ACO and CS-based hybrid optimisation method for optimum sizing of the SHES

Abstract

This study proposes an efficient novel approach for achieving optimal economic operation of a standalone hybrid energy system (SHES). Optimal economic operation is obtained through a balance between power outages, carbon emission footprint left by non-renewable resources and cost per unit of energy production of renewable energy resources. SHES with battery and without battery has been considered as two different strategies to examine the impact of the energy storage element. The resulting multi-objective function is optimised using a novel combination of ant colony optimisation (ACO) and cuckoo search (CS) algorithms. The proposed hybrid algorithm is verified against a set of well-known benchmark functions and the results are compared with ACO and CS optimisation techniques. To validate the performance of the proposed algorithm, simulations have been carried out using hourly meteorological data and load data for both strategies (without and with energy storage elements) called as strategies 1 and 2, respectively. It has been observed that strategy 2 exhibits superior performance. Comparative performance analysis of the proposed technique with ACO and CS technique has been analysed and better results have been exhibited with the proposed ACO-CS algorithm. Besides the system with energy storage element yields lesser cost. © The Institution of Engineering and Technology