A Medium-Term Virtual Power Plant Optimization Framework Considering the Failure Rate of Its Intermittent Units Using Stochastic Programming

Abstract

This article presents a model for maximizing the profit of a commercial virtual power plant (VPP) comprised of heterogeneous distributed energy resources (DERs) considering the failure or power outage of its intermittent units. The failures are taken into account through scenarios of failure happening in different parts of the units with different probabilities. The VPP has access to the future market, the day-ahead (DA) market, and bilateral contracts for trading. Since some of the parameters such as the DA market prices are volatile and uncertain, a two-stage stochastic programming approach is developed to simulate the uncertainty effectively. The VPP makes decisions regarding the future market and signing bilateral contracts in the first stage, then, decisions regarding trading in the DA market and the operation of the VPP’s DERs are taken in the second stage. Using the conditional value at risk (CVaR) approach, the behavior of the risk-neutral VPP is compared to the risk-averse VPP. It is shown that considering the failure of intermittent generation units of the VPP leads to more sensitivity of its profit toward pool prices for both risk-neutral and risk-averse VPPs. It also leads to at least 3.4% of VPP’s profit lost in the specific designed case study.