Suzhou Electric Appliance Research Institute
期刊號: CN32-1800/TM| ISSN1007-3175

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基于環(huán)路組搜索策略的多目標(biāo)配電網(wǎng)重構(gòu)研究

來源:電工電氣發(fā)布時(shí)間:2021-04-30 15:30 瀏覽次數(shù):677

基于環(huán)路組搜索策略的多目標(biāo)配電網(wǎng)重構(gòu)研究

曾浩然1,楊超1,徐立立1,夏博2
(1 貴州大學(xué) 電氣工程學(xué)院,貴州 貴陽 550025;
2 國網(wǎng)重慶市電力公司萬州供電分公司,重慶 404001)
 
    摘 要:提出一種基于環(huán)路組搜索策略的多目標(biāo)配電網(wǎng)重構(gòu)算法,對含分布式電源(DG) 的配電網(wǎng)進(jìn)行重構(gòu)。采用環(huán)路編碼的方式將網(wǎng)絡(luò)劃分為若干個(gè)基本環(huán)路,以此減少搜索空間,同時(shí)考慮的目標(biāo)函數(shù)包括系統(tǒng)的有功網(wǎng)損最小、電壓幅值偏移量最小、開關(guān)的操作次數(shù)最少,并利用層次分析法(AHP) 將以上目標(biāo)函數(shù)進(jìn)行歸一化后整合為單目標(biāo)函數(shù),降低搜索維度的同時(shí)還提高了算法的搜索效率。再通過引入變鄰域搜索(VNS) 改進(jìn)二進(jìn)制粒子群算法(BPSO),使其擁有更好的全局搜索能力。通過含DG 的PG & E69 節(jié)點(diǎn)算例分析表明:改進(jìn)后算法的尋優(yōu)效率明顯提升,目標(biāo)函數(shù)值也更優(yōu)越,重構(gòu)后配電網(wǎng)絡(luò)的各項(xiàng)情況均得到顯著優(yōu)化。
    關(guān)鍵詞:優(yōu)化重構(gòu);配電網(wǎng);環(huán)路組搜索;層次分析法;變鄰域搜索
    中圖分類號:TM715 ;TM734     文獻(xiàn)標(biāo)識碼:A     文章編號:1007-3175(2021)04-0001-05
 
Research on Multi-Objective Distribution Network Reconfiguration
Based on Loop Group Search Strategy
 
ZENG Hao-ran1, YANG Chao1, XU Li-li1, XIA Bo2
(1 College of Electrical Engineering, Guizhou University, Guiyang 550025, China;
2 Wanzhou Power Supply Branch of State Grid Chongqing Electric Power Company, Chongqing 404001, China)
 
    Abstract: A multi-objective distribution network reconfiguration algorithm based on loop group search strategy is proposed to reconstruct the distribution network with distributed generation (DG). The network is divided into several basic loops by loop coding to reduce the search space. At the same time, taking the minimum active power loss, the minimum voltage amplitude offset and the minimum switch operation times as the objective functions, the above objective functions are normalized and integrated into a single objective function by using the analytic hierarchy process (AHP), which reduces the search dimension and improves the search efficiency of the algorithm. Then the variable neighborhood search (VNS) is introduced to improve the binary particle swarm optimization (BPSO) algorithm, so that it has better global search ability. Finally, the analysis of the PG & E69 node calculation example with DG shows that the optimization efficiency of the improved algorithm is significantly improved, the objective function value is also better, and all the situations of the reconstructed distribution network are significantly optimized.
    Key words: optimization and reconfiguration; distribution network; loop group search; analytic hierarchy process; variable neighborhood search
 
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