Optimal Location of FACTS Devices in Order to Simultaneously Improving Transmission Losses and Stability Margin Using Artificial Bee Colony Algorithm

被引:24
作者
Kamarposhti, Mehrdad Ahmadi [1 ]
Shokouhandeh, Hassan [2 ]
Colak, Ilhami [3 ]
Band, Shahab S. [4 ]
Eguchi, Kei [5 ]
机构
[1] Islamic Azad Univ, Jouybar Branch, Dept Elect Engn, Jouybar, Iran
[2] Semnan Univ, Dept Elect Engn, Semnan 3513119111, Iran
[3] Nisantasi Univ, Dept Elect & Elect Engn, Fac Engn & Architectures, TR-25370 Istanbul, Turkey
[4] Natl Yunlin Univ Sci & Technol, Coll Future, Future Technol Res Ctr, Touliu 64002, Yunlin, Taiwan
[5] Fukuoka Inst Technol, Dept Informat Elect, Fukuoka 8110295, Japan
关键词
Power system stability; Thyristors; Static VAr compensators; Artificial bee colony algorithm; Power capacitors; Impedance; Buildings; FACTS devices; line loading; loss reduction; voltage profile; artificial bee colony algorithm; PLACEMENT; DESIGN; TCSC; SVC; PSO;
D O I
10.1109/ACCESS.2021.3108687
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It is not possible to use the full capacity of the transmission lines due to voltage limitations and stability issues. Therefore, compensators must be used to improve the transmission line capacity. One of the suggested ways for this purpose is to use flexible alternating current transmission system (FACTS) devices in the power system. The various capabilities of the FACTS devices have made it possible to set different targets to determine their optimal location and position. Some of the most important placement targets include increasing voltage stability, improving voltage profiles, reducing losses, increasing line capacity limit and reducing fuel costs for power plants through optimal power distribution. In this paper, optimal locating of FACTS devices to improve power system stability and transmission line losses reduction. Also, artificial bee colony algorithm is proposed for solving optimization problem. The artificial bee colony algorithm with high accuracy and high convergence speed is suitable for conducting FACTS placement studies. Finally, a comparison was made between the artificial bee colony algorithm and genetic algorithm (GA) and particle swarm optimization (PSO) algorithm. The results indicate that the artificial bee colony algorithm works better than the other algorithms in minimizing the fitness function.
引用
收藏
页码:125920 / 125929
页数:10
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