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中文摘要：
考虑多风电场相关性的概率潮流计算对评估风电接入系统所带来的影响具有重要意义。针对相邻风电场出力间相关性复杂多变的特点,提出一种基于K-means聚类和Copula函数的场景概率潮流计算方法,能够考虑多风电场出力间相关性的变化,建立其场景概率模型,得到不同场景下系统状态变量的概率指标。以澳大利亚的2个相邻风电场实测出力为样本,在含多风电场的IEEE 30节点系统中对场景概率潮流计算方法进行测试分析。算例结果表明,所提方法能够建立准确的多风电场出力概率模型,得到更可靠的概率潮流计算结果。
英文摘要：
The probabilistic load flow considering wind farm correlation is of great significance to evaluate the effects of wind power integration. According to the complex and variable characteristic correlation between the outputs of adjacent wind farms, this paper proposes a scenario probabilistic load flow calculation method based on K-means clustering and Copula function. The proposed method can consider the changes of correlation between wind farms＇ outputs under different scenarios, and get the probability index of the system state variables for each scenario. The method is tested and assessed in IEEE 30-node system, taking two adjacent wind farms＇ outputs in Australia as sample. The simulation results show that the proposed method can establish a more accurate wind power output probability model, and get more reliable results of probabilistic load flow.
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