Multi-Objective Scheduling of Coordinated Energy System using Modified Artificial Hummingbird Algorithm

Abstract

This article presents a coordinated energy system (CES) multi-objective (MO) scheduling system. Hydrothermal, solar photovoltaic and battery storage devices are all integrated into the CES. The multi-objective modified artificial hummingbird algorithm (MO-MAHA) has been used to schedule and co-plan MES. A fuzzy decision membership function is used with less computing effort to choose the optimal compromised solution. Two test systems are used to validate the suggested method, and its performance is contrasted with that of the traditional particle swarm optimization (PSO), Crisscross PSO, and artificial hummingbird algorithm (AHA) approaches. The suggested technique reduces costs 7.45%, 4.65%, and 2.51% when compared to MOPSO, MOCPSO, and MOAHA, respectively, once it is implemented in Test System-II. Similarly, compared to the same benchmark approaches, the suggested strategy improve emissions by are 16.47%, 9.48% and 2.17%. In MO analysis, the impact of solar integration has been found to be 3417 $, 5503 lb, respectively, as compared to test system-I. The simulation findings show robust convergence characteristics, improved Pareto diversity, and better economic-environmental trade-offs. Additionally, statistical analyses have been used to determine the efficacy and dependability of the suggested method.