Mean-risk stochastic electricity generation expansion planning problems with demand uncertainties considering conditional-value-at-risk and maximum regret as risk measures

Tekiner-Mogulkoc H., Coit D. W., Felder F. A.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, vol.73, pp.309-317, 2015 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 73
  • Publication Date: 2015
  • Doi Number: 10.1016/j.ijepes.2015.05.003
  • Journal Name: INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.309-317
  • Keywords: Generation expansion, Electricity demand uncertainty, Risk aversion, Conditional-value-at-risk, Maximum regret, CAPACITY EXPANSION, POWER, SYSTEMS
  • Marmara University Affiliated: No

Abstract

This paper focused on solving electricity generation expansion planning problems where there are uncertainties associated with the electricity demand forecasts. The electricity expansion plans are long-term commitments and affects people's living conditions and business prosperity deeply. Therefore it is reasonable that the decision makers may be risk averse. In this paper, mathematical models are developed to incorporate the risk aversion into the generation expansion planning problems. We use the conditional-value-at-risk and maximum regret as risk measures and the results shows that the investment plans are affected when the risk is considered. (C) 2015 Elsevier Ltd. All rights reserved.