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Risk–return incentives in liberalised electricity markets

Muireann Lynch, Aonghus Shortt, Richard Tol and Mark J. O'Malley

Energy Economics, 2013, vol. 40, issue C, 598-608

Abstract: We employ Monte Carlo analysis to determine the distribution of returns for various electricity generation technologies. Costs and revenues for each technology are calculated by means of a unit commitment and economic dispatch algorithm at hourly resolution. This represents a considerable contribution to the literature as costs and revenues are determined endogenously, which in turn allows the returns of midmerit and peaking plant to be examined. Market entry is determined on the basis of a heuristic while market exit is according to a predetermined retirement schedule. The results show that CCGT is the investment technology of choice for baseload-only portfolios, while OCGT proves optimal when all technologies are considered. The high capital costs of baseload generation reduce incentives to invest. The methodology can be expanded to consider random outages, revenues from scarcity prices, capacity markets and ancillary service payments.

Keywords: Monte Carlo simulation; Mean–variance portfolio theory; Electricity generation investment (search for similar items in EconPapers)
JEL-codes: C15 C63 L94 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:40:y:2013:i:c:p:598-608

DOI: 10.1016/j.eneco.2013.08.015

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Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

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