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Distributed energy resources (DERs) can be integrated into a single entity, namely, virtual power plant (VPP). The integration enables them to participate in competitive wholesale electricity markets. According to the different types of uncertainty faced by different DERs, this integration can also act as a risk-hedging mechanism providing a surplus profit. In this paper, using a two-stage stochastic programming approach, risk-averse optimal offering model for a VPP trading in a joint market of energy and spinning reserve service is presented. The conditional value-at-risk (CVaR) is used to control the risk of profit variability. Uncertainties involved in generation of renewables, consumption of loads, calls for reserve service, as well as prices in the day-ahead market, the spinning reserve market (RM) and the balancing (real-time) market (BM), are taken into consideration. This paper assesses how total and surplus profits of VPP are affected by risk-aversion, participation in the RM, and the pricing system in the BM. For this purpose, the role of the integration and the trends of energy and reserve transactions under both single and dual pricing systems in the BM are addressed in detail through a numerical study.
Dabbagh et al. (2015) studied this question.