Beijing actively integrates artificial intelligence (AI) into its energy infrastructure, fundamentally reshaping how electricity is generated, distributed, and consumed. This transformation impacts daily operational efficiency nationwide.
Smart Energy in Action: The Chifeng Example
A hydrogen and ammonia factory in Chifeng, northern China, showcases AI's role. Powered by a closed microgrid of local wind and solar, it navigates renewable energy's volatility. An Envision AI-driven system dynamically adjusts production based on real-time weather, effectively balancing supply and demand to ensure high operational efficiency.
A Broader Strategic Imperative
Such projects highlight China's commitment to hydrogen decarbonization and its broader strategy: using AI to manage complexities of integrating more renewable energy. Experts like Dr. Zheng Saina acknowledge AI's potential for emissions tracking and forecasting, yet also caution about its growing power demands from data centers.
Formalizing the AI+ Energy Strategy
Despite leading global renewable installations, China struggles with efficient power integration. Cory Combs of Trivium China sees AI as vital for grid flexibility, a strategy formalized in September as “AI+ energy”. Beijing aims for deep AI integration across generation, grid operations, and industrial use, projecting numerous pilot projects and over 100 use cases by 2027. Officials aspire to achieve a "world-leading" standard of AI energy integration within three years, focusing on specialized tools.
Enhancing Grid Stability Through Prediction
AI offers immediate benefits in electricity demand forecasting. Dr. Fang Lurui stresses precise predictions of renewable output and consumption are essential for grid stability, enabling proactive planning and reduced reliance on coal. Shanghai's city-wide virtual power plant (VPP) demonstrates this, integrating diverse facilities to lower peak demand. A trial reduced it by over 160 megawatts, highlighting the critical need for robust, predictive systems in a distributed power landscape.
AI's Role in Carbon Markets
Beyond grid optimization, AI is being explored for China's national carbon market, regulating over 3,000 energy-intensive companies. These sectors account for over 60% of China's carbon emissions. Chen Zhibin suggests AI could assist regulators in validating emissions data, improving allowance distribution, and providing businesses with clearer cost insights.
Navigating Risks and Mitigating Impact
However, AI's opportunities are balanced by significant risks. Projections indicate China's AI data centers could consume over 1,000 TWh annually by 2030, comparable to Japan's total yearly use. Xiong Qiyang warns rapid AI growth could jeopardize climate targets due to China's coal-heavy power mix. Regulators are responding: a 2024 plan mandates data centers to boost energy efficiency and increase renewable power use by 10% annually. New facilities are encouraged in western provinces. Eastern operators also innovate, with Hailanyun developing an underwater data center near Shanghai, using seawater for cooling and offshore wind power.
The Net Impact: A Delicate Balance
Despite AI's increasing energy footprint, Xiong posits its net effect on emissions could ultimately be positive if strategically deployed. Applied to optimize heavy industry, power systems, and carbon markets, AI will remain indispensable to China's decarbonization efforts, even while introducing new pressures for policymakers to manage.
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Source: AI News
