, generators with lower costs willmake a profit from the market prices set at themarginal cost of the marginal generator. Buthow does the marginal generator recover hisinvestment? Prices need to rise at peak times.
Methods to ensure that prices peak in timeof high demand (from best to worst):
1. Demand bidding. Used in PJM. Cus-tomers bid for what they want to take andthe price results from the normal intersec-tion of supply and demand. Demand bid-ding does two things:
(a) Raises prices when supplies are tight,thus inducing new investment.
(b) Stops generators bidding up pricesto excessive levels. Because of thesteepness of the end of the supplycurve, a very small reduction in elec-tric load from demand response canreduce the price a lot at peak peri-ods.
However, demand response is still verysmall in most markets and so demandcurves are nearly vertical. The marketsthus rely on generators bidding abovemarginal cost, which has the danger ofthem bidding far too high in times of highdemand.
2. Capacity payments. Was used in Ar-gentina and the U.K. Pool. Capacity“adders” increase the market price. Theyare higher when it is more likely that therewill be a shortage.
This is based on the correct notion thatif generators charge marginal costs atall hours, they will only break even ifthey also charge investment costs at peaktimes.
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3. Capacity obligations. All entities thatserve final customers are required to ac-quire “capacity tickets” to cover the ex-pected load of their customers plus a re-serve margin.
In the integrated model, traders can stillmake forward contracts in private and bilat-eral markets, just like they do in the wheelingand decentralized models. The contract sched-ule (MW, physical locations, and timing) mustbe notified to the system operator only if onethe following holds:
• The contract is inflexible. When all mar-ket participants are flexible — willing tomodify operations from their contractedlevels if profitable — the system operator’sdispatch is fully separate from the forwardcontracts. The forward contracts then be-come only financial, providing only pricerisk management.
• The contract requires net settlement: im-balances are calculated and settled by thesystem operator as actual metered deliv-eries net of contract volumes. Contractschedules are only used for financial set-tlement, not for physical dispatch. Netsettlement is recommend over gross set-tlement.
PJM has net settlement, allowing both inflex-ible and flexible contracts. Forward contractsare “scheduled” for delivery — but the link be-tween producer and consumer is in truth only afinancial one, it could never be a physical one.
There is transmission congestion when thecapacity of one line is filled. To manage con-gestion, plants on the import side of the con-straint have to increase production, and plantson the export side of the constraint have to de-crease production, relative to the productionschedules they would otherwise prefer. Hence,spot prices will be higher in the import area.The value of scarce transmission is equal to themarket price of electricity in the import area
minus the price in the export area.
Pay-as-bid versus (nondiscriminatory)marginal bid pricing. Almost all integratedelectricity markets have marginal bid pricing.The argument for pay-as-bid is that consumerswould pay less because more efficient gener-ators would receive lower prices. However,evidence shows that generators would quicklyadjust to pay-as-bid auction rules and wouldstop bidding at mg cost and would insteadbid at their best guess of the market-clearingprice. If there was perfect information, bothmethods would give the same clearing price;in practice, pay-as-bid creates inefficiencies.In particular, it increases the risk for efficientbase load generators (if they overshoot, theydo not run), making them less profitable andless likely to be built.
The day-ahead market operates a day in ad-vance of the spot market. For example, at 2pmon Wed, an auction is held for energy deliveryfor each hour of Thu. Transactions in the day-ahead market then become forward contractsthat are settled against spot prices. Benefits:
• Beneficial for generators with high start-up costs.
• Prevents generators from gaming the mar-ket by withdrawing capacity at short no-tice to lift spot prices.
• Promotes demand response.
A day-ahead market exists in PJM and NY.
2.3.3 Tolling Agreements [15, ch4.3,++]
With deregulation, some power plant operatorsbegan to specialize in maintaining the physicalhardware of their plants. Others, called powermarketers, specialize on marketing the power.
A tolling agreement is a contract to rent apower plant from its owners. The power mar-keter is responsible for supplying fuel to theplant and selling the resulting electricity into a
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competitive market. They take on all of theeconomic risks and earn the profits above afixed maintenance fee.
Tolling agreements give the renter the optionto convert one physical commodity (fuel) intoa different commodity (electricity). Ignoringoperating costs, the conversion in a gas plantgives:
Profit ($) =
Dispatch (MWh)× Spark Spread ($/MWh)
where the spark spread is defined in (2).
Tolling agreements can be valued through areal options approach. Each operating decision(leg) is modeled as a financial option. Eachleg requires electricity and fuel prices and theright time and location. Since tolling agree-ments can run for up to 20 or 30 years, therecan be several hundred separate commoditiestraded over the lifetime of the contract.
Implications for risk management :
• It is meaningless to add up the exposuresof different legs. For example, it is wrongto ask, “What’s the exposure of this powerplant to the price of electricity?” becausethere is no single price of electricity (Au-gust electricity is a fundamentally differ-ent product than May electricity).
• High volatility in the spread between elec-tricity and fuel prices increases the valueof the option. Hence, low correlation be-tween these prices increases the value ofthe tolling agreement.
2.3.4 Wheeling Power [15, Ch4.4, ++]
Wheeling is the act of physically transport-ing electricity from one location to another.Wheeling trades require a physical transfer ofelectricity over power lines rented from a thirdparty.
Examples of wheeling trades:
• Building a transmission line to connect theupper Midwest (where coal is the marginalfuel) to the southern US (where gas is themarginal fuel). This trade is a bet on nat-ural gas prices being much more volatilethan coal prices.
• Import hydroelectric power from the Nia-gara Falls region into the New York Citymetro area.
• Building a nuclear plant a long way froma population center [and a transmissionline].
• Investing in a PV solar installation in NewMexico and building a long distance highvoltage DC power line to get the power tothe East Coast.
Wheeling trades can be valued as financialoptions. The premium is the up-front cost ofbuilding or renting the line. The underlyingasset is the price difference between the tworegions. The strike price is the transportationcost (line losses and variable expenses).
Long-distance transmission alternatives:
• High voltage Alternating Current (AC)lines. Transmission losses are proportionalto the square of the current. To trans-fer the same amount of power, it is neces-sary to increase the voltage to reduce thecurrent. Transformers only work on AC,which is why AC transmission is the mostused.
• High voltage Direct Current (DC) lines.They are typically lower cost and lose lesspower than AC lines. However, DC powerhas to be converted to AC before beingdistributed to end users, which has 5%–10% losses. These conversion losses haveto be weighed against transmission losses.Furthermore, voltage drops whenever anyenergy is removed from a DC line, makingmultiple end points problematic. Hence,HVDC lines are primarily for extremely
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long distance, point-to-point connections.
Location spread trades are financial tradesmade in the futures or forward markets. Theycan be done financially with no physical trad-ing capability (this is the primary differenceto a wheeling trade). The trader takes a longposition in one region and a short position inanother. The trades are liquidated before thephysical delivery is required.
Example of a spread trade:
1. Opportunity: expect snow melt earlierthan April this year. This would lead tocheaper power in the Pacific Northwest(due to larger hydroelectric production)than the market is anticipating.
2. Trade March futures for peak power: buyCalifornia (NP-15) and sell Pacific NW(MID-C).
3. Result will be positive if futures priceshave changed by the time the trade is liq-uidated (must be prior to expiration).
2.4 Load Forecasting
2.4.1 Spatial Load Forecasting [15,ch4.1, ++]
Spatial load forecasting is a prediction of elec-trical demand within a specified region for aspecific period of time. In the short term, itis used to schedule power plants; in the longrun, it is used to construct new power linesand plants.
Factors that go into producing a load fore-cast:
• Location. Forecasts are made for lim-ited geographical areas, typically definedas connecting to the same part of a powergrid.
• Type of consumer:
– Residential: higher consumption be-tween 6am–9am and 6pm–11pm.
– Commercial: offices and retail. Havestandard schedule and moderate de-mands.
– Industrial: high variation.
• Base load demand. Is the minimum levelof demand that must be met at all times.To be cost effective, should be met byhighly efficient low [fuel] cost “base loadpower plants” that can take advantage ofthe fact that they will be able to workaround the clock.
• Weather. A lot of electricity is used forspace heating and cooling (AC). Hence,temperature accounts for a very large por-tion of the variation in demand, at twofrequencies:
– Day-to-day: demand will typi-cally increase (decrease) with above-average temperature in summer(winter) time.
– Month-to-month: demand is typi-cally higher in summer and winter,and much lower during spring andfall.
• Calendar effects:
– Higher demand on weekdays than onweekends and holidays.
– Typically, in the summer the dailypeak is in the early afternoon (moreAC), while in the winter there is apeak in the early morning (peoplewaking up) and another in the endof the day (people arrive home fromwork).
