Research on Regional Line Loss Prediction Method for Power Grid Based on Grey Wolf Algorithm
In order to solve the problem of significant differences between the predicted results and the actual situation when predicting power grid line losses,this study introduces the Grey Wolf algorithm and designs a new method for predicting regional power grid line losses. Firstly,the abnormal values of regional power data in the power grid should be checked to eliminate unreasonable or incorrect values in the dataset,in order to avoid negative impacts on the prediction results. Secondly,reduce the dimensionality of the data to improve the overall prediction efficiency. Thirdly,based on the dimensionality reduction data features,construct a regional power grid line loss prediction model. Finally,the grey wolf algorithm is introduced to globally search for model parameters and achieve accurate prediction of line losses. The experimental results show that compared with existing prediction methods,the new method predicts a line loss rate that is closer to the actual value,indicating that the new method has higher prediction accuracy.
Grey Wolf algorithmpower grid environmentregional line lossline loss prediction
万方数据
维普
