Study On Power Load Forecasting In The Urbanization Construction Of Handan

With the continuous development of urbanization, the industrial structure, the ratio of urban and rural population and the income of urban residents will certainly change a lot. And these changes all have a great influence on electricity consumption, so it is necessary for power supply enterprises to make predictions about the power load during the construction of urbanization.Through the discussion of the concept, the goal and meaning of urbanization, this paper analyzes the feasibility and necessity of urbanization. Besides, this paper makes the influence of urbanization on electricity load forecasting clear. This paper selects the neural network model for the prediction of power load forecasting during urbanization after the comparisons of the theoretical basis and the data method selection difficulty of different methods. We choose and calculate the related factors of electricity consumption during 2000-2006 in the urbanization construction of Handan. The method of principal component analysis is used in factor selection. Based on the neural network model, the BP neural network power load forecasting model related to the urbanization construction is established. And the BP neural network toolbox in the MATLAB software is used to realize the model. We use the historical data of electricity consumption in 2007-2012 to test the model. According to the test error, the prediction model result of Handan electricity power load is quite satisfactory. And then the power load forecasting model is used for the prediction of the power load in 2013-2017 of Handan. The predicted results can provide reference for the planning work of Handan power grid. And this paper illustrates that it is feasible to use the neural network model for power load prediction in the process of urban construction.