Inspired-based optimisation algorithm for solving energy-consuming reduction of chiller loading

Abstract

A chiller is a machine that removes heat from a liquid through one of the refrigeration cycles and heat exchangers and uses it to cool the air and the equipment. In this paper, a new method for solving a dynamic optimal chiller loading problem is proposed. The paper uses a new improved technique, quantum emperor penguin optimisation algorithm to solve the optimal chiller loading (OCL) problem with minimum power consumption. The proposed algorithm is used to improve the optimisation ability. To investigate the proposed technique, it is applied to three OCL benchmarks and the results are compared with some optimisation algorithms such as World Cup Optimisation (WCO), Improved Invasive Weed Optimisation (EIWO), Differential Search Algorithm (DS) and the typical Emperor Penguin Optimisation Algorithm (EPO). The results show the performance supremacy of the proposed algorithm in terms of power consumption for multiple chiller systems.