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This paper proposes new methods to select the optimal values of fixed and switched shunt capacitors in Radial distribution feeders for varying load conditions so as to maximize the annual savings and minimizes the energy loss by taking the capacitor cost into account. The identification of the weak buses, where the capacitors should be placed is decided by a set of rules given by the fuzzy expert system. Then the sizing of the fixed and switched capacitors is modeled using differential evolution (DE) and particle swarm optimization (PSO). A case study with an existing 15 bus rural distribution feeder is presented to illustrate the applicability of the algorithm. Simulation results show the better saving in cost over previous capacitor placement algorithm.

This paper presents new techniques for capacitor placement in radial distribution feeders in order to reduce the real power loss, to improve the voltage profile and to achieve economical saving. The identification of the weak buses, where the capacitors should be placed is decided by a set of rules given by the fuzzy expert system. Power loss and node voltage indices are used as inputs to the fuzzy expert system and the output is sensitivity index which gives the weak buses in the system where the capacitor to be placed. The sizing of the capacitors is modeled by an objective function to obtain maximum savings using Differential Evolution (DE) and Multi Agent Particle Swarm Optimization (MAPSO). To illustrate the applicability of the above algorithms, simulation is performed on an existing 15 bus and IEEE 34 bus distribution feeders. The results of the proposed approaches are compared with PSO, HPSO techniques and with results of those in the literature.

This paper presents an improved method for capacitor placement in radial distribution feeders to reduce the real power loss and to improve the voltage profile. The location of the nodes where the capacitors should be placed is decided by a set of rules given by the fuzzy expert system. The sizing of the capacitors is modeled by the objective function to obtain maximum savings using Differential Evolution (DE). A case study with an existing 15 bus rural distribution feeder is presented to illustrate the applicability of the algorithm. A comparison with the PSO is performed to show the improvement with the proposed algorithm.

This paper presents a novel method for capacitor placement in radial distribution feeders to reduce the real power loss and to improve the voltage profile. The location of the nodes where the capacitors should be placed is decided by a set of rules given by the fuzzy expert system. The sizing of the capacitors is modeled by the objective function to obtain maximum savings using Particle Swarm Optimization. A voltage constraint is taken and compared without the constraint. A case study with an IEEE 34 bus distribution feeder is presented to illustrate the applicability of the algorithm.