Core Insights - The integration of AI in the electricity market can amplify both profits and losses, necessitating companies to have autonomous control capabilities when utilizing AI models [1][2][3] - The AI products in the electricity market are still in the exploratory phase, with varying degrees of success among companies using them [7][10] Group 1: AI in Electricity Trading - Companies like Qingpeng Intelligent Technology are focusing on developing AI agents for electricity trading, with commercial operations starting in 2023 [1][5] - Major energy companies are also developing their own AI products to predict renewable energy generation and electricity demand, which are critical for trading decisions [1][2] - AI models used in electricity trading primarily include time series models, which analyze data with a temporal dimension to make predictions [2][7] Group 2: Market Dynamics and AI Implementation - The electricity market has shifted from government-set pricing to market-driven pricing, increasing volatility in supply and demand [3][4] - In the first half of 2025, the cumulative market transaction volume reached 2.95 trillion kWh, a year-on-year increase of 4.8% [3] - AI's role in electricity trading is expected to grow, with companies increasingly adopting AI tools to enhance decision-making [5][10] Group 3: Challenges and Considerations - The complexity of electricity market rules and the need for human-defined boundaries in AI applications pose challenges for companies [11][12] - The effectiveness of AI models in trading is influenced by the quality and scale of data, as well as the ability to adapt to new scenarios [9][10] - Companies must balance the pursuit of high accuracy in predictions with the risk of overfitting, which can reduce the model's generalization ability [11][12]