Analysis Model of Adjustment Potential of Industrial Large Users Based on Data Set Reconstruction

Industrial load is a key part of the new load management system. Analyzing the adjustable potential of large industrial users is of great significance to alleviating the contradiction between power supply and demand and improving the load management capacity of the new power system. Due to the large power consumption and regularity of industrial load, its adjustable potential is huge and it is one of the most ideal demand response resources. First, the main production equipment of large industrial users is modeled and analyzed. Then, based on the improved K-means clustering algorithm and combined with the industrial user regulation potential evaluation index system, the data set of large industrial users is reconstructed to obtain a high adjustable potential data set of large industrial users. Finally, considering the adjustable potential characteristics of users, a Self-Training-Bi-LSTM potential prediction model is established to obtain the adjustable potential range of large industrial users. The example results show that the proposed model can analyze the adjustable potential of typical equipment of large industrial users, and the stability and accuracy of the model are high.