Risk averse optimal operation of a virtual power plant using two stage stochastic programming

VPP (Virtual Power Plant) is defined as a cluster of energy conversion/storage units which are centrally operated in order to improve the technical and economic performance. This paper addresses the optimal operation of a VPP considering the risk factors affecting its daily operation profits. The optimal operation is modelled in both day ahead and balancing markets as a two-stage stochastic mixed integer linear programming in order to maximize a GenCo (generation companies) expected profit. Furthermore, the CVaR (Conditional Value at Risk) is used as a risk measure technique in order to control the risk of low profit scenarios. The uncertain parameters, including the PV power output, wind power output and day-ahead market prices are modelled through scenarios. The proposed model is successfully applied to a real case study to show its applicability and the results are presented and thoroughly discussed. •Virtual power plant modelling considering a set of energy generating and conversion units.•Uncertainty modelling using two stage stochastic programming technique.•Risk modelling using conditional value at risk.•Flexible operation of renewable energy resources.•Electricity price uncertainty in day ahead energy markets.