基于改进卡尔曼滤波的电力计量计费数据状态评价研究

Research on State Evaluation of Power Metering and Billing Data Based on Improved Kalman Filtering

针对电力计量计费数据通信方式多、数据量大的问题,提出了以改进无迹卡尔曼滤波进行电力计量计费数据状态评价的方法。分析了无迹卡尔曼滤波无迹变换原理,构建了动态传输策略。为进一步提高无迹卡尔曼滤波评价结果的精度,构建了自适应因子对算法进行修正,减少了算法运行过程中的影响因素。最后,为了验证提出算法的有效性和可行性,以IEEE-33节点电力系统为例进行了仿真分析。结果表明,改进卡尔曼滤波的电力计量计费数据状态评价可以满足电力计量计费数据状态评价的精度和实时性要求。

Regarding the problem of multiple communication modes and large data volume of power metering and billing data,a method for evaluating the status of electricity metering and billing data with improved unscented Kal⁃man filtering is proposed.The principle of unscented Kalman filtering is analyzed,and the dynamic transmission strategy is constructed.In order to further improve the accuracy of the unscented Kalman filtering evaluation re⁃sults,an adaptive factor is constructed to modify the algorithm and reduce the influencing factors in the operation of the algorithm.Finally,to verify the effectiveness and feasibility of the proposed algorithm,simulation analysis is con⁃ducted on the IEEE-33 node power system.The analysis results shows that the improved Kalman filtering for power metering and billing data state evaluation can meet the accuracy and real-time requirements of power meter⁃ing and billing data state evaluation.