基于智能电表量测数据的配网线变关系反向识别

Reverse Identification of the Relationship of Feeder-Transformer Connectivity in Distribution Grid Applying Smart Meter Measurement Data

针对配电系统中存储的线变关系记录与实际运行情况不一致问题,基于能量守恒定理,从满足电量约束以及尽可能降低中压线路线损率波动幅度的角度出发,文章将配网线变关系智能识别问题转化为中压线路和配电变压器之间的组合优化问题,进而提出了一种配网线变关系识别模型。此外,为加快求解速度和提高识别准确率,通过合并电压波动相关性较高的配电变压器进行降维优化,之后采用分支定界算法进行求解。最后,基于用电信息采集系统获取的量测数据,利用MATLAB和CPLEX编程对所提方案进行实例分析,分析结果验证了识别方案的可行性和有效性。

According to the energy conservation theory,from the perspective of satisfying the power constraints and minimizing the fluctuation of the line loss rates of the medium-voltage lines,this paper converts the intelligent identification of the connection relationship in distribution networks into a combination optimization problem between medium-voltage lines and distribution transformers.Accordingly,an intelligent recognition model is proposed.In order to speed up the solution speed and improve the recognition accuracy,the dimension reduction optimization is performed by merging the distribution transformers with high correlation of voltage fluctuations.After that,the branch-and-bound algorithm is used to solve the problem,and the intelligent identification is realized.Finally,applying the measurement data obtained by the electricity information acquisition system,the proposed scheme is implemented with MATLAB and CPLEX for example analysis.The analysis results verify the feasibility and effectiveness of the identification scheme.