Optimization planning of reactive power compensation for rural power grids by improved genetic algorithm

With the minimized sum of annual electrical energy loss and the investment for reactive power compensation equipment as an objective function, some mathematics models about fundamental load flow, harmonic component current, reactive power compensation and optimal planning of a rural power grid were set up. According to the feature of numerous nodes and complex calculation of the grid, a sensibility information matrix was established and an improved genetic algorithm was adopted for solving the above models. The improved genetic algorithm was to combine optimal solution found by genetic algorithm with sensibility information. The results show that the fundamental load flow, harmonic current and reactive power compensation can be observed on line. On the other hand, the total harmonic current distortion rate averagely dropped by 1.13%, the amplification levels of 3, 5, 7 order harmonics also dropped by 1% after optimizing the rural power grid, and operation expense for the rural power grid can be saved by 9%, as compared with those before optimizing. Therefore this improved genetic algorithm has good searching function and economic value.