A concurrent non-recursive textured algorithm for distributed multi-utility state estimation

During power deregulation, power companies are releasing their transmission grids to form ISOs/RTOs while maintaining their own state estimators over their own areas. A recent trend for these ISOs/RTOs is to further combine and enlarge to become a bigger Mega-RTO grid for a better market efficiency. The determination of state over the whole system becomes challenging due to its size. Instead of a totally new estimator over the whole grid, the authors propose a distributed textured algorithm to determine the whole state; in their algorithm, the existing state estimators in local companies/ISOs/RTOs are fully utilized and the new estimator is no longer required. They need only some extra communication for some instrumentation or estimated data exchange. In addition, such an algorithm has the following advantages: (1) the distributed textured algorithm is nonrecursive, asynchronous and avoids central controlling node. Therefore, it is fast and practical; (2) based on exchanging data with neighboring companies/ISOs/RTOs, textured overlapped areas become part of the process. With the developed textured decomposition method, bad data detection and identification ability is better than existing distributed state estimation algorithm, especially when bad data occur around the boundary of individual estimators; (3) discrepancy on the boundary buses of different estimators decreases and the result over whole grid become more consistent. Moreover, when updating local estimation through estimated data exchanges, matrix modification techniques that utilize sparse techniques are developed to accelerate the computation speed. Detailed numerical tests are given to verify the efficiency and validity of the new approach.