Xunce (03317) and Tianhe Computing Power signed a strategic cooperation memorandum to jointly explore data infrastructure and energy token factory models based on the integration of AI and energy

Zhitong Finance App News, Xunce (03317) issued an announcement. The company and Jiangsu Tianhe Computing Technology Co., Ltd. (Tianhe Computing) officially signed a strategic cooperation memorandum. Tianhe Computing Power is a wholly-owned subsidiary of Tianhe Solar Energy Co., Ltd. (Tianhe Solar), a leading listed company in the global photovoltaic industry, focusing on green intelligent computing and “artificial intelligence+” businesses. In recent years, Tianhe Computing Power has promoted “computational and electronic collaboration” with the goal of artificial intelligence data centers (AIDC), and laid out computing power bases through capabilities such as integrated source network load storage, direct green power supply, and high-power liquid-cooled cabinets to form a comprehensive service capability covering green energy and computing power infrastructure.

This strategic cooperation will fully integrate the resources and advantages of the two sides in terms of data, computing power, energy and industry channels, and cooperate in the direction of large-scale energy classification models, data capitalization, computing power collaboration and computing power cooperation, and commercialization of token factories to jointly explore data infrastructure and energy token factory models based on the integration of AI and energy. This cooperation marks a further extension of the company's data tokenization capabilities to the solar energy industry.

According to the strategic cooperation memorandum, the company and Tianhe Computing will carry out the following strategic cooperation:

1. Jointly build energy data infrastructure and large vertical model capabilities. The two sides will jointly promote the access, governance and modeling of energy industry data, and jointly develop large-scale energy vertical models. The company will rely on its capabilities in data infrastructure, data governance, data fusion and data modeling to support the aggregation, cleaning and labeling of heterogeneous data from multiple sources such as distributed energy, IoT equipment, and power plant operations; Tianhe Computing will provide actual business scenarios and industry experience in photovoltaics, energy storage, and power plant operation. The two sides will jointly deposit high-quality data sets and reusable vertical models for the energy industry to provide a data foundation for large-scale energy models and industry agent applications.

2. Create computer collaboration and green computing power application scenarios. The two sides will focus on Tianhe Computing's “power supply→IDC” business transformation and jointly explore a benchmark implementation scenario for power collaboration and computing power coordination. Relying on Tianhe Computing's computing power base layout in green power rich areas such as Ulanqab in Inner Mongolia and Zhongwei in Ningxia, the two sides will explore cooperation models such as computing power equipment investment, computing power services, computing power scheduling, and computing power hosting; at the same time, they will combine Tianhe Computing's direct supply capabilities to jointly promote the large-scale implementation of green computing power services.

3. Explore energy token factory business models and data asset applications. The two sides will jointly explore business model innovations such as data capitalization and token billing for the energy industry. Relying on the company's token factory model, explore connecting energy data, energy vertical models, and intelligent capabilities to the token ecosystem to achieve flexible billing through subscription systems, transaction systems, or token pay-as-you-go methods. At the same time, the two sides will explore compliance management, authorization and capitalization of operating data deposited in power plants and data centers, promote the participation of data assets in the data element market, and promote the transformation of energy data value.