Nowadays, using distributed generation (DG) resources, such as wind and solar, also improving the voltage profile in distribution companies has been considered. As optimal placement and sizing of shunt capacitors become more prevalent, utilities want to determine the im
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Nowadays, using distributed generation (DG) resources, such as wind and solar, also improving the voltage profile in distribution companies has been considered. As optimal placement and sizing of shunt capacitors become more prevalent, utilities want to determine the impact of the various capacitors placement in distribution systems. Locating and determining the optimal capacity of shunt capacitors in order to reduce power losses and improving the voltage profile and using the maximum capacity of transmission lines, are one of the common problems in the design and control of power systems. Using the shunt capacitors, not only improve voltage profiles, but also reduce system losses. In this study, a genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are proposed forsimultaneous placement of capacitors and DG resources in order to reduce power losses and improve the voltage profile in a case study radial distribution network. Simulations applied on IEEE 70-bus and 86-bus test system, and finally solutions of the proposed algorithms are compared.
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