风电负荷分布式系统无聚类随机优化调度

Non-clustering Stochastic Optimal Scheduling of Wind Power Load Distributed System

为提高电网经济调度的随机优化性能,提出风电负荷分布式系统无聚类随机优化调度算法。首先,针对含风电场的电网经济调度问题,提出考虑多风场的电网经济调度模型,并利用Copula函数建立多维依赖边缘分布的多风场随机出力概率分布模型,将其作为Parato解集选取中的参考指标;其次,引入随机分布估计算法对所提模型进行多目标优化,同时为提高算法优化性能,采用高斯模型的种群生成方式改进随机分布估计算法中的聚类过程,实现了规则随机分布估计算法的进化过程简化,有助于提高进化种群的分布多样性和计算效率;最后,通过在选取的标准测试函数和国内某省电网模型上的模拟仿真结果显示,所提算法具有更高的目标优化精度和计算效率。

In order to improve the stochastic optimization performance of power grid economic dispatch, a clustering free stochastic optimal dispatch algorithm for wind power load distributed system is proposed. Firstly,aiming at the problem of power grid economic dispatch with wind field, a economic dispatch model considering multi-wind field is proposed, and a multi wind field random output probability distributed model with multi-dimensional edge dependent distribution is established by using Copula function, which is used as the reference index in the selection of Pareto solution set. Secondly, the random distribution estimation algorithm is introduced for multi-objective optimization of the proposed model. Meanwhile, in order to improve the optimization performance of the algorithm, the clustering process of the random distribution estimation algorithm is improved by using the population generation method of Gaussian model, and the evolution process of the rule random distribution estimation algorithm is simplified, which is helpful to improve the distribution diversity and computational efficiency of the evolutionary population. Finally, the simulation results on the selected standard test functions and a provincial power grid model in China show that the proposed algorithm has good target optimization accuracy and calculation efficiency.