本文選題：風電場 + 等值模型�。� 參考：《現(xiàn)代電力》2016年06期

【摘要】：風電場等值是含風電場接入電網分析計算的重要技術手段。為降低風電場等值的難度,提高風電場分群的效率,本文基于風電機組實際運行中的監(jiān)測狀態(tài)量,采用模糊C均值(FCM)聚類算法,實現(xiàn)了風電場等值。首先選定各機組輸出有功功率、無功功率、機端電壓有效值及輸出電流有效值為分群指標,并根據(jù)給定的等值機臺數(shù),將風電場分群問題轉化為聚類問題;其次建立了風電機組類屬隸屬度函數(shù)和模糊C均值聚類算法的目標函數(shù),通過迭代求解最優(yōu)的聚類中心和模糊隸屬度矩陣,得到風電場分群結果,算法具有計算簡單、收斂性好的特點;然后,根據(jù)分群結果,對不同群的風電機組進行等值,實現(xiàn)風電場的多機等值;最后,通過仿真比較驗證了本方法的有效性。本方法選取的分群指標具有可實操性,且在給定等值機臺數(shù)條件下,計算更為簡單、等值精度更高,適合用于風電場等值的實際工程計算。
[Abstract]:Wind farm equivalence is an important technical means to connect wind farm to power network analysis and calculation. In order to reduce the difficulty of wind farm equivalence and improve the efficiency of wind farm clustering, based on the monitoring state of wind turbine in actual operation, the fuzzy C-means FCM-based clustering algorithm is used to realize wind farm equivalence. First, the output active power, reactive power, terminal voltage effective value and output current effective value of each unit are selected as cluster indexes, and the cluster problem of wind farm is transformed into clustering problem according to the given number of equivalent machines. Secondly, the membership function of wind turbine and the objective function of fuzzy C-means clustering algorithm are established. The optimal clustering center and fuzzy membership matrix are solved iteratively, and the clustering results of wind farm are obtained. The convergence is good; then, according to the cluster results, the wind turbines of different groups are equated to achieve the multi-machine equivalence of wind farms. Finally, the effectiveness of the method is verified by simulation and comparison. The cluster index selected by this method is practical, and the calculation is simpler and the equivalent precision is higher under the condition of given equivalent number of machines, so it is suitable for the practical engineering calculation of wind farm equivalence.
【作者單位】： 華南理工大學電力學院;
【分類號】：TM614
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本文編號：1854174