Solving Multiobjective volt/VAr Control Problem in Distribution Systems by Fuzzy Set Theory and Particle Swarm Optimization

Suwit Auchariyamet and Nattachote Rugthaicharoencheep


Power Systems, Multi-Agent Systems, Volt/VAr Control, Particle Swarm Optimization, Fuzzy Set


This work describes an optimal dispatch of three control devices (i.e. under load tap changer (ULTC) of a substation transformer, substation capacitors, and feeder capacitors) for multiobjective volt/VAr control in distribution systems. Five objectives of interest in the problem are energy loss, bus voltages, THD levels, power factor at substation and the total number of switching operations of all control devices. All the objectives are fuzzified using a trapezoidal membership function in fuzzy set theory and are integrated to represent a fuzzy decision value. Based on the obtained fuzzy decision value, a searching process by particle swarm optimization (PSO) algorithm is employed to find the optimal dispatch schedule that provides the best compromise among all the objectives. Case study is carried out with a modified 29-bus distribution system of Provincial Electricity Authority (PEA), Thailand to reveal the performance of the proposed methodology.

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