GCL Energy Technology Co Ltd has completed the first Real World Asset Tokenization (RWA) issuance in China's photovoltaic industry with Ant Digital Technologies, securing 200 million yuan ($27.4 million) in cross-border financing, the company said on Monday.

The initiative not only injects substantial new capital into GCL Energy Technology's growth plans but also establishes a novel financing model for Chinese photovoltaic companies seeking to fund green projects internationally, it said.

RWA represents a transformative approach to asset management, where physical assets are digitized as tokens on the blockchain, enhancing liquidity and market accessibility. For this inaugural issuance, GCL Energy Technology has tokenized two strategically significant solar power plants in Hunan and Hubei provinces, with a combined capacity of about 82 megawatts, to spearhead this new financing frontier, it said.

As the core entity of GCL (Group) Holdings Co Ltd, China's largest private power conglomerate, GCL Energy Technology has expanded its renewable energy footprint, with its total installed capacity reaching 5976.36 megawatts by the end of September, and renewable sources constituting 57.81 percent of this capacity.

This RWA initiative is a cornerstone in GCL Energy Technology's strategy to harness data for asset valorization, involving around 3,000 residential photovoltaic systems. By integrating artificial intelligence, blockchain, and IoT technologies, the project packages and stores operational and revenue data on the blockchain. This dual-chain and one-bridge architecture has garnered strong backing from prominent global investors, reinforcing RWA's role as a pivotal green finance tool that underscores the company's commitment to sustainable development and transparency, the company said.

At the same event, strategic ties were further cemented with a comprehensive partnership agreement signed with Ant Digital Technologies in Suzhou, Jiangsu province. The partnership will broaden to include joint construction, acquisition, and securitization of new energy assets, covering distributed, commercial, industrial, and residential photovoltaic power stations.

In addition, both parties will collaborate to develop AI large model applications for various scenarios including new energy generation forecasting, energy management optimization, and intelligent operations, driving the industry's move toward enhanced intelligence and sustainability.