AI資料中心轉型永續，從能源效率走向全面低碳治理

隨著生成式AI和高效能運算（HPC）的快速發展，全球資料中心正迎來新一波成長浪潮。面對龐大的能源需求與日益嚴峻的氣候變遷挑戰，新一代AI資料中心的永續性，已不再只是「用電效率」的問題，而是一場從建築設計、能源供應、運營管理到供應鏈選擇的全面性轉型。

With the rapid advancement of generative AI and high-performance computing (HPC), data centers worldwide are entering a new wave of growth. Faced with massive energy demands and the intensifying challenge of climate change, the sustainability of next-generation AI data centers is no longer just a matter of "energy efficiency" - it now calls for a comprehensive transformation that spans architectural design, energy supply, operations management, and supply chain decisions.

根據施耐德電機加拿大分公司（Schneider Electric Canada）安全電力副總裁Jim Kalogiros的觀察，AI資料中心最大的環境衝擊仍來自於其巨量的能源使用。「風能與太陽能是未來的重要選項，但這些再生能源供電並不穩定，因此仍需要天然氣等其他能源來補足。更關鍵的是，不論能源來源為何，企業都必須審視其碳中和的程度。」

According to Jim Kalogiros, Vice President of Secure Power at Schneider Electric Canada, the largest environmental impact of AI data centers still stems from their enormous energy consumption. "Wind and solar power are important options for the future, but they are intermittent by nature. That means we still need sources like natural gas to fill the gaps. More importantly, regardless of the energy source, companies must evaluate the carbon neutrality of their operations."

Sustainable Design Starts with Buildings and Equipment

建築與設備設計成為永續起點

資料中心的永續設計從最初的建築階段就開始。例如，建築採用高效節能的設計，使用可持續建材，同時預留空間與結構彈性，以應對未來5年內快速更新的設備需求。現代資料中心也開始採用模組化設計，使更新與替換更加靈活，減少未來拆除與重建的資源浪費。

此外，設備本身的效率也持續提升。隨著圖形處理器（GPU）設計演進，每單位運算所需的能耗逐漸下降，儘管整體運算負載與數據處理量仍快速成長。

冷卻系統與廢熱回收創造新價值

Sustainable data center design begins as early as the construction phase. This includes energy-efficient architecture, the use of sustainable building materials, and structural flexibility to accommodate equipment upgrades within the next five years. Modern data centers are also adopting modular designs that allow for easier system updates and replacements, minimizing the need for resource-intensive demolitions or reconstructions.

Meanwhile, the energy efficiency of computing equipment continues to improve. With advancements in graphics processing unit (GPU) architecture, the energy required for each unit of computation is gradually decreasing - even as overall computing workloads and data volumes continue to surge.

Cooling and Waste Heat Recovery Create New Energy Value

在能效管理方面，水冷系統成為主流方案之一。透過封閉式循環系統，資料中心可以重複使用冷卻水，同時將過程中移除的熱能回收，用來加熱建築或產生額外電力。這樣的設計不僅降低耗能，也為資料中心與周邊社區創造新的能源價值鏈。

數據驅動運營與預測性維護

Kalogiros指出，資料中心的運營效率是永續策略的另一個核心。資料中心基礎設施管理軟體（DCIM）能即時監控溫度、用電負載等關鍵數據，甚至可預測可能出現的熱點，主動調整冷卻資源配置。例如，當系統偵測到某一側機櫃即將過熱時，可立即將冷卻能力從另一側調度過來，提高整體能源使用效率。

此外，DCIM系統亦可藉由分析設備數據，預測電力異常或設備故障，主動啟動備援電力系統，降低非預期停機時間，並提升資源利用率。

供應鏈選擇走向低碳轉型

資料中心業者也越來越重視其供應鏈夥伴的永續表現。「當我們向某家公司採購設備時，我們會主動詢問他們的永續目標與碳中和進程。未來即使沒有法規要求，企業之間也會自然形成一套自律機制，優先與有永續承諾的供應商合作，」Kalogiros表示。

In terms of energy management, water-cooling systems have become one of the mainstream solutions. By using a closed-loop system, data centers can reuse cooling water and capture the heat removed in the process. This waste heat can then be repurposed to heat buildings or generate additional electricity. Such designs not only reduce energy consumption but also create new value chains by sharing energy with surrounding communities.