The steps in creating a load forecastingmodel should be: get historical load, look atgraphs, develop a preliminary model, expandthe model. It is important to test the modelthrough error analysis: analyze the differencesbetween actual loads and the model’s pre-dictions. Do it in-sample and out-of-sample.
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Check whether the errors correlate with typi-cal factors like weather, calendar, etc.
3 Renewable Energy Sourcesand Carbon Emissions(10%)
3.1 Economics and Financing ofGlobal Investment in RenewableEnergy
3.1.1 The Economics of Renewable En-ergy [21, ++]
Contrary to fossil fuel plants, renewable energysources are generally capital intensive and havelow or no variable costs. If we build a renew-able power station, we are effectively prepayingfor the next 40 years of electricity. This makeslong-term debt financing seem fair.
The Levelized cost of electricity (LCOE) isthe constant price at which electricity wouldhave to be sold for the production facility tobreak even over its lifetime, assuming a rea-sonable level of capacity utilization. From apolicy perspective, we should add the socialcosts.
Social costs of using a fossil fuel :
• CO2 emissions. Cost estimates range from$8 to $85 per ton of CO2.
A large coal-fired power station can use10 000 tons of coal daily, costing between50–100 $/t, so that fuel costs can reach$1 million per day. Burning 1 t of coalwill produce 1.5–3.5 tons of CO2 [eia.govsays 2 t, wet basis]. Hence, a CO2 priceof $30/t can double the fuel costs of acoal power station. At the higher priceof $85/t, the LCOE rises from $0.06/kWhto $0.11/kWh.
• Other pollutant emissions, such as SO2,NOx, PM, are associated with environ-mental damage, poor health, and early
death. Costs of electricity productionrange from almost zero to 0.15 euros perkWh [Paper has references]. Marginalcosts for new capacity in the US are lowdue to high emission standards and a capon total SO2 emissions.
The attractiveness of investing in renewablesdepends on four factors:
• Costs of oil and other fossil fuels.
• Cost of carbon emissions.
• Cost of capital.
• Incentives for production of green electric-ity. US uses production tax credits, butthis is inefficient for start-ups because itrequires federal tax liabilities. Direct sub-sidies tend to be more efficient.
The capacity factor [or load factor] is the ac-tual output as a fraction of the maximum out-put that would have been produced if the planthad operated at maximum capacity. Wind andsolar are in the 25%–35% range (due to in-termittency), while coal or geothermal reaches90%.
Intermittent renewables are only able tobid in the day-ahead electricity market be-cause they cannot guarantee steady base loadpower (usually supplied through long-termcontracts).
In states with renewable portfolio standards(RPS) there is generally a market in renewableenergy certificates (REC). REC are tradablecertificates proving that 1 kWh of electricityhas been generated from renewables. To com-ply with the RPS, electricity distributors haveto own sufficient REC at the end of the year.
Economic viability of major renewables:
• Wind. Capital costs around $4 000/kWfor offshore and $2 000/kW for onshore.LCOE for onshore in 8-10 cents/kWh.
• Solar. PV: capital $7000/kW; LCOE 25–30 cents/kWh. PV is already competitivein distributed applications where there
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is no grid connection. CSP: LCOE 11cents/kWh, 15 cents/kWh with thermalstorage.
• Geothermal. LCOE 3.5 cents/kWh.
• Water. Hydropower capacity in the USmay actually decrease to protect endan-gered fish species. Wave and tidal are notyet at commercial scale, but costs seemsubstantially above market rates.
• Carbon capture and storage. Costs in $50–100 per t of CO2, too high to be com-mercially attractive. A variant is to cap-ture CO2 directly from the atmosphere ata cost of $200/t.
• Biofuels. Sugar-based ethanol is compet-itive with gasoline at oil prices of $50–60per barrel. For biodiesel to replace dieselit will be necessary to develop new tech-nologies.
For comparison, LCOE for coal is less than 7cents/kWh, gas and diesel are higher, nuclearis in 8–10 cents/kWh.
3.1.2 Project Finance Primer [19, +,inc]
Project Finance is a method of financing inwhich the lenders have limited or no recourseto the assets of the parent company that “spon-sors” the project. The project is owned by aspecial purpose entity, the “project company”.Lenders will typically demand a secure revenuestream for the project, which in wind and solarprojects is typically obtained through a powerpurchase agreement (PPA) with the local util-ity. Project finance is a way to finance large in-frastructure projects that might otherwise betoo expensive or speculative to be carried on acorporate balance sheet.
Advantages:
• Debt is held in the project company, notin the sponsor’s books.
• Protection of key sponsor assets, such asintellectual property, key personnel, andother assets, in case of project default.
• The expected IRR for the equity in a fullyleveraged project can be very high.
• The sponsor may be able to recover devel-opment costs at the closing of the projectfinancing and put their money into newprojects.
• Monetization of tax incentives (see below).
Project finance is a realistic opportunitywhen:
• The project is large, with debt above $50million (project finance is time-consumingand expensive to consummate).
• The revenue stream will be large enoughto support a highly leveraged debt financ-ing.
• The power purchaser is creditworthy.
• The physical assets are sufficient to repaylenders in case of foreclosure.
• The technology can be new, but notuntested.
• Success does not depend only on a few keyindividuals who may depart.
• The sponsor must be willing to turn overthe project to lenders if it becomes unableto service its debt.
• The sponsor is not looking for a quick exit.
• The sponsor is willing to share manage-ment with lenders.
Project revenues are distributed to investorsthrough a waterfall with the following order:
1. Construction and operating and mainte-nance costs, typically paid to sponsor’s af-filiates.
2. Fees, interest, and principal to lenders.
3. Reserve accounts and “cash sweep” tolenders.
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4. Subordinated debt.
5. Equity holders.
[Project Finance seems just like Collateral-ized Debt Obligations...]
Federal income tax incentives for renewableenergy projects:
• Production tax credits (PTC): around 2.1cents/kWh in 2009.
• Investment tax credit (ITC): based on thecost of the qualifying property. Taxpayercan choose either PTC or ITC for facilitiesthat qualify for PTC.
• Treasury grants: cash payment in lieu ofthe ITC (and the PTC). The taxpayerneed not have a federal income tax liabil-ity to benefit from a grant.
• Accelerated depreciation.
• Advanced energy project credit for manu-facturing facilities.
• Tax credit for the production of cellulosicbiofuels: $1.01/gallon.
Tax structures used to monetize availableproject subsidies. When a developer is not ableto benefit from the various tax benefits, thefollowing strategies allow the developer to re-ceive value, or “monetize”, the tax incentivesthrough the intervention of an institutional in-vestor that can benefit from those tax incen-tives:
• Partnership flip. The developer and aninstitutional investor form a partnership.In the initial stage, the investor receivesa disproportionate allocation of the part-nership income and tax credits (PTC,ITC). When the investor’s target returnis achieved (the flip point), the investor’sallocation is reduced to a small portion.
• Sale-Leaseback. The developer sells the fa-cility to an investor. The investor leasesthe project back to the developer for aterm equal to the PPA. The investor is
considered the owner of the project andcan thus claim the ITC. The investorshares its tax savings with the developerin the form of reduced rents. Can be usedfor ITC, but not for PTC.
• Pass-through lease. More complex struc-ture. Has been used to monetize solar en-ergy credits and Treasury grants. It isusually preferred by investors who valuethe credit/grant but place less importanceon depreciation.
3.1.3 Global Trends in Renewable En-ergy Investment [5, +]
In 2010, global investment in renewable powerand fuels set a new record at $211 b(billion),+$51 b than in 2009.
Considering only “financial new investment”(venture capital and private equity, publicmarkets, and asset finance of utility scaleprojects), for the first time developing coun-tries at $72 b overtook developed countries at$70 b. This is mostly due to China at $49b, and smaller amounts in South and CentralAmerica ($13 b) and Middle East and Africa($5 b).
Nonetheless, in “total investment” (whichadds R&D and small distributed projects), de-veloped economies remain well ahead. This ismainly due to small-scale distributed capacity(SDC) investments of $60 b, most of which inrooftop photovoltaics (PV) in Europe. Totalinvestment in the US was $25 b, an increase of58% from 2009.
Total investment in solar came close to windfor the first time in 2010. Again, the big chunkin solar is SDC and the increase is due to fallingPV prices. Considering only financial new in-vestment, the decomposition is (in $b):
1. Asset finance: solar 18.9, wind 89.7.
2. Public markets new equity: solar 5.3,wind 8.2.
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3. VC/PE: solar 2.2, wind 1.5.
Challenges in renewable energy projects:
• Reduction in feed-in tariffs for newprojects and even threats of retroactivecuts.
• Low natural gas prices.
• Outside skepticism: clean energy sharesunder-performance and cooler mood in in-ternational politics.
Renewable power, excluding large hydro-electric, made up 8% of total world electricitygeneration capacity in 2010 and 5% of actualgeneration. It accounted for 34% of additionalcapacity brought online.
