michigan public service commission integrated resource planning stakeholder … · 2020-01-06 ·...

Michigan Public Service Commission Integrated Resource Planning Stakeholder Group Meeting

Tom Eckman and Natalie Mims

August 8, 2017

This work was supported by the DOE Office of Electricity Delivery and Energy Reliability

under Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH11231.

Energy Analysis and Environmental Impacts Division

Today’s Agenda

2

Time Content

9:00 – 10:00 am Review of IRP content and development process• Focus on treatment of efficiency and demand

response

10:00 – 11:00 am Time-varying value of energy efficiency research

11:00 - Noon Uncertainty and Risk Analysis

Noon – 1:30 pm Lunch break

1:30 – 3:30 Stakeholder engagement


Session 3 - Uncertainty and RiskManaging the Unknown

As we know,

There are known knowns.

There are things we know we know.

We also know

There are known unknowns.

That is to say

We know there are some things

We do not know.

But there are also unknown unknowns,

The ones we don't know

We don't know.

3

Donald Rumsfeld. Feb. 12, 2002, Department of Defense news briefing


Key Risk Analysis Questions What are the vulnerabilities of your plan?

How do you expect uncontrollable factors to influence each other? In

the short term? In the long term?

Could new regulation, market conditions, or technological innovation

change these relationships?

What are the key drivers of risk? What would force you to change your plan? What are the threshold events and values that trigger alternative plans?

Where is the perfect foresight assumption hiding?

How much would it cost to change the plan? (“Type I” and “Type II” error costs.) What is your “exit strategy?”

Which sources of uncertainty can be aggregated? (e.g., electricity

price and technology innovation)

What is the appropriate application of quantitative methods?

4


Perfect Foresight is Not Possible

5

But All IRP’s Require Assumptions About the Future


IRPs Must Address Three Major Sources of Uncertainty

Load Uncertainty

Resource Uncertainty

Output

Cost

Construction Lead Times

Technology Change

Wholesale Electricity Market

Price Uncertainty

6

Historical Levels of Load Uncertainty in Michigan Were Driven by Large Industrial Loads

-

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

1990 1995 2000 2005 2010 2015

Ind

ust

rial

Se

cto

r R

etai

l Sal

es

(GW

H/y

ear

)

Michigan Industrial Sector Sales


Best Practice Load Forecasts for IRPs Do Not Assume Perfect Foresight

0

50,000

100,000

150,000

200,000

250,000

2016 2018 2020 2022 2024 2026 2028 2030 2032 2034

Load

(G

WH

/ye

ar)

Load Forecast Rangewithout New Energy Efficiency

10% Percentile

First Quartile

Median

Third Quartile

90% Percentile

8


Load Uncertainty Is Particularly A Problem For Resources With Long Lead Times and Large Sizes

0

2

4

6

8

10

12

14

16

18

0 200 400 600 800 1000

Re

sou

rce

Le

ad T

ime

(ye

ars)

Resource Capacity (Megawatts)

Nuclear

Coal

Gas-Fired CCCTs*

9


Energy Efficiency, Demand Response and Shortened Lead Times and Smaller Sizes For Some Generating Resources Reduce Exposure to Load Uncertainty

0

2

4

6

8

10

12

14

16

18

0 200 400 600 800 1000

Re

sou

rce

Le

ad T

ime

(ye

ars)

Resource Capacity (Megawatts)

Nuclear

Coal

Energy Efficiency

Gas-Fired SCCT & CCCTs

Wind/PV

10


$0

$50

$100

$150

$200

$250

$300

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Re

al L

eve

lize

d C

ost

(2

01

6$

/MW

h)

Lifetime Capacity Factor

Lifecycle Cost of Combined Cycle Gas Fired Combustion Turbine at Varying Gas Prices and Capacity Factors

$2.00/MMBtu

$4.00/MMBtu

$6.00/MMBtu

$8.00/MMBtu

Generating Resource Cost Uncertainty Is Primarily Driven by Input Fuel Prices and Utilization (i.e., "capacity factors”)

