Research Express | Xingkong Energy Science and Technology Receives Goldman Sachs and Over 30 Other Institutions; Energy Storage Capacity of 840.54MW Positioned for Market-Based Trading

On March 19, GCL Energy Technology Co., Ltd. (hereinafter referred to as “GCL Energy Tech”) hosted on-site research with over 30 global investment institutions, including Goldman Sachs, Castle Funds, Wellington Management, and HSBC Asset Management, at Beibu Gas Turbine Power Co., Ltd. in Suzhou Industrial Park. The event included roadshows and on-site visits. Company management engaged in in-depth discussions with investors on topics such as the scale of energy storage business, operational models, revenue expectations, and core advantages.

Energy Storage Business Scale and Growth: 840.54MW in Operation, Sufficient Project Reserves

During the research, institutions first focused on the current scale and future growth potential of the company’s energy storage business. GCL Energy Tech management introduced that to date, the company has commissioned a total of 840.54MW of new energy storage power stations, including 800MW on the grid side and 40.54MW on the user side. “The company currently has ample project reserves and strong financial backing. With the implementation of capacity price policies, energy storage business is expected to achieve both scale and efficiency breakthroughs.”

Independent Energy Storage Operation Model: Regional Differences Are Significant, Capacity Price Provides a “Safety Net” for Revenue

Regarding the operation and revenue models of independent energy storage projects, the company stated that strategies vary by region: projects within Jiangsu mainly focus on arbitrage through peak-valley price differences, while projects in Guangdong emphasize frequency regulation auxiliary services. “Overall, the revenue levels of our projects are good. In the future, as capacity price mechanisms are implemented, revenue models will become more stable. Even if subsidies decline, returns can be secured through ‘capacity price guarantees + market-driven efficiency gains.’” Management emphasized that the company will leverage its first-mover advantage to ensure steady and sustainable returns.

Future Revenue Expectations: Three Core Factors Drive Industry Segmentation

Regarding future revenue prospects for independent energy storage, GCL Energy Tech analyzed from three aspects: first, regional resource endowments determine revenue ceilings; supply-demand patterns and auxiliary service needs in different provinces directly impact profitability; second, capacity price policies provide a “safety cushion,” with Document No. 114 explicitly ensuring stable baseline income for grid-side independent energy storage based on available capacity; third, the ability to participate in market-based electricity trading is a key variable in revenue differentiation. With Document No. 136 removing mandatory storage pairing, spot trading has become the largest source of income and will continue to grow in proportion. “Overall, the industry will enter a new stage of ‘regional differentiation, policy support, and capability-driven success.’”

Core Advantages: Focus on High Marketization Regions, Multiple Revenue Streams Plus AI Empowerment

In terms of competitive advantages in the independent energy storage sector, the company prioritizes regions like Guangdong and Jiangsu, where electricity marketization is high and frequency regulation demand is strong. The revenue model of energy storage systems has evolved from early single arbitrage to a diversified structure of “energy trading + auxiliary services + capacity value.” The management team specifically mentioned that, as the electricity market deepens and AI technology is integrated, trading capability will become a core determinant of project profitability. “The company will leverage the Juxing AI Virtual Power Plant platform to optimize trading strategies, improve response speed, enhance trading capabilities, and ensure stable returns for energy storage assets across multiple markets.”

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Editor: Xiao Lang Kuai Bao