基于模糊隶属度的电力系统抗差估计

Power System Robust Estimation Based on Fuzzy Membership

提出了一种电力系统模糊自适应抗差估计(fuzzy adaptive robust estimation,FARE)方法。计及了量测权重的不确定性,以连续的模糊隶属度评价测点的优劣,很好地解决了测点非优即劣的问题,以最小化测点劣质性的加权模糊隶属度之和为优化目标,采用原对偶内点法(Primal-Dual Interior Point Method,PDIPM)求解,并且实现了对量测粗差的自适应。多个IEEE标准算例以及波兰系统的仿真测试结果表明,该方法具有良好的抗差性能。

This paper proposes a Fuzzy Adaptive Robust Estimation (FARE)method. The method judges the quality of measurements based on the continuous fuzzy membership func-tion considering the uncertainty of the measurements’weights to avoid the judgment that regards a measurement as either god or bad,and the optimal objective lies in the minimal sum of weighted fuzzy membership,which is solved by the Primal-Dual Interior Point Method (PDIPM,and the self-adaption to the gross errors is realized too. Simulated results on several IEEE standard systems and a polish system indicate that the method proposed in this paper has a robust performance against gross errors.