Power data quality inspection and repair model based on neural network

This article first builds an implementation framework for incentive demand response, and explains how load service entities gather demand-side resources to participate in power market business. Then, the characteristics of the algorithm based on long short memory (LSTM) are analyzed, and an LSTM data-driven incentive-based demand response user behavior prediction method is proposed. Finally, in order to verify the accuracy of the proposed forecasting method, an example analysis was carried out on the proposed forecasting method. The simulation results show that, compared with the least squares method and k-nearest prediction method, the LSTM data-driven incentive demand response user behavior prediction method can significantly improve the prediction accuracy.