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Multiarea Distribution System State Estimation via Distributed Tensor Completion
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DOI：10.1109/TSG.2022.3183190.png)
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This paper proposes a model-free distribution system state estimation method 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 three-way tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A distributed 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. The convergence properties of the distributed algorithm and the sufficient conditions on the number of samples for each smaller network that guarantee the identifiability of the factors of the state tensor are presented. To demonstrate the efficacy of the proposed algorithm and to check the identifiability conditions, numerical simulations are carried out using the IEEE 123-bus system and a large-scale real utility feeder.
Keyword:
Tensors
State estimation
Task analysis
Area measurement
Topology
Reactive power
Particle measurements
Tensor completion
canonical polyadic decomposition
distribution system state estimation
alternating direction method of multipliers
期刊
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9.8
论文数:
5.7K
被引数:
4.3W
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