Asset finance is defined as all money in-vested in each year, either from internal funds,debt finance, or equity finance. [If it is re-ally “all” aren’t they double counting equityin “financial new investment”?] Asset financeof new utility-scale projects increased in 2010to $128 b, distributed through Asia & Ocea-nia ($56 b, mostly in China), Europe ($29 b),North America ($25 b), and South America($13 b). Balance sheet finance continued tobe dominant (70%), but non-recourse projectfinance increased to 30%. The wind sector ac-counted for 70% of overall financing.
3.2 Sustainable Energy and Biofuels
3.2.1 Sustainable Energy [33, ch9, inc]
[The paper is interesting but does not addmuch to other readings and it is a bit old.]
3.2.2 Biofuels: Markets, Targets andImpacts [40, ++]
Biofuels are classified into:
1. First-generation. Ethanol produced fromthe sugar or starch portion of plants (e.g.,sugarcane, sugar beet cereals, and cas-sava) and biodiesel produced from oilseed
crops (e.g., rape seed, sunflower, soybean,and palm oil).
2. Second-generation. Biofuels producedfrom lignocellulosic biomass (e.g., agri-cultural and forest residues) or fromadvanced feedstock (e.g., jatropha andmicro-algae).
While 1st generation biofuels directly competewith food supply, 2nd generation can produceboth food and fuel together. Unfortunately,cellulosic biomass is more difficult to breakdown than starch, sugar, and oils, and the tech-nology to convert it into liquid fuels is moreexpensive.
Leading producers:
• Ethanol. US and Brazil accounted for 90%of the total world production in 2008.
• Biodiesel. World production is less than25% of ethanol production. In addition toUS and Brazil, main producers are in theEU (Germany, France, Italy).
Despite growth in production, biofuels only ac-counted for 1% of world road transport fuelconsumption in 2005.
International trade in biofuels is only 10%of total production. The major importers arethe US and EU (due to blending mandates)and the major exporter is Brazil. Import tar-iffs, domestic subsidies, and sustainability reg-ulations have restricted trade. Still, trade isexpected to increase due to the comparativeadvantage of some developing countries.
Production costs:
• Ethanol: $0.2/liter ($0.3/liter of gasolineequivalent) for new plants in Brazil, 50%more in US, 100% more in EU. Trans-portation, blending, and distribution adds$0.2/liter. Cellulosic ethanol, still indemonstration stage, is about $1/liter.
• Biodiesel: $0.7–$1.0/liter.
Aside from sugar cane based ethanol in Brazil,biofuels are not presently competitive without
31
substantial government support if oil prices arebelow $70 per barrel.
Investments in biofuel production plants in2008 amounted to $3 billion in Brazil, $2.5 bil-lion in the US, and $1.5 billion in France. Theworldwide total was around $15 billion.
3.3 Current Trends in the CarbonMarket
3.3.1 State and Trends of the CarbonMarket [42, +, inc]
The EU Emissions Trading Scheme (EU ETS)accounted for 97% of the global carbon mar-ket value in 2010 (considering both EuropeanUnion Allowances (EUA) and Clean Develop-ment Mechanism (CDM)). The growth of theglobal market stalled in 2010.
To reduce emissions, countries are adoptingone or several of the following policies: cap-and-trade schemes, baseline and credit mech-anism, renewable energy and energy efficiencycertificates, carbon taxes, subsidies, and emis-sion standards.
Policies are fragmented across countries:
• EU. The current goal is to achieve a 20%emissions reduction by 2020 on 1990 lev-els. But the Roadmap for 2050 aims toreduce emissions by 80–95% by 2050 [rel-ative to what year?].
During Phase III of the EU ETS thatstarts in 2013, half of the allowances areexpected to be auctioned. During the pre-vious Phase II (2008–12) they were all al-located for free.
The EU ETS will include emissions fromaviation, but airlines from China and theUS are opposing the inclusion of theiremissions.
• US. Climate policy is uncertain: there areseveral regional initiatives to reduce CO2and increase renewables, but their fate is
not clear. The only state more determinedis California. It aims to reduce GHG emis-sions to 1990 levels by 2020 by: launch-ing cap-and-trade in 2012; requiring 33%renewable electricity by 2020; cut carboncontent of fuels by 10% by 2020.
• Australia. Goverment announced plansfor a carbon fixed-price mechanism thatwill transition into an emissions tradingscheme.
• China. Aims to reduce carbon intensity(CO2 emissions per unit of GDP) by 17%by 2015. May introduce emissions tradingin 2013.
The EU ETS has suffered several frauds andis undergoing regulatory reform. This has in-creased interest in OTC spot markets.
Kyoto Protocols: the uncertainties sur-rounding a post-2012 international agreementhave left Europe alone to absorb the supplyof project-based certified emission reductions(CER) after 2012.
Voluntary carbon markets remain tiny (only0.3% of global volume), but are growing. Thefastest growing product is “Reducing Emis-sions from Deforestation and Forest Degrada-tion (REDD)”, in part due to probably becom-ing eligible for offset in California’s cap-and-trade scheme.
3.4 Emissions Trading Models in theEuropean Union
3.4.1 Emissions Trading in the Euro-pean Union [17, ch37, ++]
[Paper is good, but a bit outdated. This mar-ket is changing a lot.]
The purpose of the European Union Emis-sions Trading Scheme (EU-ETS) is to allowcompanies to find the cheapest possible CO2-abatement options. It covers activities suchas electricity generation, steel production, andpaper industry.
32
The EU ETS works as follows:
1. Governments allocate allowances for atrading period (phase I, 2005–07; phaseII, 2008–12; phase III, 2013–?) to coveredcompanies. About 57% of allowances wereallocated to the power and heat sector and43% to industrial installations (which typ-ically do not trade much).
The total allocation is below the expectedemissions in a business as usual scenario.This scarcity guarantees demand and thatthe environmental goals are fulfilled.
2. Once a year, each installation must re-deem allowances corresponding to itsemissions.
3. Each company will have to decide whetherto buy allowances in the market, abateemissions by technical measures, or re-duce production. (But it is unlikely thata plant will be short in the first years ofeach phase).
4. A company that cannot meet its obliga-tions has to pay a fine and buy the missingallowances on the market.
Currently [2008?], most trade is OTC. How-ever, exchanges are expected to become moreimportant, as they eliminate counterparty riskand are reliable sources for market prices. Thetypical size of a deal in both markets is 10 000allowances, corresponding to 10 000 t of CO2.
Price drivers:
• Weather is major driver of electricity de-mand. Higher demand is typically met bysources that emit more CO2.
• More precipitation means more CO2-freehydroelectric power.
• The relative prices of coal, gas, and crudeoil determine the electricity generationmix (gas emits less CO2).
• Economic growth.
• Political and regulatory issues.
In the spot market, delivery and payment aredone within a few business days. In the forwardmarket, December 1st was established as thedelivery date. There is a “banking” arbitrage-free relationship between the prices:
FT = Stei(T−t)
where i is the interest rate. Note that this rela-tion only applies to allowances within the sametrading period because allowances from phaseI cannot be traded in phase II (it is assumedthat there will be no restrictions after 2012).
4 Financial Products and Val-uation (20%)
4.1 Forward Contracts and Ex-change Traded Futures
Terminology. At maturity (T ), the long po-sition party either: (1) buys the underlying as-set for a specified price Ft,T (physical settle-ment); or, (2) receives a payoff ST −Ft,T (cashsettlement).
4.1.1 Behavior of Commodity FuturesPrices [16, ch3, ++]
Relationships between cash (S) and futures (F)prices through time:
1. Parallelism: high correlation between Sand F. This is because the same factorsmust affect S and F when there is thepossibility of storing commodities for de-livery against the contract in the future.However, the correlation (and thereforehedges) are seldom perfect.
2. Convergence of S and F at expiration ofthe futures. This is due to the possibilityof physical delivery.
Relationships between cash (S) and futures(F) prices for several maturities at a given mo-ment:
33
• Contango or carrying charge market:
S < F1 < F2 < . . .
Futures prices are usually at a premiumto cash when there are adequate suppliesin the cash market. This is due to carry-ing charges: storage, insurance, and inter-est costs. The market is at “full carry”when F − S = carrying charge, but usu-ally F−S < carrying charge due to a con-venience yield of holding some inventory.The interest rate is the most volatile of thecarrying costs.
• Backwardation or inverted market:
S > F1 > F2 > . . .
This is caused by a shortage of supply rel-ative to demand in cash markets. Thisencourages sales now rather than in thefuture and thus discourages storage ofgoods.
