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Decision Support for Public Stake-holders assessing utilities responses to new EPA rules for coal-fired power plants
Dalia Patiño-Echeverri
Nicholas School of the Environment - Duke UniversityCEDM Annual Meeting
May 21-22, 2012, Carnegie Mellon University
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Motivation Upcoming EPA regulations for power plants are forcing
utilities to retrofit or replace coal-fired power plants
PUCs are required to assess prudency of these investments but do not have adequate tools
Other interveners that could provide alternative decision analysis to PUCs often lack tools as well
Can we help improve decision making in this transcendental and complex issue?
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Goal of this project: Provide decision making tools to facilitate analysis that: Is prospective and comprehensive
Considers current and potential future rules Considers “all” possible investment alternatives
Explicitly accounts for the multiple-criteria affecting the decision Criteria are identified, ranked, and weighted Tradeoffs between criteria are quantified
Explicitly accounts for uncertainty judgments
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Identify role
Identify multiple criteria
Determine how uncertainty is characterized
Expand / Improve PowerOptInvest
PUC Project
UC Berkeley, UCLA, UMN, UNC, USF
In collaboration with:
Using inputs from CEDM research:
Communication materials on CCS, renewables . L.Fleishman
Expert elicitation materials Morgan, G.
Expert weighting approaches, Guvenc et al.
Cost and environmental performance of Wind, natural gas, demand response
With help from:Seven MEM students working on their MP
Nicholas Institute Staff
Multiple-criteria affecting PUC decision making example 1: West Virginia: “to ensure that reasonably
priced and reliable utility services are available to all customers and to increase business investment, job creation/retention, and the state’s overall economic competitiveness”
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Multiple-criteria affecting PUC decision making example 2: Colorado: “Regulate effectively so that the
people of Colorado receive safe, reliable, and reasonably priced services consistent with the economic, environmental and social values of our state”
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Multi-criteria decision making tool
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Criteria Metric
Weight
Low unemployment
High unemployment
Capital and OM cost $/MWh 50 45Job creation / retention # jobs per plant / ph 20 30…
Investment alternative
Contribution to Criteria 1: COE Contribution to Criteria 2: JobsScenario 1: High NG price
Scenario2: Low NG Price
Scenario 1: High NG price
Scenario2: Low NG Price
New NGCC New SuperCritical Coal Retrofitted Coal
Methods: Historical Review / Interviews / Survey Instrument
Characterizing uncertainty
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1 Baseline Baseline no price2 Baseline Less Stringent no price3 Baseline More Stringent low 20204 Baseline Baseline low 2020
5 High Baseline no price6 High Less Stringent no price7 High More Stringent mid 20208 High Baseline mid 2020
9 Extra High Baseline no price10 Extra High Less Stringent no price11 Extra High More Stringent high 202012 Extra High Baseline high 2020
Scenario Natural Gas Price
Regulation Carbon Price
Characterizing uncertainty
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Example Probabilities Converging Scenario 2: Mid NG, Less Strinent EPA Reg, No Carbon PriceScenario 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
1 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.0002 0.083 0.185 0.287 0.389 0.491 0.593 0.694 0.796 0.898 1.0003 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.0004 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.0005 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.0006 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.0007 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.0008 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.0009 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.000
10 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.00011 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.00012 0.083 0.074 0.065 0.056 0.046 0.037 0.028 0.019 0.009 0.000
Methods: Historical Review / Elicitation of subjective judgments
PowerOptInvest:
UIDT available to public stake holders
Presented in a number of NARUC webinars, conferences and private meetings
Developing didactical “examples” and scenarios data to preload