11

20% Capacity

Factor

50% Capacity

Factor 90% Capacity

Factor


$0

$10

$20

$30

$40

$50

$60

$70

$80

$90

$100

$0.00 $1.00 $2.00 $3.00 $4.00 $5.00 $6.00 $7.00 $8.00 $9.00 $10.00

Mid

C W

ho

lesa

le E

lect

rici

ty P

rice

($/M

Wh

20

12

$)

Natural Gas Price ($/MMBtu 2012$)

Historic Wgt Ave Mid C Price Forecast Mid Case Lin. Fit to Forecast data

Wholesale Electricity Market Prices Are Strongly Correlated to Natural Gas Prices

12


When Natural Gas Market Prices Provide Surprises, They Pass Along That Gift To Wholesale Electricity Prices

$0

$2

$4

$6

$8

$10

$12

$141

98

31

98

41

98

51

98

61

98

71

98

81

98

91

99

01

99

11

99

21

99

31

99

41

99

51

99

61

99

71

99

81

99

92

00

02

00

12

00

22

00

32

00

42

00

52

00

62

00

72

00

82

00

92

01

02

01

12

01

2

$/M

MB

TU

13

MISO power prices crossed $200/MWh several times in July, reaching almost $350/MWh on July 10th


Combined Cycle Generation Resource Capacity Factors Can Vary Significantly From Year-to-Year

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

An

nu

al C

apac

ity

Fact

or

Combined Cycle Generator Resource Number

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

14


These Uncertainties Mean There’s No Single “Avoided Cost” for New Resources –Hence No Single Avoided Cost for Energy Efficiency (or Demand Response)

0

50

100

150

200

250

300

2018 2020 2022 2024 2026 2028 2030

Leve

lize

d C

ost

(2

01

2$

/MW

h)

Plant In-Service Year

Levelized Cost and In-Service Date of Combined Cycles Combustion Turbine Across A Sample Futures

15

The Pace of Technology Change Introduces Additional Uncertainty Into the Determination of Avoided Cost

$0.00

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

$7.00

$8.00

$9.00

2007-2009 2010 2011 2012 2013 2014 2015

20

15

$/W

att-

AC

Year of Installation

Historical Price Trends for Utility Scale Solar PV

Fixed-Tilted Median Price

Tracking - Median Price

16

Source: LBNL


Resource Analysis Model

Best Practices IRPs Use Scenario Analysis “Stress Test” Resource Strategies Across A Range of Future Conditions

17

Natural Gas Price Forecast

Wholesale Electricity Price Forecast


The “Optimization Objective” of Best Practice IRPs -Find the Lowest Cost “Insurance” for the Same Risk Coverage

18


Most Capacity Expansion Models Are Not Designed to Conduct Risk Analysis

Market equilibrium

models generally

optimize capacity

expansion for a single

future (i.e., they have

perfect foresight)

Sensitivity studies can

inform risk analysis, but

still compare

optimizations done for

single futures

19


What Does Stochastic Risk Analysis Model Do?

It test thousands of alternative resource strategies (those things we control)

Varying the amount and timing of resource development• Conservation (retrofit, lost-opportunity)

• Natural gas fired CCCT and SCCT

• Wind and Utility Scale Solar

Varying the amount and timing market purchases in lieu of resource development

Against hundreds of different futures (those things we don’t control)

Fuel price Uncertainty

Carbon risk Uncertainty

Load Uncertainty

Resource Uncertainty

Wholesale Market Price Uncertainty

It “sorts” through all of the resource strategies to find those with the lowest cost for each level of risk.

