Real-time and day-ahead risk averse multi-objective operational scheduling of virtual power plant using modified Harris Hawk?s optimization

This paper addresses optimal scheduling of a virtual power plant (VPP) to enhance the economic and environmental aspect of the anticipated VPP network comprise of renewable sources i.e., solar PV, wind power and fuel cell (FC) along with a cogeneration combined heat and power (CHP) unit. A provision of storage is also provided in the form of electric vehicle (EV) as a flexible reserve and energy storage system (ESS) as a spinning reserve to increase the system reliability and security. To improve the economy, risk management concept is incorporated in which a popular risk measure technique conditional value at risk (CVaR) is also utilized to ameliorate low profit scenarios by employing a modified version of recently developed Harris Hawk's optimization (MHHO). A comprehensive analysis is conducted by considering two types of scheduling into account i.e., day ahead scheduling followed by 5-minute interval which has been developed for the selected problem formulation. Single as well as multi-objective optimized scheduling is performed and numerical results are compared with the published work. The developed approach responds well to the proposed formulation and the statistical results indicates the effectiveness and suitability of the anticipated technique in terms of net-profit and environmental feasibility.