Title :
CVaR based purchasing portfolio for load serving entities with distributed energy
Author :
Wang, Ruiqing ; Li, Yuzeng ; Wang, Hongfu
Author_Institution :
Sch. of Comput. & Inf. Eng., Anyang Normal Univ., Anyang, China
Abstract :
Load serving entities (LSEs) are faced with the trade-off between benefit and risk when they purchase energy under electricity market environment. In terms of conditional value at risk as the measuring index for market risk, a purchasing model based on asset portfolio theory is presented, in which the object function is to minimize the purchasing portfolio loss among the wholesale market, the bilateral contract market, the interruptible load (IL) market and the distributed generation (DG) market. The impacts of IL and DG on purchasing portfolio loss are addressed. Then the effects of the compensation price of IL and the generating cost of DG on portfolio allocation are investigated. The results show that IL and DG can effectively reduce the purchasing losses of LSEs, and with the increase of the interruption cost of IL and the generating cost of DG, the hedging effect of IL and DG gradually weakens. Finally, a numerical example is used to illustrate the validity of the proposed method.
Keywords :
power markets; CVaR based purchasing portfolio; asset portfolio theory; bilateral contract market; conditional value at risk; distributed energy; distributed generation market; electricity market environment; interruptible load market; load serving entities; market risk; portfolio allocation; purchasing model; wholesale market; Costs; Decision making; Distributed control; Electricity supply industry; Forward contracts; Load management; Portfolios; Power supplies; Power system modeling; Procurement; conditional value at risk (CVaR); distributed generation; genetic algorithm; interruptible load; load serving entities; purchasing portfolio;
Conference_Titel :
Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4934-7
DOI :
10.1109/SUPERGEN.2009.5348249