Examples:
– In the US, the gasoline or driving sea-son lasts from Apr to Aug. Hence,gasoline futures prices are typicallyin contango during the early monthsof the season (Mar–May), but areinverted in the later months (May–Aug) when it is expected that gaso-line will be in short supply. [Decreas-ing F are caused by higher conve-nience yields in the later months dueto the chance of shortages.]
– The NYMEX crude oil futures hasusually been inverted since 1983.
A cash market arbitrage opportunity occurswhen prices in two different markets for thesame commodity differ by more than trans-portation costs between the markets. Exam-ple: move heating oil between NY and London.
A cash/futures arbitrage opportunity occurswhen F > S by more than carrying charges.[aka cash-and-carry arbitrage.] Example:
1. Heating oil: S0 = $0.60, F1 = $0.63, andit costs $0.015 to finance and store 1 gallonper month.
2. Strategy: buy cash, sell futures.
3. One month from now: sell at $0.63, fora profit of +$0.015 per gallon. This canbe done by either: delivering on the fu-tures at F1; or settling the futures finan-cially and selling the oil in the cash mar-ket, (F1 − S1) + S1 = F1.
The basis for a given futures contract (usu-ally the nearby) is:
Basis = Ft,T − St
where St is the cash price for a given locationwhere the commodity is traded. Since thereare typically various such locations, there is aunique basis for each location. Therefore, it ishelpful to decompose the basis into:
Basis = (Ft,T − SDt)︸ ︷︷ ︸StorageBasis
+ (SDt − St)︸ ︷︷ ︸LocationBasis
where SDt is the cash price at the deliverypoint of the futures contract. While the Stor-age basis→ 0 as t→ T , the Location basis typ-ically remains constant. There is also a productbasis when the cash and futures are not exactlythe same commodity (eg, hedging jet fuel withgasoline futures).
Basis changes. In a full carrying charge mar-ket, the basis will decrease systematically at arate approximately equal to carrying costs perunit of time. In an inverted market, S and Fstill have to converge at expiration, but basischanges are unsystematic and unpredictable.
4.1.2 Commodity Forwards and Fu-tures [29, ch6, -]
A synthetic commodity position is created by:
34
1. Going long in a forward contract. Thecash flows are: CF0 = 0, CFT = ST −F0,T .
2. Buying a ZCB with cash flows: CF0 =−e−rTF0,T , CFT = F0,T .
The total CFT = ST . To avoid arbitrage,−CF0 = S0 or
S0 = e−rTF0,T
[Note: this only applies to investment assets,like stocks, bonds, gold, silver, etc. It doesnot apply to consumption commodities, likecopper, oil, etc. The full equation for a con-sumption commodity would need to add stor-age costs (u) and the convenience yield (c):S0 = e−(r+u−c)TF0,T . See Hull [22].]
Using a simple PV relationship for the priceof a commodity, we also have
S0 = e−αT E0[ST ]
where α is the appropriate discount rate. [Doesit make sense to estimate α in the usual way(eg, CAPM) for a consumption commodity?]
Comparing these two equations, we get
F0,T = e(r−α)T E0[ST ]
Hence, the forward price is a biased estimateof the expected spot price. [Downward biasedwhen the return on the underlying has positivecovariance with the market, as r < α⇒ F0,T <E0[ST ]. Example: stock index. See Hull [22].]
Electricity forward prices can show largeprice swings (eg, in day-ahead prices) becauseelectricity is not storable. Variations in elec-tricity forward prices likely reflect variationsin expected spot prices.
Lease rate (l): l = α− g, where g is the ex-pected growth rate of the commodity price. lis the commodity analog to the dividend yieldof a financial asset. If we borrow the asset (inorder to short sell it), we have to pay the leaserate to the lender. Hence, F0,T = S0e
(r−l)T .
[I don’t see the point: l is not observable andit has exactly the same interpretation as theconvenience yield — see eqn (6.11) and ftn 5in the paper. Further, the paper does not giveany real life example of l, though Hull [22] saysthat gold and silver have lease rates (note thathe considers them investment assets, not in-vestment commodities). This formula still ig-nores storage costs.]
Storage costs (u). Let U denote the presentvalue of storage costs per unit. Then, F0,T =(S0 + U)erT . Alternatively, if u denotes stor-age costs that are paid continuously and areproportional to the value of the commodity,
F0,T = S0e(r+u)T
Note that u = −l. [Equality is only guaranteedby no arbitrage for investment assets, as shownnext.]
Cash-and-carry arbitrage for both invest-ment assets and consumption commodities:
C&C 0 TBorrow $ S0 + U −(S0 + U)erT
Buy asset −S0 +ST
Pay storage −U 0Short Fwd 0 F0,T − ST
Payoff 0 F0,T − (S0 + U)erT
Hence, defining u appropriately, no arbitragerequires
F0,T ≤ S0e(r+u)T
Reverse Cash-and-carry arbitrage for an in-vestment asset. The strategy for the holders ofthe asset is
R C&C 0 TSell asset +S0 −ST
Save storage +U 0Lend $ −(S0 + U) +(S0 + U)erT
Long Fwd 0 ST − F0,T
Payoff 0 (S0 + U)erT − F0,T
Note that these are incremental payoffs tothe holders relative to doing nothing (keep thecommodity stored). Alternatively, these are
35
the payoffs to an arbitrageur that short sellsthe asset. He needs to first borrow it from theholders, which means that the holders pay thestorage costs to the arbitrageur. Hence, defin-ing u appropriately, no arbitrage requires
S0e(r+u)T ≤ F0,T
Convenience yield (c). For a manufacturer,holding physical inventory of a consumptioncommodity provides insurance that he cankeep producing. [The convenience yield is thebenefit from holding the physical asset. It re-flects the market’s expectations concerning thefuture availability of the commodity.]
Reverse Cash-and-carry arbitrage for a con-sumption commodity. If the holders of thecommodity sell it, they stop receiving the con-venience yield, hence they only save U − C (ifthey lend it to a short seller, they will onlypay him U −C). Replacing U by U −C in thestrategy, and the defining c appropriately, noarbitrage requires
S0e(r+u−c)T ≤ F0,T
In summary, for a consumption commodity,the no arbitrage region is:
S0e(r+u−c)T ≤ F0,T ≤ S0e
(r+u)T
Thus, the convenience yield only explainsanomalously low forward prices.
[Hull [22] and Clewlow and Strickland[11] define the unobservable c such thatS0e
(r+u−c)T = F0,T .]Basis risk: the price of the commodity un-
derlying the futures contract may move differ-ently than the price of the commodity you arehedging.
4.2 Energy Swaps
Terminology. The swap buyer pays fixedand receives floating. The long/short termi-nology is not clear for swaps, but being a swapbuyer is equivalent to being long in a series offorward contracts.
4.2.1 Energy swaps [27, ch1, ++, inc]
A plain vanilla swap is an agreement whereby afloating price is exchanged for a fixed price overa specified period. There is no transfer of thephysical commodity: differences are settled incash for specific periods usually monthly, butsometimes up to annually. Counterparts:
• Swap Seller: pays the floating leg and re-ceives the fixed leg. Typically, a commod-ity producer that wants to lock in the salesprice.
• Swap Buyer: (opposite). Typically, acommodity consumer that wants to sta-bilise the buying price.
A differential swap exchanges the actual dif-ferential between two products for a fixed ref-erence value. Counterparts:
• Swap Seller: pays the actual floating dif-ferential and receives the fixed differential.
• Swap Buyer: (opposite).
Typical users are refiners that want to hedgechanging margins of refined products and com-panies that need to manage basis risk. Exam-ple: an airline hedges with gasoil futures. Tofix the basis risk, they buy a differential swapon jet minus gasoil at $36/t. If the average(jet - gasoil) is above $36 for a given month,they receive the difference multiplied by themonthly volume specified in the contract.
A refining margin swap or crack swap allowsthe profitability of a refinery to be guaranteedfor a few years forward. In the “crude oil leg”,the refiner is the fixed-price buyer thus guaran-teeing the input price; in the “refined-productsleg”, the refiner is the fixed-price seller thusguaranteing the output price.
A participation swap is similar to a regularswap in that the fixed price payer is fully pro-tected when prices rise above the agreed price,but he “participates” in the downside. Exam-ple: a fuel oil buyer sees the current dip inmarket prices as a good opportunity to hedge
36
its budget for the next year. However, it hasa strong view that prices may go lower and soit wants an instrument that allows it to bene-fit from any downside move without having topay any upfront premium. The company buysa 50% participation swap at $80 per ton. Ifprices rise to $95 it receives the full $15 differ-ence. If prices fall to $70, it would only pay $5rather than the $10 under a regular swap.
Most companies only hedge 40–60% of their1 or 2 years exposure. Some limiting factors onthe use of swaps are illiquidity and accountingissues.
Swaps are useful in the following financingstructures:• Project finance: e.g., to fix the selling
price of an oil field project.
