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Keywords
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State estimation, Two-stage stochastic programming, μ-PMU placement, Situational awareness, Distributed generation, Asymmetrical distribution network
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Abstract
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Distribution system state estimation provides essential data for the system monitoring and control, which some uncertain parameters such as the intermittent and varying output of distributed generation (DG), random meter errors, and inaccurate network parameters make situational awareness of distribution systems a challenging issue. To address these issues, this paper develops an innovative two-stage stochastic programming model, where in the first stage, optimal μ-PMU placement is implemented aiming at minimizing the installation cost of μ-PMU and maximizing the number of measurement redundancy and the system observability in the presence of zero injection nodes (ZIN), while in the second stage state estimation of three-phase asymmetric DG-integrated distribution systems is performed to enhance situational awareness. By applying the proposed model, the optimal locations of μ-PMUs in the presence of ZINs and various contingencies were achieved, and the distribution system estimate estimation was obtained with high accuracy and low error percentage. The feasibility of the proposed methodology is verified on the modified IEEE 85 bus distribution system.
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