Optimal Sizing of Solar/Wind Hybrid Off-Grid Microgrids Using an Enhanced Genetic Algorithm
Optimal Sizing of Solar/Wind Hybrid Off-Grid Microgrids Using an Enhanced Genetic Algorithm作者机构：Department of Electrical and Computer Engineering Oakland University Rochester MI USA
出 版 物：《Journal of Power and Energy Engineering》 (电力能源（英文）)
年 卷 期：2018年第6卷第5期
页 面：64-77页
学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Optimization Off-Grid Microgrid Renewable Energy Energy Storage Systems (ESS) Solar Photovoltaic (PV) Wind Battery Hybrid Genetic Algorithm (GA)
摘 要：This paper presents a method for optimal sizing of an off-grid hybrid microgrid (MG) system in order to achieve a certain load demand. The hybrid MG is made of a solar photovoltaic (PV) system, wind turbine (TW) and energy storage system (ESS). The reliability of the MG system is modeled based on the loss of power supply probability (SPSP). For optimization, an enhanced Genetic Algorithm (GA) is used to minimize the total cost of the system over a 20-year period, while satisfying some reliability and operation constraints. A case study addressing optimal sizing of an off-grid hybrid microgrid in Nigeria is discussed. The result is compared with results obtained from the Brute Force and standard GA methods.
维普期刊数据库