PORTFOLIO OPTIMIZATION FOR OPEN ACCESSCONSUMERS/DISCOMS

DEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING

INDIAN INSTITUTE OF TECHNOLOGY KANPUR

2017

15-05-2017 1

By

Dr. PARUL MATHURIAPOST DOCTORAL FELLOW

BID AREAS IN INDIA

1 N1 North Region Jammu and Kashmir, Himachal Pradesh,Chandigarh, Haryana

2 N2 North Region Uttar Pradesh , Uttaranchal, Rajasthan, Delhi

3 N3 North Region Punjab

4 E1 East Region West Bengal, Sikkim, Bihar, Jharkhand

5 E2 East Region Orissa

6 W1 West Region Madhaya Pradesh

7 W2 West Region Maharashtra, Gujarat, Daman and Diu, Dadarand Nagar Haveli, North Goa

8 W3 West Region Chhattisgarh

9 S1 South Region Andhra Pradesh, Telangana, Karnataka,Pondicherry (Yanam), South Goa

10 S2 South Region Tamil Nadu, Pondicherry (Puducherry),Pondicherry (Karaikal), Pondicherry (Mahe)

11 S3 South Region Kerala

12 A1 North EastRegion

Tripura, Manipur, Mizoram, Nagaland

13 A2 North EastRegion

Assam, Arunachal Pradesh, MeghalayaSource: IEX

VOLATILITY

Source: IEX

HISTORICAL DATA OF MCP

• APRIL 2013-1017

Source: IEX

WHY ELECTRICITY PRICES REPRESENTS

HIGH VOLATILITY ?ISSUES

Demand supply balance

Non-storable nature of electricity

Trading decisions are made well in advance

Prices depends upon the real time conditions

REASONS

Uncertain demand

Availability of production units & network components

Power production of non-dispatchable generators

Availability of generation resources

Energy prices of other markets such as fuel, emission

Legal reasons (market rules & structure)

Others

15-05-2017 5

15-05-2017 6

Timeline of Participation

more than one day ahead one day ahead

Intraday Market

real-timeoperation

Schedulingown generation

for real-time

Day Ahead Market

ForwardMarket

Hedging against the price risk & optimizing the financial part of the power portfolio

Short termMedium termLong term

more than a year Week to year

Construction & Investment

Planning

Long Term Power Purchase

Agreements

Optimizingphysical partof the power

portfolio

Balancing Market

MARKET TIMEFRAME

PERFECT MARKET

• Many Buyers– many eligible consumers/retailers with the

willingness & ability to buy the product at A certain price

• Many Sellers– with the willingness & ability to supply the product at

A certain price

• No Market Power – due to competition no seller can abuse his

position & control prices

• Sufficient Liquidity – sufficient traders so that planned trading is

achievable

• Price Taker – firms aim to sell where marginal costs meet marginal

revenue

• Regular Market Updates – for both consumers & producers

• Homogeneous Products – the products of the different firms are

similar15-05-2017 7

RISK & UNCERTAINTY

15-05-2017 8

• RISK

A chance that future value of considered parameter would be different

than expected

Viewed as A “negative”

Possibility of suffering harm or loss

Costs of future uncertainty

• REASONS

No information about future events at the time of planning

Exact estimation is not possible

UNCERTAINTY SOURCES INCLUDES

Technical, Institutional & Legal issues

RISK MANAGEMENT

METHODOLOGY THAT MAKE BEST USE OF AVAILABLE

RESOURCES

• THREE STEPS PROCESS

Risky v/s Risk Free trading options

MANY POSSIBLE OBJECTIVES:

• To minimize exposure to risk

• To maximize profit for A controlled level of risk

• Optimum selection of risk-return trade-off

15-05-2017 9

RISK IDENTIFICATION RISK ASSESSMENT RISK CONTROL

RISK CONTROL V/S RISK MITIGATION

• MANAGEMENT

• Diversification

• Risk sharing

• Uncertain outcomes are

correlated to reduce

certain variability

• Interdependency

• AVOIDANCE

• Hedging

• Contingent claims

• Contractual arrangement as

insurance

• Controlling financial

consequences

RISK CONTROL BY DIVERSIFICATION

• Diversification is about diversifying the investment in multiple trading

options, so that exposure to risk associated with any particular asset is

limited

• This concept is applied through portfolio construction by investing energy

in available different trading options.

