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

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遺傳算法優(yōu)化BP神經(jīng)網(wǎng)絡(luò)的電能質(zhì)量預(yù)測預(yù)警研究

來源:電工電氣發(fā)布時間:2021-09-18 12:18 瀏覽次數(shù):484

遺傳算法優(yōu)化BP神經(jīng)網(wǎng)絡(luò)的電能質(zhì)量預(yù)測預(yù)警研究

武晨晨1,苗霽1,祝佳楠1,張文惠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:電能質(zhì)量穩(wěn)態(tài)指標(biāo)的預(yù)測和預(yù)警對于優(yōu)化電網(wǎng)運行方式具有重要意義。以某監(jiān)測點為研究對象,根據(jù)該監(jiān)測點的歷史天氣信息、有功功率、無功功率和電能質(zhì)量數(shù)據(jù),使用遺傳算法改進 BP 神經(jīng)網(wǎng)絡(luò),構(gòu)建復(fù)合型神經(jīng)網(wǎng)絡(luò)預(yù)測系統(tǒng)。給出了電能質(zhì)量分等級預(yù)警方式,通過模糊聚類合理靈活地設(shè)置閾值并給出電能質(zhì)量預(yù)警信息,以適應(yīng)不同場合的預(yù)警。算例驗證證明了該方法的有效性與實用性。
    關(guān)鍵詞:電能質(zhì)量;遺傳算法;BP 神經(jīng)網(wǎng)絡(luò);預(yù)測;預(yù)警;模糊聚類
    中圖分類號:TM933.4     文獻標(biāo)識碼:A     文章編號:1007-3175(2021)09-0018-05
 
Power Quality Prediction and Warning Based on BP
Neural Network Optimized by Genetic Algorithm
 
WU Chen-chen1, MIAO Ji1, ZHU Jia-nan1, ZHANG Wen-hui2
(1 State Grid Jiangsu Electric Power Co., Ltd Suqian Power Supply Branch, Suqian 223800, China;
2 School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China)
 
    Abstract: The prediction and warning of power quality steady state indices is of great significance to optimize the operation of power grid.In this paper, a certain monitoring point is taken as the research object and the data about its historical weather information, active power, reactive power and power quality are performed., The genetic algorithm is utilized to improve the BP neural network and a complex neural network prediction system is constructed accordingly. This prediction system could warn by the grades of power quality and could set threshold value reasonably and flexibly by the use of fuzzy clustering aiming at giving warning information which is available for various situations. In the end ,this method is verified effective and practical by an example.
    Key words: power quality; genetic algorithm; BP neural network; prediction; warning; fuzzy clustering
 
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