• Pre-export financing: oil-exporting coun-tries pledge future oil production as col-lateral against immediate cash. [This iscash now in exchange for physical oil inthe future — why is it related to swaps?]
• Asset, bond, or equity financing: link cashflows to fuel prices.
(See pricing in Panel 8, p. 35, of the paper).
4.3 Energy Options
4.3.1 Energy options [27, ch2, +, inc]
NYMEX began trading crude oil WTI optionsin Nov 1986. IPE followed with gasoil optionsin Jul 1987. The growth of the options marketwas spurred by the launch of an OTC marketin swaps from 1986.
In the oil market, while exchange options areexercised into futures contracts (which resultin physical delivery if held to maturity), OTCoptions are generally cash settled.
Any individual settlement period for a swapbuyer (pays fixed, receives floating) is equiva-lent to either:• Long forward.
• Long call and short put options.
(Note that this implies that a call and a putmust have equal value when they are bothstruck at the forward price.)
Components of an option’s value:
• Intrinsic value: [maximum of zero andthe] amount the option would pay if ex-ercised immediately.
• Time value: amount due to the possibil-ity that the intrinsic value may increase.Time value is highest when the underlyingis trading at the strike.
Types of option exercise:
• American. Can be exercised at any timeup to maturity. Most exchange-traded op-tions are American, like the energy op-tions on the NYMEX and IPE.
• European.
• Asian. Settle in cash based upon an aver-age price. Most OTC energy options.
Greeks:
• Delta: δ := ∂c/∂S
• Gamma: γ := ∂δ/∂S = ∂2c/∂S2
• Theta: θ := ∂c/∂t
• Vega: v := ∂c/∂σ
Delta hedging. Consider an $18 call on1 000 000 barrels (1 000 futures contracts) ofcrude oil. Assume St = $18 (at-the-money)and δ = 0.517. To delta hedge a long call,a trader would need to sell short 517 futurescontracts at a price of $18 per barrel. If Stchanges, the profit/loss in the long call is com-pensated by the loss/profit in the short futures.
Energy options strategies. “Everyone wantsto buy options until they see what they cost.”The following strategies reduce the cost ofhedging by simultaneously buying and sellingoptions.
• Caps, floors, and collars. Caps(floors) areconsecutive series of call(put) options withthe same strike. A collar is the simulta-neous purchase of a call and the sale of
37
a put, often constructed to have zero up-front cost. If an airline or a gas burningelectric utility buys a collar (= long calland short put), the call strike is the max-imum price it will pay for fuel, while theput strike is the minimum price it will payfor fuel. The advantage is that the pre-mium from selling the floor subsidises thecost of buying the cap. A collar can bethought of as a forward (or a swap) witha band in the middle (the range betweenthe put and the call strikes) where noth-ing happens. A oil producer would wantto short a collar (= sell cap and buy floor).
• Participating collars. The company “par-ticipates” in any favourable price move inthe underlying commodity, while still be-ing fully protected against unfavourableprice movements. The (out-of-the-money)option bought is for a larger quantity[the amount that needs to be hedged?]than the (at-the-money) option sold. Thestrikes are such that the total premiumspaid and received are equal. The cost ofthe “participation” is the less favourableplacement of the option strike prices.
• Participating swaps. Are like participat-ing collars except that the gap betweenthe call and put strikes is eliminated bymoving the strikes to the same point.
• Bull and bear spreads. A bull(bear) spreadis a call(put) that is partly financed by si-multaneously selling back a higher(lower)strike call(put).
• Swaption. A swaption is an option to buy(or sell) a swap. Compared to a cap cov-ering the same period as the swap, thecall swaption is cheaper because after theswaption is exercised, there is two-way riskon the swap, while the cap contains nodownside risk for the buyer. Swaptions aretypically purchased by clients who need
the assurance of a maximum fixed price,but feel that there is a reasonable prospectof a price fall before the expiry of theswaption.
4.4 Exotic Options
..
4.5 Option Valuation and Risk Man-agement
Put-call parity.
• European stock options:
p+ S0 = c+Xe−rT
• European futures options:
p+ F0e−rT = c+Xe−rT
4.5.1 Overview of option pricing for en-ergies [34, ch9, - -, inc]
[Equation 9-3 is about payoffs; it is not the put-call parity, which is a relation between prices.Formula 9-4 is wrong. The terms are not stan-dard and are just more confusing.]
Parity value [is the same as intrinsic value].Call parity value = max(0, S −X).
4.5.2 Option valuation [34, ch10, inc]
The Black model is used to value options thatsettle not on the spot price at the time of theoption’s expiration, but rather on a forwardprice. The spot price is still assumed to fol-low GBM and the valuation formulas are verysimilar to Black-Scholes (see formulas in thepaper).
4.5.3 Risk management of energyderivatives [11, ch9, +]
[Greeks are defined in section 4.3.]
38
Delta Hedging an option involves dynami-cally trading a position in the underlying equalto the negative of the option delta, such thatthe changes in value offset each other.
Example: suppose we have a short call op-tion on a forward contract (−δ = −∂c/∂F ).To delta hedge, we must buy a quantity δof the underlying forward. The value of thehedged portfolio is P = −c + δF , which doesnot change for small ∆F .
Since delta changes continuously, we shouldrebalance continuously; in reality there aretransaction costs, so rebalance only when theunderlying has moved by a significant amount.
Delta for European call options starts at zerofor out-of-the-money, increases to about 0.5 forATM, and reaches almost one for in-the-moneyoptions.
Gamma Hedging neutralizes the sensitivityof our delta hedge to changes in the underlying.This is important for ATM options where δchanges faster. Steps:
1. Trade a second option such that thegamma (γ = ∂2c/∂F 2) of the combinedposition is zero: γ1 + aγ2 = 0.
2. Since this will have residual delta, neutral-ize it by taking a position in the underly-ing equal to the negative of the residualdelta. Note that since forward contractsare linear, they only have delta and nogamma. Consequently, this trade does notmess up the gamma of the overall com-bined portfolio; it only changes delta.
This portfolio needs to be rebalanced much lessfrequently.
Volatility Hedging is similar to gamma hedg-ing, replacing gamma with vega (V = ∂c/∂σ).For delta-gamma-vega hedging, we need evenanother hedge option:
1. Simultaneously find quantities a and bsuch that γ1 + aγ2 + bγ3 = 0 and V1 +aV2 + bV3 = 0.
2. Neutralize the residual delta with a posi-
tion in the underlying.Note that vegas for puts and calls with thesame strike price are the same (this resultsfrom put/call parity).
4.6 Real Option Valuation
..
4.7 Speculation and Spread Trading
4.7.1 Speculation and Spread Trading[16, ch4, ++]
Speculation increases liquidity and price effi-ciency, which facilitates hedging.
Position trading speculation consists of out-right positions in futures. If expect price toincrease, take long position (buy) in futures,for a payoff of Ft+∆t,T − Ft,T . It is difficult tomake money with this strategy because futuresmarkets are very efficient.
Spread trading speculation consists of botha long and a short position in different futurescontracts. Absolute price changes are unim-portant. If the spread X − Y is expected towiden, buy X and sell Y .
Intermarket spreads trading involve the si-multaneous purchase and sale of different butrelated commodities that have a reasonablestable relationship to each other. Examples:• A crack spread creates a “paper refinery”
by buying crude oil and selling gasolineand heating oil futures. A crack spreadposition would be assumed when refinedproduct prices are high relative to crudeoil prices and are expected to fall.
To replicate the average refinery, the ratiois:
– Buy 3 crude contracts.
– Sell 2 gasoline contracts.
– Sell 1 heating oil contract.
The resulting premium ($/barrel) is (H +2G − 3C)/3. A crack spread should be
39
implemented when this value is above$4/barrel (reverse crack if below $3/bar-rel) [the book is from 2002...].
• A spark spread allows generators to lockin a margin by purchasing natural gas fu-tures and selling electricity futures.
• Henry Hub natural gas vs. Per-mian/WAHA Hub natural gas.
• Heating oil vs. gasoline.
• NYMEX heating oil vs. IPE gas oil.
• NYMEX light, sweet crude oil vs. IPE’sBrent crude oil.
• Natural gas vs. propane futures (“frac”spread).
4.8 Hedging Energy CommodityRisks
4.8.1 Different kinds of risk [4, ch3, -]
Price or directional risk is movement on theNYMEX.
Basis or differential risk is the risk due totime or location differences. NYMEX futurescontracts can be delivered any time during afull month at the seller’s discretion, which cre-ates time basis risk for a buyer that needsprompt barrels today.
Availability or supply risk.
Volume risk is most generally associatedwith extreme temperature deviations. Oneway to protect against the possibility of need-ing greater supply is through buying call op-tions. When the risk is on the downside andlower prices, use put options.
