Multi-Area Model-Free State Estimation via Distributed Tensor Decomposition

Liu, Yajing; Zamzam, Ahmed S.; Bernstein, Andrey

doi:10.1109/ieeeconf51394.2020.9443485

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Multi-Area Model-Free State Estimation via Distributed Tensor Decomposition

Liu, Yajing·Zamzam, Ahmed S.·Bernstein, Andrey

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Abstract

This paper proposes a model-free method for distribution system state estimation based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A third-order tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. To demonstrate the efficacy of the developed algorithm, numerical simulations are carried out using an IEEE test system.

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alternating direction method of multipliers canonical polyadic decomposition distribution system state estimation MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND DISTRIBUTION tensor completion

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Liu, Yajing, Zamzam, Ahmed S., Bernstein, Andrey. 2021-06-03. Multi-Area Model-Free State Estimation via Distributed Tensor Decomposition. https://doi.org/10.1109/ieeeconf51394.2020.9443485

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