【摘要】：配電網(wǎng)中分布式風(fēng)電源選址定容時,計及風(fēng)電機組出力和節(jié)點負荷的時序性特征。利用蒙特卡洛模擬MCS(Monte Carlo simulation)對一年內(nèi)每小時風(fēng)速進行抽樣,并求出對應(yīng)的風(fēng)機出力。綜合考慮每小時風(fēng)機出力效率以及對應(yīng)的節(jié)點小時負荷負載率,構(gòu)建小時場景,利用改進K-means聚類法進行場景聚類。根據(jù)聚類后每個場景的風(fēng)機出力效率均值、負荷負載率均值以及對應(yīng)場景的概率,以配電公司最小年費用成本為目標(biāo)函數(shù),利用改進遺傳算法對分布式風(fēng)電源進行選址定容。對33節(jié)點算例的仿真分析結(jié)果表明,風(fēng)機出力與節(jié)點負荷的時序特性對分布式風(fēng)電源的選址定容有重大影響,同時也驗證了所提模型及方法的有效性。
[Abstract]:When the distributed wind power source is selected for fixed capacity in distribution network, the timing characteristics of wind turbine output and node load are taken into account. Monte-Carlo simulation MCS (Monte Carlo simulation) is used to sample the wind speed per hour in one year, and the corresponding fan output force is calculated. Considering the output efficiency of blower per hour and the load rate of node hourly load, the hourly scene is constructed and the scene clustering is carried out by using improved K-means clustering method. According to the mean of fan output efficiency, the average load rate and the probability of the corresponding scenario, the minimum annual cost of the distribution company is taken as the objective function, and the improved genetic algorithm is used to locate the distributed wind power source. The simulation results of 33 node examples show that the timing characteristics of fan output and node load have great influence on the location and capacity of distributed wind power supply, and the validity of the proposed model and method is also verified.
【作者單位】： 東北電力大學(xué)電氣工程學(xué)院;
【分類號】：TM715

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