4.9 Weather Derivatives
4.9.1 Introduction to weather deriva-tives [12, -]
Weather derivatives are trading OTC since1997 for most US cities. CME is introducing
futures and options on futures on HDD andCDD for 8–10 cities.
Weather options are written on the cumula-tive HDD or CDD over a specified period (typ-ically 1 month). One could buy a CDD optionfor the summer, or a HDD option for the win-ter.
One can also buy or sell a futures contract,such that one counter party gets paid if thedegree days over a specified period are greaterthan the predefined level.
4.9.2 Heating and Cooling DegreeDays [3, +]
A “degree day” is a measure of the averagetemperature’s departure from a human com-fort level of 18 ◦C (65 ◦F).
Heating degree days (HDDs) are defined as18 − T , where T is the average temperatureof a given day. Thus, a day with an averagetemperature of 10 ◦C will have 8 HDD.
Cooling degree days (CDDs) are defined asT − 18. Accordingly, a day with an averagetemperature of 25 ◦C will have 7 CDD.
[In Fahrenheit, the reference temperature is65 ◦F - see Considine [12].]
For both heating and cooling degree days,average temperature of a particular day is cal-culated by adding the daily high and low tem-peratures and dividing by two.
5 Modeling Energy Price Be-havior (10%)
5.1 Introduction to Energy Model-ing
5.1.1 What makes energies so different[34, ch2, -, inc]
What makes energies so different is the ex-cessive number of fundamental price drivers,
40
which cause extremely complex price behav-ior. For example, price depends on location,which does not happen with traditional finan-cial products.
Energy prices display spikes and strongmean reversion. The mean reversion appearsto be a function of either how quickly the sup-ply side of the market can react to “events” orhow quickly the events go away.
Main supply drivers are production capacity(determines long-term prices) and storage limi-tation (causes high short-term price volatility).
Main demand drivers are the convenienceyield and seasonality.
5.2 Data Analysis and EssentialStatistics
5.2.1 Essential statistical tools [34, ch4,- -, inc]
[The lognormal distribution has positive skew-ness or is skewed to the right, i.e., the tail is onthe right side. Skewness := E[(X − X)3]/σ3.]
The quantile-to-quantile (Q-Q) plot lookslike a diagonal line when the random variable isnormally distributed. [What does 4-13 mean?It should = 0 (msr 0 set)!!]
“If a rv is normally distributed, then the val-ues are uncorrelated.” [Absurd! Ex: AR(1).]
5.3 Spot Price Behavior
5.3.1 Understanding and AnalyzingSpot Prices [11, ch2, ++]
Schwartz (1997) model for a mean revertingspot price:
dS/S = α(µ− lnS)dt+ σdz (3)
The long-term mean is eµ. The half-life is thetime taken for the price to revert half way backto its long-term level: t1/2 = ln(2)/α. For α =10, t1/2 = 25 days. Mean reversion rates are
relatively low for most energy prices (exceptelectricity).
Hull and White (1988), Heston (1993), andothers, model for stochastic volatility :
dSt/St = µdt+ σtdz
dσ2t = a
(m− σ2
t
)dt+ ξσtdw
Model for jumps with mean reversion (goodfor electricity):
dS/S = α(µ− lnS)dt+ σdz + κdq
where κ is the random jump size and dq is adiscrete {0, 1} process.
The following variables may display season-ality : price, volatility, mean reversion rate,jump frequency and jump volatility.
5.3.2 Spot price behavior [34, ch5, -,inc]
Shortlist of possible models:• Lognormal price model:
dSt/St = µdt+ σdzt
Famous in nonenergy markets. Guaran-tees that prices will never be negative.Width of distribution increases with “timeto maturity (T )”.
• Mean reversion in log of price: developedby Schwartz and Vasicek - see equation(3). Spot prices are always positive.
Performs not too badly in capturing thedistribution width [for short horizons], butdoes a poor job of capturing the distribu-tion’s tails. This can be improved withjumps.
The drawback of this single-factor mean-reverting model is that it forces the im-plied Black-equivalent average volatility ofthe price distribution to go to zero overa long period of time (as the spot priceapproaches the immobile long-term meanlevel).
41
• Mean reversion in price. (Pilipovicmodel). The spot price is assumed tomean-revert toward an equilibrium pricelevel, which is itself lognormally dis-tributed. The volatility of the spot pricenever goes to zero. [See paper for eqns.]
Energy markets require mean-revertingmodels. Both models give negative autocor-relation for the changes in spot prices, whichis important for energy markets, particularlyelectricity.
[Box at the end explains reasonably well Lo-cational Marginal Pricing in electricity mar-kets.]
5.4 Forward Curve Modeling
5.4.1 Energy forward curves [11, ch4,++]
The full cost of carry relationship for an energyis:
Ft,T = Ste(r+u−c)(T−t)
Depending on the relative size of storage costs(u) and convenience yield (c) the resulting for-ward curve can be in contango or backwarda-tion. [See section 4.1 for more details.]
Oil can be in contango sometimes and inbackwardation at other times. The natural gasforward curve typically displays a seasonal pat-tern (higher prices in winter).
Electricity forward prices exhibit the mostcomplicated forward curves, with seasonal,daily, and hourly patterns. These complicatedpatterns arise because electricity is not storableand because electricity markets are segmented.
Since most electricity contracts are illiquid,other methods are used to construct the for-ward curve:
• Arbitrage approach. Although electricitycannot be easily stored, the fuel used togenerate electricity can be stored. Hence,a basic electricity forward curve can be ob-
tained via:
Power price = Fuel price×Heat Rate
where the heat rate is defined in (1).
• Econometric approach. Prices are esti-mated with econometric models based onkey variables such as fuel cost, weatherpatterns, etc. But note that the outputis a forecast of spot prices; it is not a for-ward price.
• Spot price modelling approach. Forwardprices are derived from assumptions aboutthe stochastic processes for the spot en-ergy price and other key variables (eg, thelong-term price, the convenience yield, orinterest rates). This approach is similar tointerest rate models.
5.4.2 Forward curve models [11, ch8,++, inc]
Forward curve models represent all the forwardprices simultaneously rather than just the spotprice. A simple model is:
dF (t, T )/F (t, T ) = σ(t, T )dz(t) (4)
There is no drift because futures and forwardshave zero initial investment.
A simple specification that ensures thatshort-dated forward returns are more volatilethan long-dated forwards is σ(t, T ) =σe−α(T−t).
However, the real behaviour of the curve ismore complex and we need more factors:
dF (t, T )/F (t, T ) =
n∑i=1
σi(t, T )dzi(t)
These risk factors can determined by principalcomponents analysis (PCA). Typically, thereare n = 3 risk factors, which act to shift, tilt,and bend the curve.
42
Since S(t) = F (t, t), we can derive a processfor the spot price from the process for the for-ward price. [See the paper for equations.] Oneimportant result is that the simple model in(4) with σ(t, T ) = σe−α(T−t) implies the mean-reverting spot price in (3), albeit with a timedependent drift term. If α = 0, we obtain theBlack (1976) model.
Seasonality for gas and electricity can be in-corporated by
dF (t, T )/F (t, T ) = σS(t)n∑i=1
σi(T − t)dzi(t)
where σS(t) is the time dependent spot volatil-ity.
[See the paper for option pricing formulas.]
5.5 Estimating Price Volatility
5.5.1 Volatility Estimation in EnergyMarkets [11, ch3, ++]
GBM is not a good model for energy pricesbecause:
• Energy commodities are inputs to produc-tion processes and/or consumption goods;they are not investments assets. For ex-ample, electricity prices may be negative,which is not allowed in GBM.
• Seasonality.
• Jumps.
• Mean reversion. Prices may depart fromthe cost of production in the short termdue to abnormal market conditions, but inthe long term, the supply will be adjustedand the prices will revert to the cost ofproduction.
However, a simple mean-reversion processlike Vasicek’s (1977) may not perform wellbecause:
– The speed of mean reversion may bedifferent below and above the mean.
– In many markets, especially electric-ity, departures to the upside are morelikely than to the downside.
– A price spike is frequently neutral-ized by a following spike of oppositesign.
• Prices of energy commodities behave dif-ferently during different periods of theirlives. Eg, the volatility of forward con-tracts increases as they get closer to theirmaturity.
If the underlying price follows a GBM (re-turns are iid), volatility can be estimated fromhistorical data as follows:
1. Calculate [daily] logarithmic price returns[continuously compounded returns]: St =St−1e
r ⇒ r = ln(St/St−1). Note thatr0,T := ln(ST /S0) = r1 + r2 + . . .+ rT .
2. Calculate standard deviation of daily se-ries, σd .
3. Annualize: σ2y = 250σ2
d ⇒ σy =√
250σdIf the underlying price follows a mean-
reverting Ornstein-Uhlenbeck process, dS =α(S − S)dt + σdz, volatility can still be esti-mated from historical data by considering anAR(1) discretization. [See formulas in the pa-per].
