Virtual power plant with energy storage optimized in an electricity market approach

This paper deals with the mathematical formulation and implementation of the optimization model for virtual power plants (VPPs). The daily optimized operation of the VPP is focusing on maximizing its benefit, considering VPP comprising renewable energy sources and energy storage systems, thermal engines and demand-response loads. The optimization model is tested considering two case studies of average electricity prices on the day-ahead market, each of them in four scenarios of the mix renewable energy sources. The model, analyzed on a 24 hours time horizon, is implemented and tested in GAMS. The obtained results show that the best benefit obtained by the virtual power plant owner is obtained when the energy production of analyzed available renewable energy sources is high, and the day-ahead market prices are elevated. In the present paper, the case when the power system operator constraints the exchanges with the virtual power was not considered.