Optimal operational scheduling of a virtual power plant participating in day-ahead market with consideration of emission and battery degradation cost

Abstract

In this article, optimal operation of a virtual power plant (VPP) composed of a wind power plant, a photovoltaic power plant, a combined heat and power plant, a heat-only unit, and battery energy storage system is analyzed for day-ahead market. The aim is to adjust the entire generation system for maximum profit and minimum emissions to ensure that the future of the world is clean and investors are not harmed. For these reasons, data obtained from studies in the literature are used in a 24-hour time period. In addition to the four application cases of VPPs, which are mostly discussed in the literature, a fifth case has been proposed in order to be more realistic. All cases and models are modeled and analyzed in the General Algebraic Modeling System (GAMS) software by using the LINDO solver, which has not been used before in previous studies for this problem. Also, battery degradation cost and effects of depth of discharge and temperature are included in the objective function of the VPP model both to provide reality and observe their effects. As a result of this study, it has been shown that the profit of the VPP can be increased while the emission is reduced.