A leptokurtic distribution has fat tails, ie, itskurtosis is higher than in the normal distribu-tion. Eg, electricity prices have fat tails dueto jumps. Time varying parameters can alsocause the unconditional distribution to lookleptokurtic.
An heteroskedastic process has time depen-dent volatility, be it deterministic or random.
Models for stochastic volatility. Assume re-turns are rt = k+ut, where k is a constant andut = σtεt, with εt ∼ N(0, 1). Alternatives forthe variance:
1. ARCH(q): σ2t = a0 +a1u
2t−1 + . . .+aqu
2t−q
2. GARCH(p,q): σ2t = a0 +
∑pi=1 biσ
2t−i +∑q
i=1 aiu2t−i
43
5.5.2 Volatilities [34, ch8, - -, inc]
The volatility of a price process is always as-sumed to represent the annualized standarddeviation of returns.
We can back out a rudimentary term struc-ture of implied volatilities from several optionson the same underlying. Suppose we have twooptions on the same 3-month futures:
1. Option 1 expires in 1 month, has impliedvolatility σ0,1.
2. Option 2 expires in 2 months, has impliedvolatility σ0,2.
We can then estimate σ1,2 from
σ20,2 = (σ2
0,1 + σ21,2)/2
Referring to the same 3 models of section5.3.2:• Single-factor lognormal price model
(GBM). Volatility is the same for spotand all forward prices. Spot and allforward prices are perfectly correlatedwith each other. None of this is consistentwith real energy prices.
• Single-factor log-of-price mean-revertingmodel. The volatility of the forward pricegoes to zero as the maturity date goes toinfinity. Correlations remain perfect be-cause it is still a single-factor model.
• Two-factor mean-reverting model.(Pilipovic model). Correlations be-tween spot and forward prices are lessthan one.
6 Risk Evaluation and Man-agement (15%)
6.1 Value-at-Risk and Stress Testing
6.1.1 Value-at-risk [11, ch10, +, inc]
The basic VaR model assumes that marketvariable returns are normally distributed (or
follow a random walk):
rt = µt + σtεt, εt ∼ iidN(0, 1)
where rt is a log return.Volatility estimation:• Simple Moving Average:
σ =
√√√√ 1
N
N∑i=1
(ri − µ)2
• Exponentially Weighted Moving Average:
σ =
√√√√ 1∑Ni=1 λ
i−1
N∑i=1
λi−1(ri − µ)2
The decay factor is typically 0.9 < λ <1.0. Older returns get exponentially lessweight. Note that
∑Ni=1 λ
i−1 ∼= 11−λ , as in
the RiskMetrics formula (but not good forλ close to 1!!!).
The corresponding formulas can be used to es-timate covariances.
VaR methodologies:1. Variance-Covariance or Delta VaR. As-
sumes that returns are normally dis-tributed. Derivatives are represented interms of a Delta equivalent position in theunderlying asset, ie, the weights in theportfolio are modified to wi = ∂Vi
∂Siwi (for a
basic instrument that is not a derivative,∂Vi∂Si
= 1). The variance of the portfolio is
the usual σ2p = w′Σw. Hence,
V aR = z × σ$p
z is the critical level for a given con-fidence level. For example, z(95%) =1.65, z(99%) = 2.326.
Examples:
• 100 M$ spot crude oil position. Stan-dard deviation of daily returns ofcrude oil price is 2.5%. The 1-day
44
VaR with a confidence level of 95%is
V aR = 1.65× 0.025× 100 M$
• For a portfolio with 2 underlyingmarket variables,
V aR2p = V aR2
1+V aR22+2ρV aR1V aR2
2. Delta-Gamma VaR. The change in valueof derivatives are approximated with moreterms: δ, γ = ∂2V/∂S2, and also θ =∂V/∂t. The portfolio distribution is nolonger normal [see paper for formula], sothe VaR calculation becomes more com-plicated. The main point of this approachis to compute the change in value of an op-tion without having to use the full optionpricing model. This can be integrated inthe Monte Carlo method to speed up thesimulations.
These methods up to here do not providethe accuracy required for energy markets.
3. Monte Carlo simulation. Jumps, stochas-tic volatility, or knowledge of future events(eg, changes in the operation of a market)can be easily incorporated.
4. Historical simulation. Good alternative ifreturns are not well described by the nor-mal distribution or other tractable alter-natives, as is likely for energy markets.
VaR estimates should be backtested : checkhow often the actual returns exceed the VaRforecast.
6.1.2 Incorporating stress tests intomarket risk modeling [1, +]
Stress tests are exercises to determine thelosses that might occur under unlikely butplausible circumstances, i.e., under rare or ex-treme events. Stress tests respond to VaR ex-cessive dependency on history or unrealisticstatistical assumptions.
Types of stress tests:
1. Uses scenarios from recent history.
2. Uses predefined scenarios that haveproven to be useful in practice. Eg, fallin stock index of x standard deviations.
3. Mechanical-search stress tests.[?]
Problems with stress tests:
• Choice of scenarios is subjective.
• Results are difficult to interpret and to acton because there is no probability for theevent concerned.
• VaR and Stress Tests are often presentedas two separate measures of risk. How-ever, the two methods can be integratedby assigning (subjective) probabilities tothe stress scenarios.
• Stress tests often ignore the correlationbetween the stressed prices and otherprices.
6.2 Credit and Counterparty Risk
6.2.1 Credit risk management [7, ch6.3,-, inc]
Credit risk is the risk that a counterparty can-not fulfil his contractual obligations. Creditrisk exposure results from:
• Settlement risk: the possibility that acounterparty cannot pay the obtainedbenefits, e.g. the delivered energyamount.
Example: at some point before the matu-rity of a forward contract, the risk is thepresent value of the terminal payoff, as-suming that ST is the current spot price.
• Replacement risk: the possibility that anew replacement contract will have to beentered into, under potentially worse mar-ket conditions.
Credit risk can be quantified through:
• Risk-at-Default. [= EAD x LGD ?]
45
• Expected loss.
• Potential exposure: maximum credit lossto a given counterparty with a given confi-dence level. Obtained by generating mar-ket prices scenarios. Useful for settingcredit limits.
• Credit VaR.
Credit risk can be reduced through:
• Margining agreements. Most powerfulmethod. [Works like in exchange-tradedproducts.]
• Transfer an OTC transaction into an regu-lar exchange-traded futures contract. TheEuropean Energy Exchange allows this.
• Additional collateralization.
• Countertrade.
• Price adjustment [?].
6.2.2 Defining counterparty credit risk[18, ch2, ++, inc]
Counterparty risk is the risk that a counter-party in an OTC derivatives transaction willdefault prior to expiration of a trade and willnot therefore make the current and future pay-ments required by the contract. Since the fu-ture value of the derivative contract is uncer-tain, each counterparty has risk to the other.
Traditionally, credit risk has been associatedonly with lending risk. This is the risk thatwe don’t get our money back. It applies toloans, bonds, mortgages, credit cards, and soon. Only one party takes lending risk and eventhe amount is fairly predictable.
Metrics for credit exposure:
• Exposure is the maximum between zeroand the current Mark-to-Market(MtM) ofthe position.
• Expected MtM is the expected value of atransaction for some future time.
• Expected Exposure is the average of pos-itive MtM values at some future time.Note that E[MtM ] < E[E].
• Potential Future Exposure is the worse ex-posure distribution for a given confidencelevel (similar to a VaR).
• Effective Expected Exposure is a nonde-creasing time series of E[E].
6.2.3 Mitigating counterparty creditrisk [18, ch3, ++, inc]
Termination gives the possibility that an in-stitution can terminate a trade prior to theircounterparty going bankrupt. It may exist asan option or be conditional on certain condi-tions being met (e.g., ratings downgrade).
Close-out allows the unilateral terminationof all contracts with the insolvent counterpartywithout waiting for the bankruptcy process tobe finalized. It is often combined with nettinginto a single contract.
Netting is the ability to offset amounts dueat termination of individual contracts betweenthe same counterparties when determining thefinal obligation. Netting comes into force inthe event of a bankruptcy. Can be contractedbilaterally or multilaterally. Long options withupfront premiums do not give any benefit fromnetting because their MtM will never be nega-tive. However, they may still be worth puttingunder a netting agreement to offset negativeMtM of other instrument within the same net-ting set in the future.
Collateral is an asset supporting a risk in alegally enforceable way. Typical assets: cash(most common), bonds, equity.
6.3 Enterprise Risk Management
..
46
6.4 Case Studies in Risk Manage-ment
6.4.1 The collapse of Amaranth Advi-sors [10, ++, inc]
Amaranth Advisors was a large-sized hedgefund that failed in September 2006 due tolosses in natural gas futures and options.
