CASE STUDY 3 China Energy Investment Corporation China Energy has pioneered the use of digital and intelligent early warning systems to create a closed-loop process that links monitoring, forecasting, operational management and planning. By integrating advanced meteorological monitoring equipment, big data analytics and AI algorithms, the company has built a collaborative, intelligent and highly efficient meteorological support capability. This system enables comprehensive situational awareness of weather changes across all operational regions, significantly enhancing both operational efficiency and risk resilience. –Precision decision-making: Real-time, high-accuracy meteorological data and risk warnings provide a scientific basis for management decisions across production, logistics and sales. For example, before the onset of heavy rainfall, precise precipitation forecasts allow the company to adjust coal mining schedules in advance, preventing equipment flooding and reducing the risk of personnel injury. –Proactive contingency planning: Based on early warnings, China Energy formulates forward-looking emergency plans for production, transportation and sales, optimizing resource allocation and improving the foresight and scientific basis of decision-making. This proactive approach enables business units and subsidiaries to prepare thoroughly for adverse weather, minimizing operational disruptions and economic losses, while maximizing resource utilization and cost control. Source: China Energy Investment Corporation.24 CASE STUDY 4 Beijing Drainage Group Beijing Drainage Group is a state-owned enterprise responsible for wastewater treatment, drainage management and flood control in the centre urban area of Beijing. The company has harnessed digitalization and AI to transform urban flood risk management, for example by establishing a “smart flood control” command and dispatch system that integrates over 300 video monitoring points at pump stations, underpasses and known waterlogging hotspots. Proprietary AI algorithms analyse video feeds in real time to identify water accumulation, replacing manual inspection with a more efficient, automated process. –Digital twin and risk simulation: The company has developed a digital twin model for urban flood risk simulation, enabling precise prediction of waterlogging based on real-time rainfall forecasts and hydrological modelling. This supports intelligent scheduling and rapid emergency response. –Automated meteorological monitoring and alerts: All high-risk locations are equipped with automated weather monitoring and alert systems. Leveraging the BeiDou satellite system, the company can pinpoint stormwater inlets to within 50 centimetres, enabling field teams to quickly locate and clear blockages. Mobile applications ensure that early warnings and dispatch instructions are instantly communicated to all relevant personnel, streamlining the emergency response. –Upgraded infrastructure for rapid response: To support early warning with rapid action, Beijing Drainage Group has upgraded 76 underpass pump stations in the city centre, expanded rainwater pipelines and increased pumping and storage capacity. The total pumping capacity has nearly doubled and storage capacity now exceeds 200,000 cubic metres, providing a robust hardware foundation for fast drainage following early warnings. Source: Beijing Drainage Group.25 By integrating national meteorological resources with enterprise-level digital innovation, China’s utilities sector is setting new standards in predictive risk assessment and early warning. These advanced systems not only enable more precise and timely responses to extreme weather but also support smarter, more resilient operations across the entire utilities value chain. As climate risks continue to evolve, the ongoing development and deployment of such technologies will be critical to safeguarding infrastructure, ensuring service continuity and protecting communities. Building Climate-Resilient Utilities: Lessons from China and Future Pathways 13

Building Climate Resilient Utilities 2025