Optimal scheduling of combined cooling, heating, and power microgrid based on a hybrid gray wolf optimizer

Abstract

ABSTRACT This study aims to reduce economic cost and pollutant emissions of microgrid while satisfying the loads demand and system constraints. A combined cooling, heating and power microgrid model is established integrated with photovoltaic power generation unit and energy storage system. A hybrid grey wolf optimizer is proposed by introducing chaos strategy, mutation strategy and levy strategy into grey wolf optimizer to deal with the shortcomings of mathematical methods and original intelligent optimization methods in microgrid optimal scheduling. The proposed method is verified from a case study and compares with the original grey wolf optimizer. The hybrid grey wolf optimizer reduces the daily economic cost, environmental cost and comprehensive cost of microgrid system by 9.9 $, 34.3 $ and 20.27 $, with the reduction rates of 1.20%, 10.99% and 3.27%. This study is beneficial for alleviating environmental pollution and energy crisis, and promotes economic production and sustainable development.