NETWORK RECONFIGURATION ALGORITHM FOR AUTOMATED DISTRIBUTION-SYSTEMS BASED ON ARTIFICIAL-INTELLIGENCE APPROACH

This study develops an expert system to solve the problems of the main transformer (MTr) or feeder overload and the feeder constraint violation in automated distribution systems, where each feeder is subject to the thermal overload and voltage drop limits. Then, the objective is to perform the network reconfiguration by switching the tie and sectionalizing switches so that the system violation is removed, while achieving the load balance of the MTrs and feeders with a fewer number of switching operations. Since the switching operation in the practical system does not cause the large change in the voltage, an approximation method is used in order to check the voltage violation, instead of a full ac load flow solution. To reduce the search space, an expert system based on heuristic rules is presented, and implemented in Prolog. This system adopts the best-first tree search technique. List processing and recursive programming techniques are then utilized to solve the combinatorial type optimization problem. The computational results are also prepared to show the performance of the heuristic algorithms developed.