PARALLEL AND DISTRIBUTED STATE ESTIMATION

The need in recent years for higher frequency in state estimation exec ution covering larger supervised networks has led to the investigation of faster and numerically more stable state estimation algorithms. Ho wever, technical developments in distributed Energy Management Systems , based on fast data communication networks, open up the possibility o f parallel or distributed state estimation implementation. In this pap er, this possibility is exploited to derive a solution methodology bas ed on conventional state estimation algorithms and a coupling constrai nts optimization technique. Numerical experiments show suitable perfor mance of the proposed method with regard to estimation accuracy, conve rgence robustness and computational efficiency. The results of these e xperiments also indicate the decoupled nature of the state estimation problem.