Two-stage optimal risk management of large electricity consumer using second-order stochastic dominance

Abstract

Various energy consumers, such as large energy consumers (LEC), are targeted to procure the demanded energy from various power markets such as the pool market and different energy resources, including renewable energy resources (RES), and conventional energy resources optimize the traded energy. In this article, a novel decision-making framework is proposed to schedule the LEC. The proposed technique in this article is based on the second-order stochastic dominance (SSD) to investigate the uncertainty in the total operation cost of the LEC. It is assumed that the market price, pool price, electricity load, and the power output of renewable energy sources (RES), including PV and WT, are uncertain parameters. In the proposed SSD-constrained stochastic programming, demand response programming (DRP) is provided to decrease the operation cost of the LEC. A case study is used to illustrate the effectiveness and efficiency of the novel SSD approach. According to the simulation results, the operation cost of LEC is remarkably decreased from 62,960 to 59,550 in the risk-neutral case (without including risk factor) and SSD case (worst case) with considering DRP, respectively.