Damao Brings AI-Energy Coordination to Fujian
💡See how a 15,000P AI center is integrating storage, grid services, and compute operations.
⚡ 30-Second TL;DR
What Changed
The AI computing center’s first phase is planned at 15,000P of computing capacity.
Why It Matters
The deployment illustrates how AI data centers can treat electricity flexibility and storage as operational assets rather than fixed costs. If successful, the model could lower energy expenses, improve power resilience, and provide a replicable blueprint for regional AI infrastructure operators.
What To Do Next
Model your AI cluster’s hourly load and SLA requirements, then evaluate whether peak shaving, demand response, and storage dispatch can reduce its projected electricity cost.
Key Points
- •The AI computing center’s first phase is planned at 15,000P of computing capacity.
- •Damao will deploy an AI-energy coordination platform supporting peak shaving, demand response, auxiliary services, energy-efficiency optimization, and spot-market assistance.
- •The partnership includes design review, construction management, acceptance testing, energy-storage operations, and maintenance for batteries, PCS, and EMS systems.
- •The project targets a green AI computing hub serving research, finance, manufacturing, and healthcare across Fujian and South China.
🧠 Deep Insight
Background and context from public sources — not the original article. 5 sources cited.
🔑 Enhanced Key Takeaways
- •Damao Technology specializes in 'computing-power and electricity consumption coordination' (算电协同), a niche technical framework designed to mitigate the high operational costs of AI data centers.
- •The company successfully closed a Series A+ financing round in October 2025, raising nearly 100 million yuan to scale its energy-management infrastructure.
- •Damao maintains strategic industrial alliances with major Chinese technology and energy players, including SenseTime, CATL, and Sugon.
- •The firm's core value proposition centers on optimizing the consumption of clean energy within high-performance computing environments to align with China's national energy structure.
- •The project in Fujian leverages the regional infrastructure of the Fujian Big Data Group, reflecting a broader trend of provincial-level integration of AI computing and energy-grid management.
🛠️ Technical Deep Dive
- Focuses on AI-energy matching (AI能源配套) to resolve power supply constraints in high-performance computing clusters.
- Implements energy-storage operations and EMS (Energy Management Systems) to facilitate peak shaving and demand response.
- Integrates with PCS (Power Conversion Systems) to manage the bidirectional flow of electricity between the grid and computing center storage.
- Utilizes algorithmic optimization to align computing workloads with real-time energy market pricing and availability.
🔮 Future ImplicationsAI analysis grounded in cited sources
⏳ Timeline
📎 Sources (5)
Factual claims are grounded in the sources below. Forward-looking analysis is AI-generated interpretation.
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Original source: 雷峰网 ↗
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