20


How the Strategic Risk Analysis Approach Differs

Likelihood analysis that captures strategic

uncertainty

Imperfect foresight and use of decision

criteria for capacity additions

Adaptive plans that respond to futures

“Scenario analysis on steroids”

Hundreds of futures, strategic uncertainty

Frequency that corresponds to likelihood

21


Modeling Process

The portfolio modelLi

kelih

ood (

Pro

babili

ty) Avg Cost

10000 12500 15000 17500 20000 22500 25000 27500 30000 32500

Power Cost (NPV 2004 $M)->

Risk = average ofcosts> 90% threshold

Like

lihood (

Pro

babili

ty) Avg Cost

10000 12500 15000 17500 20000 22500 25000 27500 30000 32500



Like

lihood (

Pro

babili

ty) Avg CostAvg Cost

10000 12500 15000 17500 20000 22500 25000 27500 30000 3250010000 12500 15000 17500 20000 22500 25000 27500 30000 32500



22


Nu

mb

er o

f O

bse

rvat

ion

s

Cost for Future 2

Cost for Future 1

A Resource Strategy’s Cost and Risk Depend on the Future

10000 12500 15000 17500 20000 22500 25000 27500 30000 32500

Net Present Value Power Cost (millions)->

23


Expected Cost and Risk Metrics Are Used to Characterize Each Resource Strategy

Like

liho

od

(P

rob

abili

ty)

Expected Value of Resource Strategy’s Cost = Average Cost Across All Futures

10000 12500 15000 17500 20000 22500 25000 27500 30000 32500

Net Present Value Power System Cost (millions)->

Expected Value of Resource Strategy’s Risk = Average Cost of “Worst” 10% of Futures

24


Like

lihood (

Pro

babili

ty) Avg Cost

10000 12500 15000 17500 20000 22500 25000 27500 30000 32500



Like

lihood (

Pro

babili

ty) Avg Cost

10000 12500 15000 17500 20000 22500 25000 27500 30000 32500



Like

lihood (

Pro

babili

ty) Avg CostAvg Cost

10000 12500 15000 17500 20000 22500 25000 27500 30000 3250010000 12500 15000 17500 20000 22500 25000 27500 30000 32500



Risk Analysis Models Are Use These Metrics To Select the Resource Strategies with the Lowest Expected Cost for Varying Levels of Risk

Incr

eas

ing

Ris

k

Increasing Cost

25

Resource Strategy’s Average Cost

Resource Strategy’s Risk


All Resource Strategies That Meet Pre-Defined Constraints (e.g., reliability)

The “Best” (i.e. Lowest Cost) Resource Strategies at Each Risk Level Form the Efficient Frontier

Incr

eas

ing

Ris

k

Increasing Cost

Efficient Frontier

26

Best Resource Strategies

The Efficient Frontier Permits Policy Choices Regarding the Cost of Insuring Against Risk

$155.0

$155.5

$156.0

$156.5

$157.0

$157.5

$158.0

$104.0 $104.5 $105.0 $105.5 $106.0

NP

V S

yste

m R

isk

(2

00

6$

Bill

ion

s)

NPV System Cost (2006$Billions)

Least Risk Plans

Least Cost Plans


Lessons Learned from Exploring the “Efficient Frontier”

Power plant construction lead time is major source of economic risk

It is better to be a little surplus in resources than a little deficit, but…

The biggest blunder is overbuilding

Not all resources can or should recover their cost in the wholesale

electricity market

Specifically, acquiring EE at levelized cost above short-run market prices reduces both cost and risk

Low Cost resource portfolios rely more heavily on the wholesale market

purchases, while Low Risk resource portfolios build additional resources

Energy Efficiency is a Lower Cost and Lower Risk Source of Reserves

Than Natural Gas Generation

Hedges and Options can be used to manage risk

28


The Least Cost and Least Risk Resource Portfolios Both Rely Heavily on Energy Efficiency

29

0

10,000

20,000

30,000

40,000

50,000

60,000

0 20 40 60 80 100 120

Effi

cie

ncy

Re

sou

rce

Ad

dit

ion

s (G

WH

/yr.

)

Portfolios On Efficient Frontier

Least Cost Portfolios

Least Risk Portfolios


The Near-Term Pace of Energy Efficiency Development Does Not Vary Significantly Between Least Cost and Least Risk Portfolios

30

-

10,000

20,000

30,000

40,000

50,000

60,000

2010 2015 2020 2025

Cu

mu

lati

ve D

evel

op

men

t (G

WH

/yr)

Year

Least Cost

Least Risk


The Near-Term Pace of Energy Efficiency Development Does Not Vary Significantly Across A Wide Range of Policy Assumptions

-

10,000

20,000

30,000

40,000

50,000

2015 2020 2026 2031Cu

mu

lati

ve D

eve

lop

me

nt

(GW

H/y

r.)

