期刊
IEEE TRANSACTIONS ON POWER SYSTEMS
卷 36, 期 2, 页码 1264-1273出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2020.3013677
关键词
Voltage measurement; Current measurement; Phasor measurement units; Robustness; Jacobian matrices; Transmission line measurements; Power measurement; Huber loss function; pmu; power system operation; rtu; scada; schweppe-type estimator; state estimation
This paper introduces a hybrid linear robust state estimator to enhance the accuracy of power system State Estimation. Through improved automatic bad data rejection and simplified formulations, the proposed SE formulation allows for more efficient estimation in real-world large-scale grids.
This paper intends to improve the accuracy of power system State Estimation (SE) by introducing a hybrid linear robust state estimator. To this end, automatic bad data rejection is accomplished through an M-estimator, i.e. a Schweppe-type estimator with Huber loss function. The method of Iteratively Reweighted Least Squares (IRLS) is used to maximize the likelihood function in the M-estimator. Leverage measurements are also treated by a simple yet effective formulation. To run the algorithm for real-world large-scale grids, cumbersome construction of the Jacobian matrix at each iteration is avoided. In addition, convergence to the local minima faced in the large-scale Gauss-Newton algorithm is not a concern as the proposed formulation is linear with no approximation. As observability and redundancy considerations mandate SE to take advantage of traditional SCADA measurements along with available PMU measurements, the linearity of the proposed SE formulation is guaranteed regardless of whether PMU-only, SCADA-only or hybrid SCADA/PMU measurements are utilized. In this regard, covariance matrix for measurements weights is derived for both types of measurements. Thanks to the linear formulation and therefore swiftness of the proposed algorithm, SE could be run for different power systems with a few up to thousands of buses.
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