Nature-inspired Hybrid Optimization Algorithms for Load Flow Analysis of Islanded Microgrids

作     者：Saad Mohammad Abdullah Ashik Ahmed Quazi Nafees Ul Islam Saad Mohammad Abdullah;Ashik Ahmed;Quazi Nafees Ul Islam

作者机构：the Department of Electrical and Electronic EngineeringIslamic University of TechnologyBoard BazarGazipur 1704Bangladesh 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报（英文）)

年 卷 期：2020年第8卷第6期

页      面：1250-1258页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0808[工学-电气工程] 080802[工学-电力系统及其自动化] 08[工学] 0807[工学-动力工程及工程热物理] 

主　　题：Nature-inspired hybrid algorithm global optimization islanded microgrid load flow analysis 

摘      要：Load flow analysis is a significant tool for proper planning,operation,and dynamic analysis of a power system that provides the steady-state values of voltage magnitudes and angles at the fundamental ***,due to the absence of a slack bus in an islanded microgrid,modified load flow algorithms should be adopted considering the system frequency as one of the solution *** paper proposes the application of nature-inspired hybrid optimization algorithms for solving the load flow problem of islanded *** nature-inspired algorithms such as genetic algorithm(GA),differential evolution(DE),flower pollination algorithm(FPA),and grasshopper optimization algorithm(GOA)are separately merged with imperialistic competitive algorithm(ICA)to form four hybrid algorithms named as ICGA,ICDE,ICFPA,and *** of these algorithms are tested on the 6-bus test system and the modified IEEE 37-bus test system.A comparison among the proposed algorithms is carried out in terms of statistical analysis conducted using SPSS statistics *** the statistical analysis,it is identified that on an average,ICDE takes less number of iterations and consequently needs less execution time compared with other algorithms in solving the load flow problem of islanded microgrids.