基于数据挖掘的低压配电网运行状态评估方法

Evaluation Method for Operating State of Low-voltage Distribution Network Based on Data Mining

为解决低压配电网运行状态评估问题,首先建立低压配电网回路阻抗模型,提出基于电压与电流变化速率比值计算回路阻抗的近似方法;继而建立短期评估回路阻抗阵,并基于该阵对低压配电网停电、复电、负荷停运、窃电、线路老化等多种运行状态予以评估分析;同时建立中长期运行状态信息阵,并基于该阵和加权平均方法从停电次数、停电时间、最大负载率、窃电电量、线路老化率等5个方面对智能电表负荷供电情况进行评估分析;最后基于该分析结果对低压配电网络的中长期整体运行状态进行评估。通过实例分析验证了所提方法的可行性。

To solve the problem of operating state evaluation for the low-voltage distribution network, this paper firstly establishes a loop resistance model and presents an approximation method for calculation loop resistance based on specific value of change rate of voltage and current. Then it establishes a short-term evaluation loop resistance matrix and makes analysis for multiple operating states of the low-voltage distribution network such as power cut, power recovery, load outage, electricity stealing,line aging, and so on. Meanwhile, it establishes a medium and long term operating state information matrix, and on the basis of this matrix and the weighted average method, it makes evaluation analysis for load power supply of the smart meter in five aspects including power cut times, power off time, the maximum load rate, electricity stealing quantity and line aging rate. Finally, it evaluates integral medium and long term operating state of the low-voltage distribution network based on related analysis results and by means of instance analysis, it verifies feasibility of the proposed method.