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Correlation Analysis of Wind Power Based on Mixed Copula Model and Its Application into Stochastic Dispatch

机译:基于混合Copula模型的风电相关性分析及其在随机调度中的应用

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There is a strong correlation among wind power outputs within the same area. However, the correlation is not considered in traditional error scenario generation methods. This paper analyzes characteristics of four Copulas based on the correlation theory, and build a mixed Copula function model according to a linear combinations of four Copulas. A new error scenario generation method is proposed using this mixed Copula function model. Also, it is verified that the mixed Copula function has better performance than the single Copula function in fitting accuracy. To further testify the utility of this method, we compare the solutions obtained from two different stochastic economic dispatch models. Furthermore, stochastic dispatch simulation on IEEE 39-bus system and a real provincial power system is performed and the results obtained are analyzed according to evaluation indices including accessible wind energy, conventional units' outputs and the objective value. The simulation results on two systems with different sizes show the proposed method is beneficial to accommodate more wind energy through dispatching.
机译:同一区域内的风能输出之间存在很强的相关性。但是,在传统的错误方案生成方法中未考虑相关性。本文基于相关理论分析了四种Copulas的特征,并根据四种Copulas的线性组合建立了混合Copula函数模型。利用该混合Copula函数模型,提出了一种新的错误场景生成方法。此外,已证实混合Copula函数在拟合精度上具有比单个Copula函数更好的性能。为了进一步证明该方法的实用性,我们比较了从两种不同的随机经济调度模型中获得的解决方案。此外,在IEEE 39总线系统和实际省级电力系统上进行了随机调度仿真,并根据可访问的风能,常规单位的输出和目标值等评估指标对获得的结果进行了分析。在两个不同大小的系统上的仿真结果表明,该方法有益于通过调度来容纳更多的风能。

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