Application of Artificial Intelligence in Predicting Transmission and Distribution Electricity Prices

Transmission and distribution (T&D) are important links in the construction of electric energy. In order to improve the real-time and reliability of T&D electricity price prediction, this paper combined artificial intelligence (AI) technology and used Support Vector Machine (SVM) algorithm to conduct in-depth research on T&D electricity price prediction. This article first analyzed the influencing factors of T&D electricity prices, and then described the prediction of T&D electricity prices as a mathematical mapping problem. The problem of T&D electricity price prediction was optimized, and finally, the SVM algorithm was used to construct a T&D electricity price prediction model. To verify the effectiveness of the model, this article compared it with Convolutional Neural Network (CNN) algorithm and Long Short-Term Memory (LSTM) algorithm in terms of prediction accuracy and efficiency. The experimental results showed that in terms of prediction efficiency, compared to CNN algorithm and LSTM algorithm, SVM algorithm improved the average prediction completion rate of the prediction model by 3.8% and 5.4%, respectively. The conclusion indicated that SVM algorithm under AI technology can effectively improve the efficiency of T&D electricity price prediction, which helps to promote the high-quality development of the electricity market.