The mean–WCVaR based model for LDC's optimal portfolio in multi-energy markets (pages 364–377)

摘要

In a competitive electricity market with highly fluctuated electricity price, local distribution companies(LDCs) need to purchase electric power from several energy markets, such as spot markets, long-term tollingagreements and forward contracts, to maximize profits and minimize risks. Conditional Value-at-Risk(CVaR) can measure risk efficiently, but only one kind of price distribution rule may be considered. In fact,the spot electricity price usually does not follow the normal distribution, and it might be shown aslogarithmic normal distribution if there was no enough supply at peak load situation. In this paper, a novelWCVaR method—Weighted Conditional Value-at-Risk—is proposed to measure the purchasing risk ofLDC with multiple purchase options, especially when the electricity price follows more than one distributionrules. The Mean–WCVaR model is built as a mathematical programing problem to derive the efficientfrontier that indicates the optimal tradeoffs available to LDC between expected revenue and purchasing riskin several energy markets. The existence of optimal solution of proposed WCVaR model is provedmathematically. Simulation results show the efficiency of the proposed model. The proposed modelprovides a new method for LDC to determine the optimal purchasing strategies considering the risk.Copyright # 2011 John Wiley & Sons, Ltd.