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Extracting Insights from Many Scenarios: Examples from FACETS

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Extracting Insights from Many Scenarios: Examples from FACETS

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Extracting Insights from Many Scenarios: Examples from FACETS

  1. 1. Extracting Insights from Many Scenarios: Examples from FACETS Evelyn Wright, Sustainable Energy Economics Amit Kanudia, KanORS-EMR 71th Semi-annual ETSAP Meeting, College Park, MD July 10, 2017
  2. 2. The Framework for Analysis of Climate-Energy-Technology Systems (FACETS) is a multi-region US TIMES model 2 • 134 Power regions • Unit-level power sector • State-level demands and policies
  3. 3. When we run scenarios, we run lots of them • 78 Clean Power Plan scenarios • Dimensions: compliance pathway, interstate compliance trade, gas resource, energy efficiency 3http://lma.vedaviz.com/Presenter/Predex.aspx?pkp=11&pkv=60782
  4. 4. 1. ”Business as usual” depends very much on what you assume • Emission trajectories depend on gas price, renewable technology costs, and lifetimes of existing nuclear units (light vs. dark lines), and • The impact of each of these dimensions depends upon what’s assumed for the others • We now call these “No New Policies” cases 4 US Power Sector Emissions under 12 “BAUs” Hi RE costs Lo RE costs Low gas priceHi gas price Ref gas price
  5. 5. 2. Response to policy is similarly sensitive: carbon taxes under different gas prices Low gas prices lead to lower emissions in No Policy case and early in tax cases, flipping later. In the No Policy case, BOTH high AND low gas prices result in lower emissions than Reference gas prices after 2030. Low gas price Hi gas price Ref gas price
  6. 6. What do we look for in interpreting many scenarios? • What are the competing technologies? • Who’s on the margin in different scenarios? 6
  7. 7. Marginal competition varies across scenarios in 2035 generation mix 7 Coal vs. wind Coal vs. wind and PV Gas vs. coal Gas vs. coal Gas vs. coal All of the above?
  8. 8. What do we look for in interpreting many scenarios? • What are the competing technologies? • Who’s on the margin in different scenarios? • How does that affect the response to incentives set up by policy? 8
  9. 9. The difference in marginal technologies across scenarios impacts the response to a moderate carbon tax… 9 Coal vs. wind Coal vs. wind and PV Gas vs. coal Gas vs. coal Gas vs. coal All of the above?
  10. 10. …which in turn drives the emissions outcomes 10 When gas is the marginal capacity, emissions reductions are not sustained over time.
  11. 11. What do we look for in interpreting many scenarios? • What are the competing technologies? • Who’s on the margin in different scenarios? • How does that affect the response to incentives set up by policy? • How is the response to one dimension affected by the others? • Identify key combinations of dimensions: are there combinations of dimensions in which a policy becomes ineffective? Super costly? Non-binding? • This allows us to identify key risks and opportunities • What is consistent across scenarios? • How do different sensitivites affect the winner and losers from a policy? 11
  12. 12. Conclusions • Never again “A BAU scenario” • Relationships within the energy system are what matters: • We should be delivering an understanding of these relationships, not projections • Finding ways to empower policymakers/stakeholders to explore results and learn about these relationships themselves is a key goal and challenge 12
  13. 13. For More Information about FACETS See http://www.facets-model.com or contact Evelyn.L.Wright@gmail.com

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