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Risk constrained stochastic economic dispatch considering dependence of multiple wind farms using pair-copula

机译:考虑对数风电对多个风电场的依赖性的风险受限的随机经济调度

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摘要

With higher and higher penetration of wind power into power systems, dependence among the wind speeds of different wind farms should be considered when modeling the wind power outputs. In this paper, a novel pair-copula method is applied to formulate the dependence of multiple wind farms. A large number of stochastic scenarios, in which the complicated dependence of multiple wind farms are considered, are generated to represent the uncertainties of wind power based on quasi-Monte Carlo (QMC) simulations. To find an optimal dispatch solution, a risk constrained mean-variance (MV) model is constructed for the stochastic economic dispatch (SED) problem. The MV model considers economic cost and economic risk under the uncertainties of wind power simultaneously, among which economic risk is calculated by means of least variance of fuel cost. Moreover, with the probability density function (PDF) obtained for fuel cost, a predefined level of confidence interval is proposed to improve the MV model to acquire more practical dispatch solutions. For solving the multi-objective SED problem, group search optimizer with multiple producers (GSOMP) is employed in this paper. The effectiveness of the proposed pair-copula method and the improved MV model are validated via numerical simulations with a modified IEEE 30-bus system.
机译:随着风能在电力系统中的渗透率越来越高,在对风能输出进行建模时应考虑不同风电场的风速之间的相关性。在本文中,采用了一种新颖的对-关联法来建立多个风电场的依赖关系。基于准蒙特卡罗(QMC)模拟,生成了许多随机情景,其中考虑了多个风电场的复杂依赖性,以表示风电的不确定性。为了找到最佳的调度解决方案,针对随机经济调度(SED)问题构建了风险约束均方差(MV)模型。 MV模型同时考虑了风电不确定性下的经济成本和经济风险,其中经济风险通过燃料成本的最小方差来计算。此外,利用针对燃料成本获得的概率密度函数(PDF),提出了预定义的置信区间,以改进MV模型以获得更实际的调度解决方案。为了解决多目标SED问题,本文采用了具有多个生产者的组搜索优化器(GSOMP)。通过改进的IEEE 30总线系统的数值模拟,验证了所提出的配对对策方法和改进的MV模型的有效性。

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