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

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基于改進(jìn)NSGA-Ⅱ的考慮負(fù)載率指標(biāo)的風(fēng)電接入電網(wǎng)規(guī)劃

來源:電工電氣發(fā)布時間:2020-07-16 16:16 瀏覽次數(shù):831
基于改進(jìn)NSGA-Ⅱ的考慮負(fù)載率指標(biāo)的風(fēng)電接入電網(wǎng)規(guī)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(wǎng)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(xué) 自動化學(xué)院, 江蘇 南京 210094)
 
    摘 要:為保證風(fēng)電接入電網(wǎng)的經(jīng)濟性和安全性,提出了基于機會約束的多目標(biāo)電網(wǎng)規(guī)劃模型。經(jīng)濟性目標(biāo)中包含了新建線路成本、網(wǎng)損和切負(fù)荷懲罰費用。安全性目標(biāo)考慮了期望值潮流熵和某置信度下線路的負(fù)載率水平。針對傳統(tǒng)NSGA-算法的不足,采用基于個體支配等級的自適應(yīng)參數(shù)調(diào)整策略改進(jìn)了NSGA-Ⅱ,增加了最優(yōu)解集的多樣性且改進(jìn)了算法的收斂效果。以加入風(fēng)電場的18節(jié)點系統(tǒng)為算例,結(jié)果表明,該模型獲得的方案切負(fù)荷量較低,系統(tǒng)越限線路少,具有較高的可靠性和適應(yīng)性。
    關(guān)鍵詞:風(fēng)電;負(fù)載率;期望值潮流熵;多目標(biāo)電網(wǎng)規(guī)劃;改進(jìn)NSGA-Ⅱ算法
    中圖分類號:TM715     文獻(xiàn)標(biāo)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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