Hedging Supply-Side Risks with Energy Efficiency · Efficient portfolio: minimize expected cost for...

Hedging Supply-Side Risks with Energy Efficiency

Hossein Haeri

2015 ACEEE National Conference on Energy Efficiency as a Resource, September 22

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Energy efficiency avoids waste, lowers energy service costs, and helps protects the environment.

Can it also help hedge against fuel price volatility?

2015 ACEEE National Conference on Energy Efficiency as a Resource |

Evolution of Utility Resource Planning

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Meet demand, minimize production cost, lower revenue requirement

Meet demand, manage costs, broaden resource mix, include unconventional sources

Meet demand, manage cost, manage risk, broaden resource mix, meet broad public policy and environmental objectives, public participation

Resource Portfolio Planning

Integrated Res. Planning (IRP)

Least-Cost Planning (LCP)

EARLY DAYS 1990’S TODAY…


The Setting of the Modern IRP

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ADEQUACY

COST RELIABILITYForecast Demand

Evaluate Technologies

Model Production

Cost

Analysis Future

Scenarios

SECURITY

Legislative Mandates Regulatory Requirements

Environmental Policy Social Policy


Dealing With Uncertainty in IRP

Scenario analysis:Develop alternative visions of the future, identify appropriate combinations of resources that best fit each future, create a unified plan.

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Sensitivity analysis:Evaluate alternative outcomes by changing key inputs and assumptions.

Probabilistic analysis:Assign probabilities to different values of key variables and evaluate the expected outcomes –usually as a probability distribution.

Portfolio analysis:Multiple portfolios (i.e., combinations of future resource options) are developed with each meeting a different set of objective.


Resource Portfolio Planning

Low-cost versus efficiency in portfolio design

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E(rp) = X1 E(r1) + X2 E(r2)

Varp = X1 Var1 + X2 Var2 + X2 X2 Cov12

Efficient portfolio: minimize expected cost for any given level of risk, while minimizing expected risk for every level of expected cost.

The mean-variance

portfolio (MVP) theory:

1)

2)

The basic principles:• There is value in certainty.

• Portfolio variance can be reduced by choosing assets with a low or negative correlation.

• Adding assets with a constant cost improves the portfolio’s return, even if the initial cost is higher than other assets.


Application to the (Near) Real-World

Hypothetical western utility: • Coal (30%)

• Natural gas (56%, split between CC and CT units)

• Mix of renewable (7%, including wind, solar, geothermal, hydro, biomass, and waste-heat

• Cost-effective energy efficiency (7%)

• Potential system capacity shortfalls and open positions to be met through market purchases.


8

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033

Coal Gas (ST) Gas (CC) Renewables Energy Efficiency

Base-Case Resource Stack


Planning Assumptions

Planning horizon: 2014-2033

Base-year operating capacity:

8,300 MW

End-year capacity requirement:

11,950

All coal generation to be

retired by 2026, being

replaced almost entirely with natural gas generation.

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Natural gas generation surges from 4,600 MW

to about 9,750 MW to make up 81% of

the portfolio’s capacity in 2033.

Renewable resources grow from 600 MW in 2014 to 1,400 MW in 2018, and grow

gradually to 1,650 MW in 2025, to satisfy Nevada's renewable resource requirement (RPS) of 15%, staying at that level through the end of the planning period.


The Changing Complexion of Electricity Generation Market

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-40%

-20%

0%

20%

40%

60%

80%

100%

120%

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

All Fuels Coal Natural Gas Nuclear Renewables

Source: Energy Information Administration


Natural Gas Prices – Oracle Speaks

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$1

$2

$3

$4

$5

$6

$7

$8

$9

$10

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032

FORECASTACTUAL

Source: Energy Information Administration


Characterizing Generation

Resource Characteristics:• Availability

• PV of full life-cycle cost (mainly capital, fuel and O&M)

• Discount rate (weighted average cost of capital (WACC), no variability across resources)

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Stochastic variables

(ranges):• Load forecast – high,

medium, low

• Coal prices – 20-year historical

range of 45% - 250%

• Natural gas prices – 20-year

historical range of 70% - 140%

• CO2 and SO2 emission costs

• Market electricity prices


Characterizing EE Resources

Availability: expected

savings realization, a

common metric for

evaluating performance

in EE programs, 65% to

100% of planned values.

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Resource cost (CCE): 50% to 250% of the planned cost.


Resource Evaluation Scenarios

Five scenarios:• Energy efficiency share:

– 550 MW (4.5% of portfolio in the base-case)

– EE progressively replaces natural gas by increments of 250 MW

– 1,550 MW (12.5%) in the final scenario

– 1,550 MW (12.5%) in the final scenario

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Portfolio performance metrics: • Per-unit cost of output

($/MWh)

• Risk (coefficient of variation, CV)


EE Measures Up

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Base-Case

Scenario 1

Scenario 2

Scenario 3

Scenario 4

Scenario 5

9.0%

9.2%

9.4%

9.6%

9.8%

10.0%

10.2%

10.4%

32.0 32.5 33.0 33.5 34.0 34.5 35.0

Ris

k (σ

/μ)

Portfolio Cost ($/MWh)


And So…

Cost-effective EE has the potential to lower portfolio cost and risk (improve return).

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Cost-effective EE lowers overall portfolio cost at nearly all tested volumes, but the effect tapers off.

EE helps lower portfolio risk even under conditions of

extreme uncertainty in savings realization rates and cost.


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