Data-Driven Operations and Predictive Maintenance

Kalogiros points out that operational efficiency is another pillar of a sustainable data strategy. Data center infrastructure management (DCIM) software enables real-time monitoring of key metrics such as temperature and energy load. It can also predict potential hot spots and proactively adjust cooling resources. For instance, if the system detects an imminent heat buildup in one server rack, it can instantly reroute cooling from other areas to optimize energy use.

DCIM systems also analyze equipment data to anticipate power anomalies or device failures, automatically activating backup systems to reduce unplanned downtime and improve resource efficiency.

Decarbonizing the Supply Chain

Data center operators are increasingly scrutinizing the sustainability performance of their supply chain partners. “When we procure equipment from a company, we actively ask about their sustainability goals and carbon neutrality progress,” Kalogiros explains. “Even without regulatory pressure, businesses are beginning to form self-regulated networks that prioritize working with partners committed to sustainability.”

舉例來說，施耐德電機已針對其伺服器設備包裝進行碳足跡評估，嘗試使用回收材料，並減少紙箱使用量。縮小包裝體積30%，不僅降低運輸成本與碳排，亦可提高運輸效率，一台貨車可運載更多設備。

政策趨勢：資料中心永續將成國際標準要求

資料中心的永續轉型並非企業單方面努力，政策面也正快速跟進。例如歐盟的《能源效率指令》（EED）已將大型資料中心納入能源報告範圍；而在美國與加拿大，資料中心運營者也面臨越來越嚴格的碳揭露與效率標準。

同時，投資者與用戶也開始將「永續運算」作為評估企業責任與風險控管的重要依據。例如Google、Microsoft、Amazon等大型雲端平台已承諾未來數年內全面採用再生能源供應其資料中心，並以「碳中和運算」為終極目標。

For example, Schneider Electric has assessed the carbon footprint of its server equipment packaging, tested the use of recycled materials, and reduced cardboard usage. By cutting package volume by 30%, they not only lower transportation emissions and costs but also improve logistics efficiency - enabling each truckload to carry more equipment.

Policy Trends: Data Center Sustainability Becoming a Global Standard

Sustainability in data centers is not solely driven by corporate initiatives - governments are catching up quickly with regulations. For example, the EU’s Energy Efficiency Directive (EED) now includes large-scale data centers in mandatory energy reporting. In the U.S. and Canada, operators are also facing stricter requirements for carbon disclosure and operational efficiency.

At the same time, investors and end-users are beginning to use “sustainable computing” as a benchmark for assessing corporate responsibility and risk management. Tech giants like Google, Microsoft, and Amazon have pledged to power their data centers entirely with renewable energy in the coming years, aiming for carbon-neutral computing as their ultimate goal.

協力共創永續能源基礎設施

Kalogiros認為，未來企業之間將不只是競爭對手，更可能成為共同推動基礎設施升級的合作夥伴。「如果這些科技巨頭能攜手與政府及電力公司對話，承諾以長期固定價格大量購電，那麼他們就能促進整體電網升級、擴大可再生能源投資，進一步保障經濟未來對AI與運算力的需求。」

Collaborating to Build Sustainable Energy Infrastructure

Kalogiros believes that companies will increasingly become partners - not just competitors - in advancing sustainable infrastructure. “If these tech giants can unite to engage with governments and utilities, and commit to large-scale long-term power purchase agreements, they could accelerate grid modernization and unlock broader renewable energy investment - ultimately securing the economic future of AI and compute demands.”

結語

Conclusion

AI資料中心的崛起是數位經濟發展的必然趨勢，但其龐大的能源消耗也成為碳中和目標下不可忽視的挑戰。唯有透過技術創新、供應鏈轉型與政策對接，資料中心才能成為低碳經濟的重要支柱，而非環境負擔。

The rise of AI data centers is an inevitable trend in the digital economy, but their massive energy consumption poses a serious challenge to global carbon neutrality goals. Only through technological innovation, supply chain transformation, and alignment with evolving policies can data centers evolve into key pillars of a low-carbon economy - rather than environmental liabilities.