Real-Coded Genetic Algorithm Applied to Optimal Placement of Capacitor Banks for Unbalanced Distribution Systems with Meshed/Radial Configurations

One of the most important methods in loss reduction and controlling the voltages of distribution systems is the utilization of the fixed and switched capacitors. To do this, real modeling of the system in large scale unbalanced or balanced for both radial and meshed configurations are required. In this paper, a new technique for finding the optimal values of the fixed and switched capacitors in the distribution networks based on the Real-Coded Genetic Algorithm (RCGA) is presented. In this method, the modeling of radial or loop feeders with unbalanced or balanced network loads are basically considered. Also, the modeling of the load at different levels is simulated which low voltage and medium voltage capacitors those are available in the market are used. Regarding the above factors in addition to the various parameters in optimization problem, the RCGA is used to find the best and real optimal network with the best rate for the capacitors. Finally, this methodology is tested on a region of the distribution network of the city of Ahvaz in Iran and satisfactory results are obtained. These results show that in addition to the decreasing of the network losses and improvement of the voltage profile, the benefit saving due to application of capacitors is increased.