China Securities Co., Ltd.: The electricity reform is gradually entering deep waters, with AI reshaping the new blue ocean of power trading.

China Securities Co., Ltd. releases a research report stating that China's electricity reform is gradually entering a deep water area. With the comprehensive deployment of the electricity spot market and increasingly complex trading rules, leveraging AI to empower electricity trading to "reduce costs, increase revenues, and control risks" has become a core proposition for the development of various market entities. The exploration and application of massive high-value data is key to building this core competitive barrier. Looking at mature market experiences in the US, Europe, and Australia, whether it is dealing with price fluctuations at nodes or the volatility brought by a high proportion of new energy grid connections, AI has evolved from being an auxiliary tool to a survival necessity. With the smooth implementation of national policies and the steady progress of the spot market, the increase in electricity price volatility is expected to rapidly open up demand space for AI trading products and services for electricity market entities. In a neutral valuation scenario, assuming an AI penetration rate of 75%, the incremental space for AI-empowered electricity trading market by 2030 will reach 29.52 billion yuan. Key points of China Securities Co., Ltd. are as follows: Riding on the momentum of electricity reform, AI is reshaping a new blue ocean for electricity trading. China's electricity system reform is gradually entering a deep water area, and the country is accelerating the construction of a nationwide unified electricity market system at the national level, strengthening the core role of spot markets in discovering real-time prices and accurately reflecting supply and demand, with the aim to achieve regular operation of the spot market by 2027. By 2025, the total electricity consumption in society has almost reached 10 trillion kilowatt-hours, with market-based trading accounting for over two-thirds. With the comprehensive deployment of the electricity spot market and increasingly complex trading rules, leveraging AI to empower electricity trading to "reduce costs, increase revenues, and control risks" has become a core proposition for the development of various market entities. The exploration and application of massive high-value data is key to building this core competitive barrier. Looking at global practices, the exploration and practice of overseas advanced markets. The US relies on real-time clearing mechanisms and node pricing systems to drive AI to focus on high-frequency forecasting and precise node arbitrage, making it the "ultimate battlefield" of algorithmic competition; Europe, through cross-border market coupling and diversified product systems, leads AI in the aggregation of virtual power plants and large-scale application of system-level models, solving the "complex constraints" of cross-border coordination; Australia, as a high-proportion wind and solar energy storage extreme pressure field, the extreme price fluctuations force AI to shift from an efficiency tool to a "survival necessity", leading the arms race in high-frequency trading. Industry benchmarks, models and progress of global electricity trading leaders. Global electricity trading pioneers such as Octopus Energy, Fluence Energy, Second Foundation, rely on their deep industry background and cutting-edge AI algorithms, combined with various approaches such as aggregation of distributed resources and intelligent scheduling of energy storage systems, to effectively capture real-time price fluctuations in the electricity market, successfully turning them into high certainty and scalable excess profits. Market space calculation: With the smooth implementation of national policies and the steady progress of the spot market, the increase in electricity price volatility is expected to rapidly open up the demand space for AI trading products and services from electricity market entities. In a neutral valuation scenario, assuming an AI penetration rate of 75%, the incremental space for AI-empowered electricity trading market by 2030 will reach 29.52 billion yuan. Risk warning: Model prediction deviation and market adaptation risks; data quality and security compliance risks; algorithm black box and regulatory penetration risks; technical dependence and system resilience risks; business model and investment return risks.