New Method based in Particle Swarm Optimization for Power Factor Remote Control and Loss Minimization in Power Systems with Wind Farms Connected

This work describes the development of a new algorithm for the solution of a multi-objective problem in power systems with wind produces connected using Particle Swarm Optimization. Basically, the purpose is to search an optimal operation point of system which allows simultaneously power factor remote control and loss minimization. The instruments used for succeeded results are the reactive power produced by wind generators and power flow at feeder buses of distribution company. Broadly, wind farms have grids with predominant radial feature become mixed systems ill-condicional grids. The hybrid load flow option, composed by Gauss-Seidel and Power Summation Method, make viable several systems simulations, including optimal analysis. The principle proposed used to obtain the data from vulnerability analysis to characterize the power system, with no necessity of knowing the whole set of network parameters. A hybrid load flow using parameters of the Z_bus matrix without the formal construction algorithm is presented. The optimization problem was solved by three different formulations: gradients in radial networks, particle swarm optimization and evolution particle swarm optimization. The results obtained in the system with 417 buses demonstrated the efficiency of the proposed methods, once in all the simulations carried out for different operation conditions no convergent difficulties occurred using the hybrid load flow, the power factor in the interconnection bus was kept close to the unit and have got advance in loss minization acquired using de optimal load flow.