Demand response management in day ahead market for optimal energy trading in VPP framework using PSO

Abstract

A Virtual Power Plant (VPP) aggregates a variety of distributed generation units as a single entity to participate in energy market. A VPP is very effective in utilizing the characteristics of distributed energy sources and implementation of demand response. This paper addresses energy trading and demand response scenario involving VPP, having PhotoVoltaic (PV) generation, along with primary and secondary electricity consumers. The participants engage in day ahead energy markets. In this paper, a novel demand response approach based on creation of two types of time zones namely excessive zone and non-excessive zone is proposed. The load scheduling is performed by shifting load in between these zones. A Particle Swarm Optimization (PSO) based technique is proposed between the VPP and users, to optimize the economic advantages of all participants. The results show that the proposed scheme improves the profit of VPP and simultaneously reduces the energy costs of users in day ahead energy market.