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中文摘要：
大规模风电场接入电网后,由于风电具有间歇性和随机性等特点,会对电网潮流分布产生较大的影响。特别是当风速具有较强的相关性时,会造成部分线路出现输电阻塞。由于风速分布呈现非线性和尾部相关性的特点,使用广义Copula函数对风电场风速进行相关性建模,然后对其进行参数估计,并对风速相关性模型进行评价和对比,最后将特定相关性风速数据应用于潮流优化算法中。通过基于改进的小生境遗传算法的潮流优化和排序集抽样的蒙特卡洛仿真获取断面的潮流有功功率的概率分布,从而预测输电断面的阻塞概率。最后通过IEEE39节点系统的算例表明,在故障条件下风速相关性对电网阻塞有较大的影响,同时所提方法和模型是有效的。
英文摘要：
Due to intermittence and randomness of wind power, large-scale integration of wind farms in power system will exert influence on power flow distribution. Transmission congestion was caused in part of lines by strong wind speed correlation. Because characteristics of wind power distribution is nonlinear and of tail dependence, wind speed correlation model was obtained with generalized Copula function, and then its parameters were estimated. The correlation model was evaluated and compared with other Copula functions. Wind speed data with specific correlation, obtained from generalized Copula function, is applied to optimal power flow. Probability distribution of sectional power flow was obtained with optimal power flow with improved niche genetic algorithm and Ranked Set Sampling Monte Carlo simulation, and thus congestion probability of transmission section is predicted. At last, the proposed model is applied to IEEE-39 test system. Results show that transmission congestion is influenced by wind speed correlation for component failure. Meanwhile, the model and proposed method are valid.
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