期刊
RENEWABLE ENERGY
卷 96, 期 -, 页码 1-10出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2016.04.069
关键词
Hybrid energy system; Cuckoo search; Genetic algorithm; Particle swarm optimization; Wind turbine generator force outage rate
Solar and wind power based hybrid energy system with energy storage unit provides a reliable and cost effective energy alternative above the conventional diesel generator based system commonly used by remote consumers. In this context, this paper explores the application of a new meta-heuristic algorithm called Cuckoo Search (CS) in the area of a hybrid energy system design problem. Cuckoo Search (CS) is applied for optimal sizing of three different system schemes viz. Photovoltaic-Battery, Wind-Battery and Photovoltaic-Wind-Battery system applicable to a remote area located in Almora district of Uttarakhand, India while minimizing total system cost and considering seasonal variation of load. The effectiveness of Cuckoo Search algorithm in solving hybrid energy system design problem is investigated and its performance is compared with other well known optimization algorithms like Genetic Algorithm (GA) and Particle Swarm,Optimization (PSO) algorithm. Optimization results further, shows that hybrid integration of photovoltaic, wind and battery storage gives most reliable and economical system scheme for the study area. In addition, this paper assesses the effect of wind turbine generator (WTG) force outage rate (FOR) on the optimal system reliability and economics. (C) 2016 Elsevier Ltd. All rights reserved.
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