Abstract
In this paper, a distributed state estimation method based on moving horizon estimation (MHE) is proposed for the large-scale power system state estimation. The proposed method partitions the power systems into several local areas with non-overlapping states. Unlike the centralized approach where all measurements are sent to a processing center, the proposed method distributes the state estimation task to the local processing centers where local measurements are collected. Inspired by the partitioned moving horizon estimation (PMHE) algorithm, each local area solves a smaller optimization problem to estimate its own local states by using local measurements and estimated results from its neighboring areas. In contrast with PMHE, the error from the process model is ignored in our method. The proposed modified PMHE (mPMHE) approach can also take constraints on states into account during the optimization process such that the influence of the outliers can be further mitigated. Simulation results on the IEEE 14-bus and 118-bus systems verify that our method achieves comparable state estimation accuracy but with a significant reduction in the overall computation load.
Highlights
Power system state estimation (PSSE) plays an indispensable part in the power industry [1].One common centralized approach named the weighted least squares (WLS) has been widely used for PSSE, employing a nonlinear measurement model
The partitioned moving horizon estimation (PMHE) is more reasonable and suitable for large-scale systems monitoring because each local area solves for the local states via a smaller optimization problem and the computational load is smaller whereby measurements are only sent to the local estimator but not to the centralized estimator, so a large amount of communication burden would be saved
We illustrate the effect of the number of phasor measurement units (PMUs) installed in the power systems and consider two scenarios: one with redundant observations on selected buses and one with a minimum number of PMUs for full topological observation
Summary
Power system state estimation (PSSE) plays an indispensable part in the power industry [1]. The PMHE is more reasonable and suitable for large-scale systems monitoring because each local area (or subsystem) solves for the local states via a smaller optimization problem and the computational load is smaller whereby measurements are only sent to the local estimator but not to the centralized estimator, so a large amount of communication burden would be saved. In this paper, considering the high speed of mMHE, the accuracy of MHE, and the advantage of PMHE to implement the MHE in a distributed way, a distributed state estimation method named the modified PMHE (mPMHE) is proposed and implemented for PSSE. The mPMHE achieves comparable state estimation accuracy but with a significant reduction in the overall computation load It is a distributed algorithm and is suitable for large-scale PSSE. The simulations on the IEEE 14-bus and 118-bus systems are shown in Section 4 and conclusions are made in Section 5 respectively
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