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

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基于神經(jīng)網(wǎng)絡(luò)的并網(wǎng)光伏電站自適應(yīng)距離保護(hù)

來源:電工電氣發(fā)布時間:2020-04-20 13:20 瀏覽次數(shù):959
基于神經(jīng)網(wǎng)絡(luò)的并網(wǎng)光伏電站自適應(yīng)距離保護(hù)
 
薛風(fēng)華1,徐微微1,王洪寅1,龐吉年1,祁言嘉2,王寶華2
(1 國網(wǎng)江蘇省電力有限公司宿遷供電分公司,江蘇 宿遷 223800;2 南京理工大學(xué) 自動化學(xué)院,江蘇 南京 210094)
 
    摘 要:光伏電站并入配電網(wǎng)后,原先配電網(wǎng)的距離保護(hù)動作特性發(fā)生變化,其分支系數(shù)隨著光伏電站的出力變化而變化,給含有分布式電源的配電網(wǎng)保護(hù)整定計算帶來困難。針對某實(shí)際光伏電站結(jié)構(gòu),分析了光伏電站并網(wǎng)后作為分布式電源對配電網(wǎng)距離保護(hù)的影響,利用BP神經(jīng)網(wǎng)絡(luò)建立光伏電站的等效阻抗模型,通過BP神經(jīng)網(wǎng)絡(luò)建立其輸出功率與等效阻抗的關(guān)系,并以此得到自適應(yīng)距離保護(hù)的整定方法,實(shí)例驗(yàn)證了該方法的正確性與實(shí)用性。
    關(guān)鍵詞:光伏發(fā)電;配電網(wǎng);分支系數(shù);距離保護(hù);神經(jīng)網(wǎng)絡(luò)
    中圖分類號:TM615     文獻(xiàn)標(biāo)識碼:A     文章編號:1007-3175(2020)04-0025-05
 
Adaptive Distance Protection of Grid-Connected Photovoltaic Power Plant Based on Neural Network
 
XUE Feng-hua1, XU Wei-wei1, WANG Hong-yin1, PANG Ji-nian1, QI Yan-jia2, WANG Bao-hua2
(1 Suqian Power Supply Branch of State Grid Jiangsu Electric Power Co., Ltd, Suqian 223800, China;
2 School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China)
 
    Abstract: The distance protection action characteristics of the original distribution network will change after the photovoltaic power station is integrated into the distribution network, and its branching coefficient will change with the output of the photovoltaic power station, which makes it difficult to calculate the distribution protection of distributed power grids. Aiming at the structure of certain actual photovoltaic power station, this paper analyzed the impacts of distributed generation on the distribution network distance protection, used BP neural network to establish the equivalent impedance model in photovoltaic power station and the relationship between the output power and the equivalent impedanceby BP neural network, and obtained the tuning method of adaptive distance protection on this account. The correctness and practicability of this method are verified by an example.
    Key words: photovoltaic power generation; distribution network; branching coefficient; distance protection; neural network
 
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