DIVERSIFICATION

DERIVATIVE TRADING/ HEDGING

• Having a Position In Security Using Derivatives

• Trading with Financial Instruments or Contracts (Agreements) such

as Forward, Future , Option , Swap, CfD, FTR Or TCC

• Limitations

– Market Of Hedging Contracts Is Limited

– Requires Additional Payment

– Restricts Opportunities For Higher Profit

15-05-2017 12

PORTFOLIO

• Energy combination of available trading approaches

• Aiming to maximizing participants’ benefits (profits/ returns/ cost)

& minimizing the corresponding risk

• Substantially reduces the variability of returns without an

equivalent reduction in expected returns

• There is a reward for bearing risk

13

PORTFOLIO OPTIMIZATION

MARKET MECHANISM

• Two Types Of Markets

– PHYSICAL MARKET

• Spot Market (Exchange)

• Bilateral Contracts (OTC)

– FINANCIAL MARKET

• Forward, Future , Option ,

Swap, CfD, FTR Or TCC

Derivative Instruments

15-05-2017 14

GenCos

Power Pool

Loads

Bilateral/OTC Transactions

Pool

Trading

Mandatory Transaction Notification

Transactions are scheduled by

MO+SO

Day-ahead Market

Adjustment Market

Balancing Market

PoolOTC (Over the

counter ) trading

Exchange Traded

Derivatives

FORWARD

FUTURE

OPTION

SWAP

MARKET PRODUCT PORTFOLIO INDIA

Source: PPT 2016, Mr. Prasanna Rao, IEX

BUYERS IN ELECTRICITY MARKET

Buyers

Open Access Consumers

Captive

Consumers

DisComs

Retailers/ Aggregators

ALLOWED TO TRADE IN POWER EXCHANGE

• With Higher Voltage Grade

• Larger Power Consumption

• Procures Electricity for Forecasted

Demand

• Risk of price

• Risk of availability of transmission

corridor

• Risk of getting cleared in market

OBJECTIVE

• Minimize Total Purchasing Cost

• Minimize Risk

RETAILERS V/S DISCOMS

15-05-2017 17

• Retailers are subsidiary of a DISCOM

• Manage two sets of contracts, on supply & demand side

• Supply Side: Electricity procurement from various contracts and

pool for fulfilling customer demand

• Demand Side : Obliged to serve varying customer demand

• Retailer’s RM problem is basically bi-level optimization problem

– Purchase Cost Minimization

– Selling Price Determination with consideration of elastic nature

of demand

POWER PROCUREMENT PROBLEM

• Participate in wholesale trading

• Procures electricity for its known

demand

• Optimally decide its mix of

electricity purchase from

– Pool, (day ahead )

– Bilateral contracts (local and

non-local)

– Self production

• Free to purchase from any

supplier, irrespective of its

location

• Prices are correlated with each

other

15-05-2017 18

Large Consumer

Supplier 1

Supplier 2

Supplier 3

Self Generation

Spot Market

PROCUREMENT COST

• Bilateral contract, with home location supplier

• Bilateral contract with supplier of non-home location would be

• Spot market

• Self-generation Facility

• Total electricity procurement cost

1 1, 1,

1

1T

B B B

t t

t

C P for i

, 1, , ,

1

2 ~T

B B S S B

i i t t i t i t

t

C P for i n

1,

1

TS S S

t t

t

C P

2

1

( ) ( )T

G G G su

t t t t

t

C c u b P a P c

1

nS G B

P i

i

C C C C

15-05-2017 19

PURCHASE PORTFOLIO SELECTION

– Expected Procurement Cost

– Risk of Cost

– Minimize Risk Weighted Cost

0 0

1

N

P i i

i

E C w C w E C

2 2

1 1 1 1 1

, ,N N N N N

P i j i j i i i j i j i ji j i i j

w w Cov C C w Var C w w Cov C C

2min P PZ E C

0

1N

i

i

w

0iw

2

2 2 2 2

( ) 2 , ,n n n n

S B S B B B

P P i i i j

i i i j i j

Var C Var C Var C Cov C C Cov C C

1

2

nG B S B

P i

i

E C C C E C E C

15-05-2017 20

OVERALL OPTIMIZATION PROBLEM

,

2

, , , ,min .su

i t t tP Pw c u i t

Z E C

,

1

nS G B

t t t i t

i

PD P P P t

1

su su

t t tc c u u t

min max

G G G

t t tP u P P u t

1

G G up

t t tP P R u t

1 1

G G dw

t t tP P R u t

min , , max ,

B B B

i i t i t i i tP v P P v t

, 0S su

t tP c t

,, 0,1t i tu v t

• OBJECTIVE FUNCTION

• POWER BALANCE CONSTRAINT

• STARTUP COST

• GENERATION LIMITS

• RAMP UP LIMIT

• RAMP DOWN LIMIT

• LIMITS ON BILATERAL CONTRACTS

• VARIABLE DECLARATION CONSTRAINT

15-05-2017 21

CASE STUDY

Contract Index Location Contracted Price Minimum Limit per hour Maximum Limit per hour

