A Novel Hybrid Swarm Intelligence and Cuckoo Search Based Microgrid EMS for Optimal Energy Scheduling

Abstract

A grid-connected or islanded microgrid made up of distributed energy sources (DERs), requires a power management/dispatch system to control the power dispatch and meet the load demand in the system. At the tertiary control level in a typical microgrid, an optimal scheduling mechanism is used to manage the power generated from the local DERs, energy drawn from the grid and energy consumption by the load. This paper proposes a novel hybrid optimization technique for day-ahead scheduling in a smart-grid. A Hybrid Feedback PSO-MCS algorithm is implemented using swarm intelligence and cuckoo search to enhance the performance and obtain a cost-effective solution for a microgrid prosumer. A comparison has been made of the Hybrid Feedback PSO-MCS (HFPSOMCS) algorithm with PSO and modified CS (MCS) algorithm. The best performing algorithm among the three is executed in MATLAB/Simulink and Python IDE platforms to compare the execution time.