They made a general bet that winter naturalgas prices would rise, while nonwinter naturalgas prices would increase to a lesser degree,referred to as the long winter, short non-winterspread trade.
Their trades had high levels of market andliquidity risk, and also funding risk. TheirVaR numbers underestimated the risk. Someof their traders were in a different city thanrisk managers.
6.4.2 The Case for Enron [37, +, inc]
Enron’s Board of Directors “failed to monitor... ensure ... or halt abuse.” Sometimes theBoard “chose to ignore” problems, other timesit “knowingly allowed Enron to engage in high... risk practices.”
At Enron, risk management neither providedaccurate information nor ensured accountabil-ity.
7 Current Issues in Energy(10%)
7.0.3 The World’s Greatest Coal Arbi-trage: China’s Coal Import Be-havior and Implications for theGlobal Coal Market [32, -]
[They do not use “arbitrage” in the usual sense.The paper simply says that Chinese consumersbuy coal from the cheapest source: domestic orinternational.]
Coal is produced in the North of China andmoved to the consumption centers in the South
by rail and sea. Transport is expensive, repre-senting 50–60% of the final price. During 2009,it was cheaper to import coal from Indonesia,Australia, and Russia. Hence, Chinese importsaccounted for 15% of all globally traded coalin 2009, despite China still being the largestcoal producer. International coal prices havesince recovered and the import window beganto close by summer 2010.
This highlights the fact that, since China hasa massive domestic coal market, China’s will-ingness to import when international prices arelower than domestic prices will move these twoprices closer to parity.
7.0.4 Oil Scarcity, Growth and GlobalImbalances [26, +, inc]
Oil is considered scarce when its supply fallsshort of a specified level of demand, over a longperiod. Oil scarcity is reflected in the marketprice, relative to the price of other goods.
Scarcity arises from continued tension be-tween rapid growth in oil demand in emerg-ing economies and the downshift in oil supplytrend growth.
Real oil prices have not trended persistentlyup or down in 1875–2010. Instead, prices haveexperienced slow-moving fluctuations aroundlong-term averages. This suggests that periodsof oil scarcity have been long lasting but havecome to an end, and that investment, technol-ogy, and discovery are eventually responsive toprice signals.
Energy consumption will depend largely onGDP growth. However, the relation differsacross countries: linear for emerging markets,but flatter for high-income countries.
The paper concludes that gradual and mod-erate increases in oil scarcity may not presenta major constraint on global growth in themedium to long term.
47
References
[1] J. R. Aragones, C. Blanco, and K. Dowd.Incorporating stress tests into market riskmodeling. Institutional Investor, 2001.[cited in p. 45]
[2] J. T. Bartis, F. A. Camm, and D. S. Or-tiz. Producing Liquid Fuels from Coal:Prospects and Policy Issues. RAND, 2008.[cited in p. 7, 8]
[3] K. Baumert and M. Selman. Data Note:Heating and Cooling Degree Days. WorldResources Institute, 2003. [cited in p. 40]
[4] P. C. Beutel. Surviving Energy Prices.PennWell Books, 2005. [cited in p. 40]
[5] Bloomberg New Energy Finance. GlobalTrends in Renewable Energy Investment,2011. [cited in p. 30]
[6] Bunkerworld. D2 and No.2 Diesel Fuel:An Introduction, 2009. [cited in p. 6]
[7] M. Burger, B. Graeber, and G. Schindl-mayr. Managing Energy Risk: An Inte-grated View on Power and Other EnergyMarkets. Wiley, 2007. [cited in p. 45]
[8] A. Chambers. Renewable Energy in Non-technical Language. PennWell, 2004. [cited
in p. 19]
[9] V. Chandra. Fundamentals of NaturalGas: An International Perspective. Pen-nWell Books, 2006. [cited in p. 9, 10, 11, 12]
[10] L. Chincarini. A Case Study on Risk Man-agement: Lessons from the Collapse ofAmaranth Advisors L.L.C. Journal of Ap-plied Finance, 2008. [cited in p. 47]
[11] L. Clewlow and C. Strickland. EnergyDerivatives: Pricing and Risk Manage-ment. Lacima, 2000. [cited in p. 36, 38, 41,
42, 43, 44]
[12] G. Considine. Introduction to WeatherDerivatives. Aquila Energy, 2001? [cited in
p. 40]
[13] P. Coy. The Prospect for Safe Nuclear.Bloomberg Businessweek, March 24, 2011.[cited in p. 22]
[14] Department of Energy. Liquefied Natu-ral Gas: Understanding the Basic Facts,2005. [cited in p. 13]
[15] D. W. Edwards. Energy Trading and In-vesting. McGraw-Hill, 2010. [cited in p. 8, 16,
25, 26, 27]
[16] S. Errera and S. L. Brown. Fundamen-tals of Trading Energy Futures & Options,2002. [cited in p. 33, 39]
[17] F. Fabozzi. The Handbook of CommodityInvesting. John Wiley & Sons, 2008. [cited
in p. 13, 32]
[18] J. Gregory. Counterparty credit risk. Wi-ley, 2010. [cited in p. 46]
[19] C. Groobey, J. Pierce, M. Faber, andG. Broome. Project Finance Primerfor Renewable Energy and Clean TechProjects. Wilson Sonsini Goodrich &Rosati, 2010. [cited in p. 29]
[20] C. Harris. Electricity Markets: Pricing,Structures and Economics. Wiley, 2006.[cited in p. 17]
[21] G. Heal. The Economics of Renewable En-ergy. Review of Environmental Economicsand Policy, 2009. [cited in p. 28]
[22] J. C. Hull. Options, Futures, and otherderivatives. Pearson, 2009. [cited in p. 35, 36]
[23] S. Hunt. Making Competition Work inElectricity. Wiley, 2002. [cited in p. 18, 22,
23, 24]
48
[24] N. J. Hyne. Nontechnical Guide toPetroleum Geology, Exploration, Drilling,and Production. PennWell, 2001. [cited in
p. 3]
[25] Institut Francais du Petrole. Oil, GasExploration, and Production: Reserves,Costs, Contracts. (Ch 3), 2007. [cited in
p. 2]
[26] International Monetary Fund. OilScarcity, Growth and Global Imbalances,2011. [cited in p. 47]
[27] V. Kaminski. Managing Energy PriceRisk. Risk Books, 2004. [cited in p. 36, 37]
[28] W. L. Leffler. Petroleum Refining in Non-technical Language, 3rd Edition. Pen-nWell, 2000. [cited in p. 6]
[29] R. McDonald. Derivatives Markets. Pear-son Education, 2006. [cited in p. 34]
[30] K. Medlock. Impact of Shale Gas Devel-opment on Global Gas Markets. Wiley Pe-riodicals, 2011. [cited in p. 14]
[31] T. O. Miesner and W. L. Leffler. Oil andGas Pipelines in Nontechnical Language.PennWell, 2006. [cited in p. 4, 5]
[32] R. Morse and G. He. The World’s Great-est Coal Arbitrage: China’s Coal ImportBehavior and Implications for the GlobalCoal Market. SSRN, 2010. [cited in p. 47]
[33] R. L. Nersesian. Energy for the 21st Cen-tury: A Comprehensive Guide to Con-ventional and Alternative Sources. M.E.Sharpe, 2007. [cited in p. 20, 31]
[34] D. Pilipovic. Energy Risk: Valuing andManaging Energy Derivatives. McGrawHill, 2007. [cited in p. 38, 40, 41, 44]
[35] PriceWaterhouseCoopers. Today’s LNGMarket Dynamics, 2010. [cited in p. 14]
[36] Purvin and Gertz. The Role of WTI as aCrude Oil Benchmark, 2010. [cited in p. 5]
[37] R. E. Rosen. Risk Management and Cor-porate Governance: The Case of Enron.Connecticut Law Review, 2003? [cited in p.
47]
[38] D. Schlissel and B. Biewald. NuclearPower Plant Construction Costs. SynapseEnergy Economics, 2008. [cited in p. 21]
[39] J. Speight. Handbook of Coal Analysis.Wiley-Interscience, 2005. [cited in p. 15, 16]
[40] G. Timilsina and A. Shrestha. Biofuels:Markets, Targets and Impacts. The WorldBank, 2010. [cited in p. 31]
[41] M. Toman, A. E. Curtright, D. S. Ortiz,J. Darmstadter, and B. Shannon. Uncon-ventional Fossil-Based Fuels: Economicand Environmental Trade-Offs. Rand,2008. [cited in p. 6]
[42] World Bank. State and Trends of the Car-bon Market, 2011. [cited in p. 32]
[43] C. Wright and R. Gallun. Fundamentalsof Oil and Gas Accounting. PennWell,2008. [cited in p. 2, 3]
49