Contract 1 APS 52 $/ MWh 60 MW 400 MW

Contract 2 PECO 56.5 $/ MWh 20 MW 200 MW

Contract 3 DOM 58.5 $/ MWh 50 MW 500 MW

Total capacity 120 MW

Minimum power output 20 MW

Ramp rate 80 MW/h

Quadratic cost 0.01 $/MW2h

Linear cost 42 $/ MWh

No-load cost $ 600

Start-up cost $ 200

TABLE II Specifications for Self-Generation Facility

Spot Market Contract 2 Contract 3

Spot Market 1207830135 -96097141.9 -382901659.8

Contract 2 -96097141.9 71896411.19 40024748.14

Contract 3 -382901659.8 40024748.14 708777796.3

TABLE III Variance-Covariance Matrix between Uncertain Costs at 0.0001

Large Consumer located at APS

Case Study Of PJM Electricity Market

Planning Period Is 120 Hours, With Each Hour As A Trading IntervalTABLE I Specifications for Bilateral Contracts

15-05-2017 22

CASE STUDY…

20

30

40

50

60

70

80

90

100

110

1 11 21 31 41 51 61 71 81 91 101 111

Pri

ce in

$/M

Wh

Hours

APS DOM PECO

390

410

430

450

470

490

510

530

550

570

1 11 21 31 41 51 61 71 81 91 101 111

Dem

and

in M

W

Hours

Demand dataDay ahead LMPs of three different locations

38

40

42

44

46

48

50

52

54

56

1 11 21 31 41 51 61 71 81 91 101 111

Pri

ce $

/MW

h

Hours

Contract 1 Contract 2 Contract 3

Hourly expected procurement price from risky bilateral contracts15-05-2017 23

RESULTS

2.2

2.3

2.4

2.5

2.6

2.7

2.8

2.9

3

0.5 1.5 2.5 3.5 4.5 5.5 6.5

Exp

ecte

d P

ort

folio

Co

st $

X1

06

Standard Deviation $X104

Scenario IScenario II

α=0.1

α=0

Electricity purchase from different contracts for various values of α

0

5

10

15

20

25

30

35

40

0 0.002 0.004 0.006 0.008 0.01

Trad

ed P

ow

er in

MW

hX

10

3

Risk weighing factor α

Self-generation Contract 1Self-generation II Contract 1 II

0

5

10

15

20

25

30

0 0.002 0.004 0.006 0.008 0.01

Trad

ed P

ow

er in

MW

h X

10

3

Risk weighing factor α

Spot Market Contract 2 Contract 3

Spot Market Contract 2 Contract 3

(b) Risk-free Procurement Options

(a) Risky Procurement Options

Efficient Frontier

15-05-2017 24

SCENARIO I WITH CORRELATION

SCENARIO II WITHOUT CORRELATION

RESULTS…

Mix of electricity purchase for each trading interval at α =0

0

100

200

300

400

500

600

1 21 41 61 81 101

Ener

gy in

MW

Hours

Spot Market Self Generation Contract 1 Contract 2 Contract 3 Demand

0

100

200

300

400

500

600

1 21 41 61 81 101

Ener

gy in

MW

Hours

Spot Market Self Generation Contract 1 Contract 2 Contract 3 PD

Mix of electricity purchase for each trading interval at α =0.0115-05-2017 25

OPEN ACCESS CONSUMER: INDIAN CONTEXT

.

5/15/2017 26/16

Open Access Consumer

Short term power trading

Unscheduled Interchange (UI)Mechanism

UI Charge for deviation fromScheduled withdrawal

Renewable purchase obligations (RPO)

Price uncertainty and

demand flexibility

Frequency linked UI charge

FiT

REC

RPO

PROBLEM DESCRIPTION

• UI Mechanism

• Part of Availability Based Tariff

• Penalty for deviation from schedule

(against grid frequency)

• Incentivizes to support grid

frequency

• Real time balancing mechanism

• Maintain grid frequency in narrow

band

• Post transaction charges

• Deviation Settlement Mechanism

and Regulations (DSM, 2014)

• RPO

• Fixed percentage renewable energy

purchase

• FiT contracts as long term PPAs

• FiT near to cost of production of

renewable energy

• RECs as environmental attributes

• 1 REC = 1 MW h of electricity

injected into grid.

