海博思创王劲松：AI赋能储能别做“表面功夫”，决策型技术才是破局关键

Core Insights - The "AI + Energy Development Conference" held in Beijing focused on exploring new paths and opportunities for the integration of AI and the energy industry, attracting over 300 representatives from government, energy companies, and experts [1] - Wang Jinsong, Chief Scientist of AI at Beijing Haibo Sichuang Co., emphasized the current limitations of AI applications in the energy sector, particularly in power and energy storage, where AI is primarily used for basic reporting and predictive maintenance rather than fully leveraging its potential [5] Industry Challenges - Wang identified five core pain points in the current application of AI in the energy storage sector: 1. Insufficient data quality and credibility hindering precise decision-making 2. High safety and operational standards in energy storage and grid sectors demanding rigorous AI output 3. Complexity of energy storage systems making AI solutions challenging 4. Balancing the cost of high-end AI models with their application value 5. Lack of clear decision-making hierarchies in AI, making it difficult to adapt to various energy storage and grid integration needs [6] Solutions and Innovations - To address these challenges, Wang proposed a "full-process, multi-scenario, and implementable" AI empowerment solution, highlighting Haibo Sichuang's transition from equipment supplier to power station operator, with significant projects like the 1GWh and 7.4GWh independent energy storage stations serving as practical examples [7] - The company has developed over 400 health indicators covering various levels of energy storage systems, optimizing operations to exceed industry averages, achieving a 20% reduction in auxiliary power consumption and a 3.5% improvement in overall performance [7] - Wang emphasized that AI empowerment in energy storage is not merely a single technology application but a comprehensive system that connects data seamlessly from the ground to the cloud, covering the entire chain from R&D to operation [8] Future Outlook - The future of AI in the energy storage sector is expected to play a more critical role in decision-making, with Haibo Sichuang committed to deepening the integration of AI and energy, accumulating practical experience to address industry pain points and promote more efficient, stable, and economically viable energy storage solutions [8]