Risk-Return Incentives in Liberalised Electricity Markets
AbstractWe employ Monte Carlo analysis to determine the distribution of returns for various electricity generation technologies. Costs and revenues for each technology are arrived by means of a sophisticated unit commitment and economic dispatch algorithm. The results show that small amounts of coal investment along with high investment in advanced CCGT can reduce the risk of baseload-only portfolios, while flexible generation technologies appear on the efficient frontier when all technology types are considered. Diversification incentives regarding operational considerations dominate over incentives to diversify between fuel types
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Department of Economics, University of Sussex in its series Working Paper Series with number 4012.
Date of creation: Oct 2012
Date of revision:
Contact details of provider:
Postal: Jubilee Building G08, Falmer, Brighton, BN1 9SL
Phone: +44 (0) 1273 678889
Fax: +44 (0)1273 873715
Web page: http://www.sussex.ac.uk/economics
More information through EDIRC
Power generation; mean-variance portfolio;
Find related papers by JEL classification:
- Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-05-11 (All new papers)
- NEP-CMP-2013-05-11 (Computational Economics)
- NEP-ENE-2013-05-11 (Energy Economics)
- NEP-REG-2013-05-11 (Regulation)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Bar-Lev, Dan & Katz, Steven, 1976. "A Portfolio Approach to Fossil Fuel Procurement in the Electric Utility Industry," Journal of Finance, American Finance Association, vol. 31(3), pages 933-47, June.
- Roques, Fabien & Hiroux, Céline & Saguan, Marcelo, 2010.
"Optimal wind power deployment in Europe--A portfolio approach,"
Elsevier, vol. 38(7), pages 3245-3256, July.
- Fabien Roques & Céline Hiroux & Marcelo Saguan, 2009. "Optimal Wind Power Deployment in Europe - a Portfolio Approach," RSCAS Working Papers 2009/17, European University Institute.
- Roques, Fabien A. & Newbery, David M. & Nuttall, William J., 2008. "Fuel mix diversification incentives in liberalized electricity markets: A Mean-Variance Portfolio theory approach," Energy Economics, Elsevier, vol. 30(4), pages 1831-1849, July.
- Hobbs, Benjamin F., 1995. "Optimization methods for electric utility resource planning," European Journal of Operational Research, Elsevier, vol. 83(1), pages 1-20, May.
- Delarue, Erik & De Jonghe, Cedric & Belmans, Ronnie & D'haeseleer, William, 2011. "Applying portfolio theory to the electricity sector: Energy versus power," Energy Economics, Elsevier, vol. 33(1), pages 12-23, January.
- H. Brett Humphreys & Katherine T. McClain, 1998. "Reducing the Impacts of Energy Price Volatility Through Dynamic Portfolio Selection," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 107-131.
- Awerbuch, Shimon, 2000. "Investing in photovoltaics: risk, accounting and the value of new technology," Energy Policy, Elsevier, vol. 28(14), pages 1023-1035, November.
- Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, 03.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Russell Eke).
If references are entirely missing, you can add them using this form.