分布式電源多點(diǎn)接入布局優(yōu)化研究
王帥1,周雯1,吳忠頂2,何曉敏1
(1 南京工程學(xué)院 電力工程學(xué)院, 江蘇 南京 211167;2 國(guó)電南京自動(dòng)化股份有限公司, 江蘇 南京 210003)
摘 要:以降低系統(tǒng)網(wǎng)絡(luò)損耗和提高電壓質(zhì)量為出發(fā)點(diǎn),研究了分布式電源的接入布局優(yōu)化問題。通過實(shí)例來(lái)驗(yàn)證分布式電源并網(wǎng)的影響,理論分析分布式電源的接入對(duì)系統(tǒng)電壓的影響。提出基于遺傳算法(GA)進(jìn)行DG的布局優(yōu)化,建立了配電網(wǎng)絡(luò)損耗最小、節(jié)點(diǎn)電壓偏移最小的分布式電源多目標(biāo)優(yōu)化函數(shù)。對(duì)遺傳算法每代產(chǎn)生各種DG配置方案進(jìn)行潮流計(jì)算,并利用多目標(biāo)優(yōu)化函數(shù)進(jìn)行方案的優(yōu)劣評(píng)估,通過遺傳算法中的選擇、交叉、變異等操作進(jìn)行DG配置方案的優(yōu)化,若不滿足終止條件將會(huì)繼續(xù)進(jìn)行潮流計(jì)算,直到滿足終止條件后輸出最優(yōu)的DG配置。
關(guān)鍵詞:分布式電源;布局優(yōu)化;潮流計(jì)算;遺傳算法(GA)
中圖分類號(hào):TM715;TM727 文獻(xiàn)標(biāo)識(shí)碼:A 文章編號(hào):1007-3175(2018)10-0023-07
Research on Layout Optimization of Multi-Point Access for Distributed Generation
WANG Shuai1, ZHOU Wen1, WU Zhong-ding2, HE Xiao-min1
(1 School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 2111 67, China;
2 GUODIAN Nanjing Automation Co., Ltd, Nanjing 210003, China)
Abstract: Starting from reducing the loss of system network and improving the voltage quality, this paper researched on the problem of access layout optimization of distributed generation (DG). Via the example, this paper verified the impacts of distributed generation grid connected and analyzed the impact of DG on the system voltage theoretically. This paper proposed to carry out the layout optimization of DG based on genetic algorithm (GA) and established the multi-objective optimization functions of DG with minimum loss of distribution network and node voltage excursion. The GA in each generation produced a variety of DG configuration scheme for load flow calculation and used the multi-objective optimization functions to carry out merits evaluation and allocation plan optimization via the operations of selection, crossover and variation etc. If the DG configuration scheme is not optimized, the load flow calculation will be continued and the optimal DG configuration will be output until the termination condition is satisfied.
Key words: distributed generation; layout optimization; load flow calculation; genetic algorithm
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