A hybrid algorithm (BAPSO) for capacity configuration optimization in a distributed solar PV based microgrid

被引:38
作者
Almadhor, Ahmad [1 ]
Rauf, Hafiz Tayyab [2 ]
Khan, Muhammad Attique [3 ]
Kadry, Seifedine [4 ]
Nam, Yunyoung [5 ]
机构
[1] Jouf Univ, Dept Comp Engn & Networks, Sakakah, Saudi Arabia
[2] Staffordshire Univ, Ctr Smart Syst AI & Cybersecur, Stoke On Trent, Staffs, England
[3] HITEC Univ Taxila, Dept Comp Sci, Taxila, Pakistan
[4] Noroff Univ Coll, Fac Appl Comp & Technol, Kristiansand, Norway
[5] Soonchunhyang Univ, Dept Comp Sci & Engn, Asan, South Korea
关键词
Optimization; Solar grid; Microgrid; Bat algorithm; Particle Swarm Optimization; PARTICLE SWARM OPTIMIZATION; NEURAL-NETWORK; SYSTEM; BATTERY; SEGMENTATION; ALLOCATION; STORAGE;
D O I
10.1016/j.egyr.2021.01.034
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper proposes a hybrid algorithm for capacity configuration optimization of a solar PV-battery-based micro-grid. The hybrid algorithm (BAPSO), which is a combination of Particle Swarm Optimization (PSO) and Bat Algorithm (BA), is designed to optimize the solar generation location and capacity for the efficient performance of a micro-grid. The algorithm considers dynamic transmission power loss optimization and integrates PSO and BA algorithms' respective advantages to form a hybrid algorithm. The proposed algorithm combines PSO's fast convergence ability with the less computation time ability of BA to better optimal solution by incorporating the BA's frequency into the PSO velocity equation to control the pace. The design from the proposed algorithm is tested and validated on IEEE 30 bus test system. The transmission power loss before implementing the algorithm was 22 kW and reduced to 20 kW after the algorithm is used. A further reduction of 0.3 kW of losses is observed by placing the solar generation system at bus number 29. (C) 2021 The Author(s). Published by Elsevier Ltd.
引用
收藏
页码:7906 / 7912
页数:7
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