Abstract
We propose a linear state estimation (SE) model with complex coefficients and variables suitable for processing large-scale data in electric power systems observable by phasor measurement units. The presented model is based on factor graphs and solved using the belief propagation (BP) algorithm. The proposed algorithm is placed in the non-overlapping multi-area SE scenario without a central coordinator. The communication between areas is asynchronous, where neighboring areas exchange only “beliefs” about specific state variables. Presented architecture directly exploits system sparsity, can be flexibly paralellized and results in substantially lower computational complexity compared to traditional SE solutions. Finally, we discuss performances of the BP-based SE algorithm using power systems with 118, 1354 and 9241 buses.
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