Optimal Virtual Power Plant Scheduling using Elephant Herding Optimization

Abstract

A virtual power plant (VPP) is an aggregate of any combination of distributed generation (DG), energy storage (ES) devices, and interruptible loads (ILs), exercising active control over these resources so that they are represented as a single flexible unit in the main grid and in the electricity market. Due to physical and economic constraints, the scheduling of VPP resources is regarded as an optimization problem. This study proposes a decision tool for a VPP operator in optimizing the profits in scheduling of VPP resources participating in a day-ahead market. The decision tool is based on elephant herding optimization (EHO), a relatively new metaheuristic technique inspired by the social behaviour of elephants. The method is implemented on a test system with a VPP comprising DGs, ES devices, and ILs. Economic characteristics of these resources and of the network were considered. The results from a test case validate the algorithm’s ability to manage the scheduling of VPP resources, thereby suggesting that it can perform well as a decision support tool to the VPP operator.