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Essays in energy policy and planning modeling under uncertainty: Value of information, optimistic biases, and simulation of capacity markets

Posted on:2010-05-15Degree:Ph.DType:Dissertation
University:The Johns Hopkins UniversityCandidate:Hu, Ming-CheFull Text:PDF
GTID:1449390002470962Subject:Economics
Abstract/Summary:
Optimization and simulation are popular operations research and systems analysis tools for energy policy modeling. This dissertation addresses three important questions concerning the use of these tools for energy market (and electricity market) modeling and planning under uncertainty. (1) What is the value of information and cost of disregarding different sources of uncertainty for the U.S. energy economy? (2) Could model-based calculations of the performance (social welfare) of competitive and oligopolistic market equilibria be optimistically biased due to uncertainties in objective function coefficients? (3) How do alternative sloped demand curves perform in the PJM capacity market under economic and weather uncertainty? How does curve adjustment and cost dynamics affect the capacity market outcomes?;To address the first question, two-stage stochastic optimization is utilized in the U.S. national MARKAL energy model; then the value of information and cost of ignoring uncertainty are estimated for three uncertainties: carbon cap policy, load growth and natural gas prices. When an uncertainty is important, then explicitly considering those risks when making investments will result in better performance in expectation (positive expected cost of ignoring uncertainty). Furthermore, eliminating the uncertainty would improve strategies even further, meaning that improved forecasts of future conditions are valuable ( i.e., a positive expected value of information). Also, the value of policy coordination shows the difference between a strategy developed under the incorrect assumption of no carbon cap and a strategy correctly anticipating imposition of such a cap.;For the second question, game theory models are formulated and the existence of optimistic (positive) biases in market equilibria (both competitive and oligopoly markets) are proved, in that calculated social welfare and producer profits will, in expectation, exceed the values that will actually be received. Theoretical analyses prove the general existence of this bias for both competitive and oligopolistic models when production costs and demand curves are uncertain. Also demonstrated is an optimistic bias for the net benefits of introducing a new technology into a market when the cost of the new technology is uncertainty. The optimistic biases are quantified for a model of the northwest European electricity market (including Belgium, France, Germany and the Netherlands). Demand uncertainty results in an optimistic bias of 150,000-220,000 [Euro]/hr of total surplus and natural gas price uncertainty yields a smaller bias of 8,000-10,000 [Euro]/hr for total surplus. Further, adding a new uncertain technology (biomass) to the set of possible generation methods almost doubles the optimistic bias (14,000-18,000 [Euro]/hr).;The third question concerns ex ante evaluation of the Reliability Pricing Model (RPM)---the new PJM capacity market---launched in June 2007. A Monte Carlo simulation model is developed to simulate PJM capacity market and predict market performance, producer revenue, and consumer payments. An important input to RPM is a demand curve for capacity; several alternative demand curves are compared, and sensitivity analyses conducted of those conclusions. One conclusion is that the sloped demand curves are more robust because those demand curves gives higher reliability with lower consumer payments. In addition, the performance of the curves is evaluated for a more sophisticated market design in which the demand curve can be adjusted in response to previous market outcomes and where the capital costs may change unexpectedly. The simulation shows that curve adjustment increases system reliability with lower consumer payments. Also the effect of learning-by-doing, leading to lower plant capital costs, leads to higher average reserve margin and lower consumer payments. In contrast, a the sudden rise in capital costs causes a decrease in reliability and an increase in consumer payments.
Keywords/Search Tags:Market, Uncertainty, Energy, Simulation, Model, Policy, Consumer payments, Optimistic bias
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