AI Reshapes Power Industry: Wider Applications, Greater Challenges
▲ In Yaodongzhuang Village, Longyao Town, Longyao County, Xingtai City, Hebei Province, power workers operate robots for maintenance tasks.
As an advanced form of digital technology, Artificial Intelligence (AI) is transforming power generation, operation, and transmission, supporting the development of new power systems and new energy infrastructures. With the rapid integration of digital and intelligent technologies, how will AI empower the power sector? And how should risks and challenges be addressed?
Expanding Applications
In May, as solar power generation continued to rise, efficiently integrating these clean energy sources became a challenge. Real-time monitoring and accurate forecasting of Photovoltaic (PV) plant operations are crucial for managing large-scale PV integration.
In Jiangsu—a leading province in distributed PV capacity—State Grid Jiangsu Electric Power Company uses AI-powered distributed PV monitoring systems to track and predict the performance of over 610,000 low-voltage distributed PV systems (totaling 25+ GW). By analyzing generation patterns, weather forecasts, and satellite cloud data, the system achieves minute-level real-time monitoring and ten-day short-term forecasts, with 97% real-time estimation accuracy and 95% day-ahead prediction accuracy. This provides critical data for grid dispatching and local PV consumption.
Smart Inspections Are Also Gaining Traction. On May 10, strong winds in Shizuishan, Ningxia, blew a plastic strip onto a substation insulator. Instantly, the central control room 30 km away received an alert with precise location details, enabling quick hazard removal.
Liu Jiang, Head of the Substation Monitoring Team at State Grid Shizuishan Power Supply Company, noted that all 46 substations under their management now support remote AI inspections, achieving 100% coverage. AI can detect foreign objects, overheating, and cracks 24/7, slashing inspection time from four days (manual) to two hours (AI-powered AR “Smart Inspection Eye”).
Beyond Grid Management, AI Is Enabling Holistic Energy Governance. In Xiaoshan District, Hangzhou, Zhejiang, a regional energy management platform integrates charging stations, microgrids, and grid-side storage, using real-time monitoring and smart coordination to enhance grid stability and economic efficiency.
Leveraging First-Mover Advantages
Under the “Dual Carbon” goals, energy systems are evolving: sources are more diverse, grids more complex, and consumption more flexible. To ensure energy security and affordability while transitioning to green energy, intelligent upgrades are essential.
The International Energy Agency (IEA) predicts that digital technologies could cut oil and gas production costs by 10–20% and reduce solar/wind curtailment from 7% to 1.6% by 2040. Studies suggest digital solutions could help China reduce 1.4 billion tons of CO₂ annually.
Among energy sectors, power systems are leading in digitalization. A State Grid Energy Research Institute report shows that power sector digitalization contributes over 70% of energy-related efficiency gains, thanks to its high proportion of electronic devices.
· Generation Side: AI optimizes smart power plants (both thermal and renewable), lowering costs and improving efficiency.
· Grid Side: Digitalization enhances resource allocation and interconnection.
· Consumer Side: AI enables data-driven demand response, supporting flexible energy use.
“AI Is Critical for Building New Power and Energy Systems,” said Jiang Chengling, Deputy Director of Digital Operations at State Grid Jiangsu. “It overcomes limitations like data gaps, computational bottlenecks, and manual decision-making, addressing challenges in load balancing, equipment maintenance, and renewable integration.”
Technologies like computer vision, deep learning, and neural networks are unlocking new solutions—but cybersecurity, data privacy, and workforce adaptation remain key challenges.
▲In Yaodongzhuang Village, Longyao County, Hebei, power workers use robots for maintenance.
