Analysis of multi-pollutant policies for the U.S. power sector under technology and policy uncertainty using MARKAL

摘要

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 US. 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 (ECU) 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.