| The site selections of substations based on load forecasting plays a significant role in distribution of network planning. The structure of distribution network is influenced by the site, the reliability and economic efficiency of power grid depend on whether the site is reasonable or not.This paper mainly discusses the application of intelligent algorithm in the network planning. The city power grid planning programs based on intelligent algorithms, which includes the city power grid load forecasting and substation site planning, is studied in the paper. It introduces the gray model, Wavelet and BP Neural Networks, and multiple linear regression model in the part of load forecasting. The three models are applied for example analysis, and simulating software is used for modeling and simulation. Optimizing the algorithms existed in the part of substation site selection. The significance of the substation site selection is represented first, and the theory of IA-PSO is formulated, then the specific planning project is designed according to actual factors which influence the site selection. And the IA-PSO is proposed after the standard particle swarm optimization algorithm is improved, by which, the simple mathematical model of the substation site selection is optimized. The GUI of MATLAB is applied here to make the functions of algorithm work. Finally a typical application is presented as a case study. The case shows that the method is more scientific, and of higher practical value in projects. |
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