Quasi real time state estimation of distribution systems using soft computing methodology

An approach based on methodology of soft computing is developed to estimate the quasi real time modes of operation in distribution systems taking into consideration uncertainty of information. The algorithms for constructing electrical load curves on the basis of processing short statistical samplings and expert estimates, forming fuzzy load estimates using aggregation of information, load coordination taking into account real time remote load measurements, and load forecasting are discussed in this paper. The effectiveness of using various aspects of soft computing, including heuristic procedures, apparatus of fuzzy set theory, neural network models and rule-based systems for solving the problems mentioned above is demonstrated. The proposed approach can provide valuable information to distribution system operation and planning.