Dynamic topology adaptation for distributed estimation in smart grids

This paper presents new dynamic topology adaptation strategies for distributed estimation in smart grids. A dynamic exhaustive search-based topology adaptation algorithm and a dynamic sparsity-inspired topology adaptation algorithm, which can exploit the topology of smart grids with poor-quality links and obtain performance gains, are proposed. An optimized combining rule, named the Hastings rule, is incorporated into the proposed dynamic topology adaptation algorithms. Compared with existing techniques for distributed estimation, the proposed algorithms have a better convergence rate and significantly improve the system performance. The performance of the proposed algorithms is compared with that of existing techniques in the IEEE 14-bus system.