考虑分布式电源不确定性与相关性的配电网状态估计

State Estimation in Distribution Systems Considering Distributed Generation Uncertainties with Correlations

可再生能源发电技术的发展以及在电网中日益普及的分布式电源(DG)给电力系统带来了更多不确定性,使电力系统状态估计量测数据不足的问题更加突出。当前多采用对DG进行伪量测建模的方法来提高系统量测冗余度,针对同时考虑DG之间的不确定性和相关性的伪量测建模研究相对薄弱的现状,提出了一种基于Pair-Copula风电功率相关性模型和高斯混合模型(Gaussian mixture model,GMM)等效不确定性模型的DG伪量测建模方法,该方法可以考虑复杂的DG出力相关性和不确定性,提高伪量测的准确性从而提高配电网状态估计的精确度。通过对经修改的IEEE-14节点算例系统进行仿真计算,说明所提方法能够合理刻画状态估计问题中分布式电源的出力不确定性与相关性,计算结果验证了所提方法的有效性。

The development of renewable energy resources(RESs)and distributed generation(DG)technology has brought more uncertainties to power systems and aggravated the problem of insufficient measurements in state estimation.In most studies,pseudo-measurement modeling is adopted to improve the measurement redundancy of the system.In view that the present pseudo-measurement modeling researches taking both uncertainty and correlation between DGs into consideration are relatively weak,this paper presents a DG pseudo-measurement model based on the Pair-Copula method to describe a wind power correlation,and a Gaussian mixture model(GMM)with an equivalent uncertainty to describe the uncertainty of the DGs.It was found that the developed method can improve the accuracy of pseudo measurements so as to improve the accuracy of state estimation for distribution networks.The results obtained based on a modified IEEE-14 bus network were analyzed and verified the correctness and validity of the proposed method,and showed that the proposed method can reasonably depict the uncertainty and correlation of DGs outputs in state estimation.