Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets
This study uses an agent-based test bed ("AMES") to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs. Related work can be accessed at: http://www.econ.iastate.edu/tesfatsi/AMESMarketHome.htm
|Date of creation:||09 Jun 2009|
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Web page: http://www.econ.iastate.edu
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- Li, Hongyan & Tesfatsion, Leigh S., 2009. "Capacity Withholding in Restructured Wholesale Power Markets: An Agent-Based Test Bed Study," Staff General Research Papers 13070, Iowa State University, Department of Economics.
- Paul L. Joskow, 2006.
"Markets for Power in the United States: An Interim Assessment,"
The Energy Journal,
International Association for Energy Economics, vol. 0(Number 1), pages 1-36.
- Paul L. Joskow, 2005. "Markets For Power In The United States - An Interim Assessment," Working Papers 0512, Massachusetts Institute of Technology, Center for Energy and Environmental Policy Research.
- Somani, Abhishek & Tesfatsion, Leigh S., 2008. "An Agent-Based Test Bed Study of Wholesale Power Market Performance Measures," Staff General Research Papers 12977, Iowa State University, Department of Economics.
- Sun, Junjie & Tesfatsion, Leigh S., 2006.
"Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework,"
Staff General Research Papers
12649, Iowa State University, Department of Economics.
- Junjie Sun & Leigh Tesfatsion, 2007. "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework," Computational Economics, Society for Computational Economics, vol. 30(3), pages 291-327, October.
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