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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
Perfect Foresight is Not Possible
5
But All IRP’s Require Assumptions About the Future
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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 Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
$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
Energy Analysis and Environmental Impacts Division
$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
Energy Analysis and Environmental Impacts Division
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 $350/MWh on July 10th
Energy Analysis and Environmental Impacts Division
Combined Cycle Generation Resource Capacity Factors Can Vary Significantly From Year-to-Year
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
An
nu
al C
apac
ity
Fact
or
Combined Cycle Generator Resource Number
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
14
Energy Analysis and Environmental Impacts Division
These Uncertainties Mean There’s No Single “Avoided Cost” for New Resources –Hence No Single Avoided Cost for Energy Efficiency (or Demand Response)
0
50
100
150
200
250
300
2018 2020 2022 2024 2026 2028 2030
Leve
lize
d C
ost
(2
01
2$
/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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
The “Optimization Objective” of Best Practice IRPs -Find the Lowest Cost “Insurance” for the Same Risk Coverage
18
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Power Cost (NPV 2004 $M)->
Risk = average ofcosts> 90% threshold
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
Power Cost (NPV 2004 $M)->
Risk = average ofcosts> 90% threshold
22
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
Like
lihood (
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
Power Cost (NPV 2004 $M)->
Risk = average ofcosts> 90% threshold
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
Power Cost (NPV 2004 $M)->
Risk = average ofcosts> 90% threshold
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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 ($/MWH)
Energy Analysis and Environmental Impacts Division
Energy Efficiency’s Non-Linear Supply Curve Has Implications for Its Risk Mitigation Value
0
50
100
150
200
250
0 10000 20000 30000 40000 50000 60000
Re
al L
eve
lize
d C
ost
(2
01
6$
/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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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?
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
Lunch Break
43
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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
Energy Analysis and Environmental Impacts Division
Session 2 - Risk and Uncertainty Backup Slides
45
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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
Energy Analysis and Environmental Impacts Division
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