Existing Policy Social Cost of Carbon - MidRange

Retire Coal and Inefficient Gas Retire Coal

Retire Coal w/SCC MidRange Retire Coal w/SCC MidRange and No New Gas

Regional RPS @ 35%

31

Energy Efficiency Is an Inexpensive Source of Reserve Margin, Which Reduces Market Exposure Risk & May Moderate Wholesale Price Swings

Efficiency’s value stems from “being there” when a shortage hits (high prices)

Higher levels of efficiency (lower demands) provide more price moderation

$0

$20

$40

$60

$80

$100

$120

$140

$160

-

5

10

15

20

1997 1998 1999 2000 2001 2002 2003 2004

Mar

ket

Pri

ce (

$M

WH

)

Cu

mu

lati

ve S

avin

gs (

GW

H/y

r)

Cumulative Efficiency - w/o Risk Premium

Cumulative Efficiency - w/ Risk Premium

Wholesale Market Price w/o Risk Premium ($/MWH)

Wholesale Market Price w/ Risk Premium ($/MWH)


Energy Efficiency’s Non-Linear Supply Curve Has Implications for Its Risk Mitigation Value

0

50

100

150

200

250

0 10000 20000 30000 40000 50000 60000

Re

al L

eve

lize

d C

ost

(2

01

6$

/MW

h)

Resource Potential (GWH/year)

Change in Price

$10/MWh Price Change

Quantity Change

Quantity Change

$10/MWh Price Change

• EE Supply Curve Exhibits “Diminishing Returns”

• Acquiring EE At A Premium over Short Term Market Prices

– Builds more EE when market prices are low

– Does not overbuild EE when market prices are high

33


Why Is EE A Lower Cost Way of Providing Reserves?Energy Efficiency Has Value Even In Low Market Price Conditions

$Net Benefit per $Expense

0

2000

4000

6000

8000

10000

12000

14000

16000

18000-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

1.2

1.4

1.6

1.8 2

2.2

2.4

2.6

2.8

Ratio ($Net Benefit\$Expense)

Fre

quency

SCCT discretionary conservation lost opportunity conservation

Benefits/Cost = 1.0

34


A Bit More Explanation . . .

Operate under circumstances of relatively lower electricity market prices and volatility This is a direct consequence of having the additional

resources that give us protection against uncertainty (i.e., “we are never short”)

Do not pay for themselves! If we want to reduce risk, we have to pay the insurance

premium of extra capacity that may not be used frequently enough to cover its costs.

SCCT and Energy Efficiency Resources Serving As Reserves:

35


Summary

The quality of reserves provided by EE is superior to conventional resources, because: EE has value under low market prices

EE is not subject to forced outages

EE is not subject to fuel price risk

EE is not subject to carbon control risk

Implication - For low-risk plans, the cost-effectiveness limit for energy efficiency resources is higher than long-term view of the average wholesale market price for electricity

36


0

50

100

150

200

250

- 10,000 20,000 30,000 40,000 50,000 60,000

Leve

lized C

ost

(2016$/M

WH

)

Achievable Potential (GWH/yr)

Setting A Cost-Effectiveness Limit Above Short-Term Market Prices, Acquires More Efficiency (Increases Reserves) and Reduces Both System

Cost and Risk

Long-Term Equilibrium Market Price

“Risk Premium” + Long-Term Equilibrium Market Price Sets Cost-Effectiveness Limit for Energy Efficiency

37


What does the Efficient Frontier Tell Us?

The Efficient Frontier does not tell us what to do

The Efficient Frontier tells us what not to do

Most useful if there are a large number of choices

38


What Can We Learn from Exploring the Efficient Frontier

If we cannot use the efficient frontier to select a plan, what good is it?

Unless we have a large number of plans, not much in itself, but ...

In combination with the space and with other objectives, it can be very useful in addressing questions such as:

What are the similarities among strategies close to the efficient frontier?