• RECs traded in PXs

5/15/2017 27/16

PROBLEM DESCRIPTION

5/15/2017 7

Open Access Large

Consumer

DA Contracts

Bilateral Contracts

IEXDA

PXILDA

Self generation RPO

Indian Grid System

UI Charge

Demand

Generation

REC FiT

FrequencyMean-

Variance

PROBLEM DESCRIPTION

• Grid frequency is calculated from [12]

• ft = Grid frequency

• Lt=System Load

• Gt=System generation

• PFR= Power deficit- frequency fall ratio

• Mean Variance approach for Indian case study.

• Demand shifting using flexibility in projected mind accounting UI

deviations

5/15/2017 29/16

[ ]50

*

t t tt

t

L G UIf

PFR L

OBJECTIVE

• To develop a planning model for short term power

procurement of a large Indian electricity consumer considering

uncertainties (DAM price) and renewable promotional policies

while addressing real time grid frequency imbalances using

demand flexibility.

5/15/2017 6/16

MODELLING

• Objective

• Cost and Risk Minimization

• Cost = Cost of power purchase from (bilateral contracts + Spot Markets + FiT Contacts+ Self

Generation) + UI Penalty/Revenue.

• Risk = Uncertainty of spot market prices

• Constraints

• Demand Balance

• Base Demand + Demand Fluctuations = Shifted Demand + UI deviations

• Expected Demand = Scheduled Demand

• RPO

• Purchasing a percentage from FiT contracts

5/15/2017 6/16

PLANNING MODEL

Minimum and Maximum Purchase Constraints

Bilateral contracts, Spot market

Self Generation Constraints

Quadratic Cost Function

Minimum and Maximum Generation

Ramp up and Ramp down

UI Charge

Calculated from grid frequency

Deviation limitations according to DSM 2014.

5/15/2017 6/16

CASE STUDY

.

5/15/2017 33/16

Capacity 120 MW

Minimum power output

20 MW

Ramping limit (up/down)

80 MW

Quadratic Cost 0.6 Rs./(MW)2h

Linear Cost 2700 Rs./MWh

No-load Cost 2000 Rs.

Startup Cost 1000 Rs.

Generation Unit

Bilateral contract price 3000 Rs./MW h

Min./Max bilateral vol.

limit

30 MW/800MW

Demand Flexibility 12%

Min./Max limit on SI 900 MW/ 1100 MW

Min./Max limit on flexible

load

-40MW/40 MW

RPO, PFR 10 %, 4%

Trading intervals 168 hours

RPO purchase price 5000 Rs./MW

System demand/gen. 100 GW

Other Data Values

960

1010

1060

1110

0 50 100 150Ac

tua

l D

em

an

d (

MW

)

Time (hours)

2000

3000

4000

5000

0 50 100 150Ave

rag

e D

AM

Pri

ce

(R

s./

MW

)

Time (Hours)

PXIL avg price IEX avg price

1b

RESULTS

5/15/201712/16

587

592

597

602

607

612

617

1.4 3.4 5.4

Co

st

(×10

6R

s.)

Standard deviation (× 106 Rs.)

Efficient Frontier

0

50000

100000

150000

0 0.000005 0.00001

Po

we

r P

roc

ure

me

nt

(MW

)

α

Self Generation Bilateral

IEX DAM PXIL DAM

49.94

49.96

49.98

50

50.02

50.04

50.06

-140

-120

-100

-80

-60

-40

-20

0

0 100

Fre

qu

en

cy (

Hz)

UI A

llo

ca

tio

n (

MW

)

Time (Hours)

UI Allocation Grid Frequency

49.96

49.98

50

50.02

50.04

0 100

Fre

qu

en

cy (

Hz)

Time (Hours)

Improved Frequency Grid Frequency

RESULTS

5/15/201712/16

850900950

100010501100115012001250

1 49 97 145

De

ma

nd

(M

W)

Time (Hours)

SCHEDULED DEMAND EXPECTED DEMAND

850

950

1050

1150

1250

0 10 20 30 40

De

ma

nd

(M

W)

Time (Hours)

Scheduled Demand Expected Demand

THANK YOU

15-05-2017 36