Robust state estimation for power systems via moving horizon strategy

In this paper, I propose a re-weighted moving horizon estimation (RMHE) to improve the robustness for power systems. The RMHE reduces its sensitivity to the outliers by updating their error variances real-time and re-weighting their contributions adaptively for robust power system state estimation (...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Chen, Tengpeng
مؤلفون آخرون: School of Electrical and Electronic Engineering
التنسيق: مقال
اللغة:English
منشور في: 2017
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/84091
http://hdl.handle.net/10220/42960
الوسوم: إضافة وسم
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المؤسسة: Nanyang Technological University
اللغة: English
الوصف
الملخص:In this paper, I propose a re-weighted moving horizon estimation (RMHE) to improve the robustness for power systems. The RMHE reduces its sensitivity to the outliers by updating their error variances real-time and re-weighting their contributions adaptively for robust power system state estimation (PSSE). Compared with the common robust state estimators such as the Quadratic-Constant (QC), Quadratic-Linear (QL), Square-Root (SR), Multiple-Segment (MS) and Least Absolute Value (LAV) estimator, one advance of RMHE is that the RMHE incorporates the uncertainty of process model and the arrival cost term during the optimization process. Constraints on states are also taken into account. The influence of the outliers can be further mitigated. Simulations on the IEEE 14-bus system show that the RMHE can obtain estimated results with smaller errors even when the outliers are present.