中文摘要：

风功率概率分布模型的研究对于风电场规划以及运行都具有重要意义。提出了一种基于模糊序优化的风功率概率密度模型非参数核密度估计方法。该方法利用风电运行数据样本构建风功率概率密度的非参数核密度估计模型;然后建立用于模型带宽选择的多目标优化模型;最后利用模糊序优化对带宽优化模型进行求解。实际算例结果表明,所提建模方法完全由样本数据驱动,不需要对概率密度模型进行先验主观假设,因而具有更高的建模精度和更强的适用性。

英文摘要：

Study of wind power probability distribution model has important implications for wind farm planning and operation. This paper presented a non-parametric kernel density estimation method for modeling probability characteristics of wind power based on fuzzy distributed ordinal optimization. In this method, firstly, a non-parametric kernel density estimation model of wind power probability distribution was constructed by sampling wind power data. Then, a multi-objective optimization model was built for bandwidth selection. Finally, bandwidth optimization model was solved with fuzzy ordinal optimization. Numerical simulation results showed that the proposed modeling method was completely driven by the sample data, not requiring priori probability density model of subjective assumptions. Therefore, this model was more accurate and applicable.