https://scholars.lib.ntu.edu.tw/handle/123456789/358091
Title: | Analysis of multi-pollutant policies for the U.S. power sector under technology and policy uncertainty using MARKAL | Authors: | MING-CHE HU Hobbs, B.F. |
Keywords: | Decision analysis; Electricity; Greenhouse gas; MARKAL; Stochastic programming; Value of information | Issue Date: | 2010 | Journal Volume: | 35 | Journal Issue: | 12 | Start page/Pages: | 5430-5442 | Source: | Energy | Abstract: | Investments in power generation, pollution controls, and electricity end use equipment are made in the face of uncertainty. Unanticipated events can cause regret-commitments that in retrospect were the wrong choices. We analyze how three uncertainties-electricity demand growth, natural gas prices, and power sector greenhouse gas regulations-could affect electric power sector investment decisions and costs in the U.S. over the next four decades. The effect of multi-pollutant regulations such as the Clean Air Interstate Rule (CAIR) upon these decisions and costs is also considered.We use decision trees to structure the problem, defining multiple futures for each uncertainty and then simulating how the U.S. energy market responds to them. A two-stage stochastic version of the energy-economy model MARKAL simulates the market. Relative importance of the uncertainties is assessed using two indices: expected cost of ignoring uncertainty (ECIU) and expected value of perfect information (EVPI). We also calculate the value of policy coordination (VPC), the cost saved by avoiding surprise changes in policy. An example shows how a stochastic program can be used to compute these indices. The analysis shows that the possibility of greenhouse gas regulation is the most important uncertainty by these measures. © 2010 Elsevier Ltd. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-78649867147&partnerID=MN8TOARS http://scholars.lib.ntu.edu.tw/handle/123456789/358091 |
DOI: | 10.1016/j.energy.2010.07.001 | SDG/Keyword: | Costs; Decision trees; Economics; Electric power generation; Global warming; Greenhouse gases; Investments; Natural gas; Pollution; Stochastic models; Stochastic programming; Stochastic systems; Clean air interstate rules; Decision analysis; Electric power sector; Electricity demand growth; Electricity end-use; Energy markets; Energy-economy models; Expected costs; Expected values; Greenhouse gas regulation; Investment decisions; MARKAL; Natural gas price; Pollutant policies; Power sector; Relative importance; Two stage; Value of information; Uncertainty analysis; decision analysis; electrical power; energy market; energy policy; greenhouse gas; investment location; natural gas; pollution control; pollution policy; power generation; stochasticity; United States |
Appears in Collections: | 生物環境系統工程學系 |
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