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

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    基于改進NSGA-Ⅱ的考慮負載率指標的風電接入電網規劃

    來源:電工電氣發布時間:2020-07-16 16:16 瀏覽次數:755
    基于改進NSGA-Ⅱ的考慮負載率指標的風電接入電網規劃
     
    王軒1,蔣海峰2,韓偉1,李峰1,雷文寶1,李海濤1,王冰冰2
    (1 國網江蘇省電力有限公司淮安供電分公司, 江蘇 淮安 223002;2 南京理工大學 自動化學院, 江蘇 南京 210094)
     
        摘 要:為保證風電接入電網的經濟性和安全性,提出了基于機會約束的多目標電網規劃模型。經濟性目標中包含了新建線路成本、網損和切負荷懲罰費用。安全性目標考慮了期望值潮流熵和某置信度下線路的負載率水平。針對傳統NSGA-算法的不足,采用基于個體支配等級的自適應參數調整策略改進了NSGA-Ⅱ,增加了最優解集的多樣性且改進了算法的收斂效果。以加入風電場的18節點系統為算例,結果表明,該模型獲得的方案切負荷量較低,系統越限線路少,具有較高的可靠性和適應性。
        關鍵詞:風電;負載率;期望值潮流熵;多目標電網規劃;改進NSGA-Ⅱ算法
        中圖分類號:TM715     文獻標識碼:A     文章編號:1007-3175(2020)07-0001-08
     
    Multi-Objective Grid Planning Connected with Wind Farm Considering Load Rate Based on Improved NSGA-II Algorithm
     
    WANG Xuan1, JIANG Hai-feng2, HAN Wei1, LI Feng1, LEI Wen-bao1, LI Hai-tao1, WANG Bing-bing2
    (1 State Grid Huaian Power Supply Company, Huaian 223002, China;
    2 School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China)
     
        Abstract: In order to ensure the economics and safety of wind power connected to the power grid, a multi-objective grid planning model based on chance constraints is proposed. The economic goals include the cost of newly constructed lines, network loss and load-shedding costs.The safety objective takes into account the expected power flow entropy and the load factor level of the line at a certain confidence level.In response to the shortcomings of the traditional NSGA-II algorithm, an adaptive parameter adjustment strategy based on individual dominance levels is used to improve NSGA-II, increase the diversity of optimal solution sets and improve the convergence effect of the algorithm. Taking an 18-bus system set on a wind farm as an example, the results show that the scheme obtained by this model has a lower loadshedding capacity, fewer lines beyond the system limit, and high reliability and adaptability.
        Key words: wind power; load rate; expected value power flow entropy; multi-objective power grid planning; improved NSGA-II algorithm
     
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