How do strategies change as we move along the efficient frontier?

What are the similarities among strategies removed from the efficient

frontier?

Relationships among plans on, off, and over the efficient frontier can provide insight into what are more and less successful strategies

How do plans differ with respect to other sources of risk?

How do details within particular futures differ?

When do you really have to make a choice?

What costs and elements can you control?

39


Parting Shot

“The essence of risk management lies in maximizing

the areas where we have some control over the

outcome while minimizing the areas where we have

absolutely no control over the outcome and the

linkage between effect and cause is hidden from us.”

(emphasis is the author’s)

--Peter L. Bernstein, Against the Gods, The

Remarkable Story of Risk

40

Any Questions?


Resources

Binz, Ron, Sedano, R., Furey, D. and Mullen, D. Practicing Risk-Aware Electricity Regulation: What

Every State Regulator Needs to Know. CERES 2012. Available at:

http://www.ceres.org/resources/reports/practicing-risk-aware-electricity-regulation/view

Lazar, Jim and Colburn, K. Recognizing the Full Value of Energy Efficiency. Regulatory Assistance

Project. September 2013. Available at: http://www.raponline.org/wp-content/uploads/2016/05/rap-

lazarcolburn-layercakepaper-2013-sept-9.pdf

Northwest Power and Conservation Council. “Overview of the Council’s Power Planning Methods.”

Council Document 2011-02. Available at: www.nwcouncil.org/media/29998/2011_02.pdf.

Northwest Power and Conservation Council. Fifth Northwest Power and Conservation Plan, Chapter 6 –

Risk Assessment and Management. Available at:

https://www.nwcouncil.org/media/5786/_06__Risk_Section.pdf and Appendix P, Treatment of

Uncertainty and Risk. Available at: https://www.nwcouncil.org/media/4401598/AppendixP.pdf

SEE Action. “Using Integrated Resource Planning to Encourage Investment in Cost-Effective Energy

Efficiency Measures.” DOE/EE-0668. Driving Ratepayer-Funded Efficiency through Regulatory Policies

Working Group. J. Shenot, Regulatory Assistance Project. Available at:

https://www4.eere.energy.gov/seeaction/system/files/documents/ratepayer_efficiency_irpportfoliomanag

ement.pdf.

42


Lunch Break

43

To learn more about our work:

Visit our website at: http://emp.lbl.gov/

Click here to join the Berkeley Lab Electricity

Markets and Policy Group mailing list and stay

up to date on our publications, webinars and

other events. Follow us on Twitter:

@BerkeleyLabEMP


Session 2 - Risk and Uncertainty Backup Slides

45


Definition of Terms

Uncertainty: Imperfect information, or events about

which we have imperfect information

Risk: The likelihood and magnitude of “bad” outcomes

This is not volatility; this is not uncertainty

Some uncertainties do not create risk

Futures: Combinations of uncertainty aspects about the

future that we cannot control

Plans: Actions or policies that we can control

Scenario: How a particular plan (what we control)

performs under a particular future (what we don’t control)

46


Definition of Terms - Risk Mitigation

Options.• The right, but not the obligation to take a particular action or

engage in a particular transaction.

• Has two sides, and must be traded between participants.

• Usually asymmetric with respect to a given risk: limits outcome in a single direction.

Hedging.• Commitment to action or transaction that reduces the variability

or uncertainty of outcome. Does not provide optionality.

• Usually symmetric with respect to a given risk: limits outcome in both directions.

Neither in itself decreases expected costs.

47


Risk Mitigation: Optionality

Long-term flexibility• Start-up and shut-down speed and flexibility

• Demand reduction

• Mothball and delay flexibility

• Operational and administrative control, independence

• Sizing flexibility (capital cost flexibility)

Short-term flexibility• Dispatchability, if fixed cost component is small

• Demand curtailment

48


Definition of Terms - HedgingLong-term hedges

• Independence from fuel price

• Resource diversity

• High availability and proven technology

• Reliable technology

• Cash flow: how and when capital is committed (complex)

• R&D

Short-term hedges• Diversity of fuels

• Reliability of resource and reduced maintenance

49

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