The Practical Engineering Application of Improved Grey Prediction Model in Power Load Forecasting

In the process of power system operation and planning research, Medium and Long-Term Load Forecasting is an important content, and plays a crucial part in ensuring the stability and reliability of power system. The social and economic benefits of power system operation are directly affected by the accuracy of forecasting results. Low prediction accuracy is one of the significant shortcomings of the traditional gray prediction model. The basis of this study is the GM (1,1) model in the gray system. Through analyzing the limitations of this model, the method of smoothing the original data, the method of using the data of the latest year in the historical data as the initial value of the prediction model, and the method of modifying the original model by residual processing are adopted. The accuracy of load forecasting is improved. Through the study of the simulation results of a practical example in a certain area, it is found that compared with the traditional grey prediction model, the accuracy of the data prediction results of the prediction model has been effectively improved after the improvement, and the effectiveness of the improved measures has been verified.