Application Of Power System Short-term Load Forecasting Based On Wavelet Analysis

The economic operation of the power grid is to meet the safety production and ensure the quality of power supply. Power system load forecasting is the basis of the economic operation of the power grid. The result of power system load forecasting reflects the development status and economic level of the load, its accuracy is related to the safe and economic operation of power system. Accurate load forecasting can ensure the electricity demand and high quality electricity, effectively reduce the cost of electricity, improve people’s living standards and social satisfaction. With the steady advancement of socialist economy, the electricity market policy, and the reform of electric power enterprises, the competition is inevitable, so short term load forecasting is an indispensable part of power market operation, both power plants and electricity grid power basis, it’s a powerful tool and basis for accurate load forecasting directly related to the economic interests of the generation companies and power grid.This paper first introduces the concept of load forecasting, explains the study of load forecasting purpose and significance, the load forecast characteristics, the importance of short term load forecasting, prediction method and its development status, advantages and disadvantages of the different methods of forecasting and introduced based on wavelet analysis of electric power system short term load forecasting. It introduces the principle and classification of wavelet analysis and the wavelet function, which is applied to the short term load forecasting. It’s combined wavelet analysis and neural network to generate wavelet neural network prediction method, according to the load data of the area, it’s established wavelet analysis model, BP neural network model and wavelet neural network model, and the application of matlab, compared the results of load curve and the error analysis,concluded that the wavelet neural network has the characteristics of wavelet analysis.Compared with the neural network, wavelet neural network has the shorter training time and the better accuracy, its prediction results have better and more accurate.