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商品編碼

2148217

人工智慧資料中心散熱系統市場規模、市場佔有率及成長預測（2026-2032 年）

AI Data Center Heat Rejection Systems Market Size, Share & Growth Forecast (2026-2032)

出版日期: 2026年09月25日 | 出版商:

Knowledge Sourcing Intelligence | 英文 153 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

2026年人工智慧資料中心散熱系統市場規模估計為46億美元，預計2032年將達到131.7億美元。這意味著在預測期內，複合年成長率將達到19.2%。

直接晶片冷卻 (DTC) 能有效地將圖形處理器 (GPU) 和中央處理器 (CPU) 產生的熱量傳遞到技術冷卻迴路，但這些熱量仍需散發到機房外部。冷卻劑分配單元將這些熱負荷輸送到機房迴路，最終透過冷卻器、乾式冷卻器、冷卻塔或混合系統散發出去。隨著人工智慧運算密度的增加，這個最終階段的重要性也隨之提升，因為即使降低機房層面的氣流，單位建築面積的熱量也會增加。因此，機房冷卻正從眾多機房冷卻單元轉向更少但容量更大的中央溫度控管系統。人工智慧也改變了溫度分佈。傳統的冷凍水系統通常以較低的水溫運作，以適應風冷式伺服器。而液冷人工智慧硬體則能承受更高的冷卻劑溫度，這使得營運商可以提高機房內的水溫，並在一年中更長時間地使用乾式冷卻器和節熱器。江森自控的2026年人工智慧工廠參考設計明確採用了高溫冷卻技術，以減少用水量和散熱。特靈和施耐德電機也積極探索以高溫迴路、乾式冷卻器和絕熱流體冷卻器為核心的設計方案。從經濟角度來看，重點在於改變設備配置，而不僅僅是增加冷卻器機組的冷氣量。氣候條件仍然是關鍵因素。乾式冷卻器無需製程用水即可散熱，也無需在冷卻塔中進行水處理，但其進風溫度會根據環境條件而升高。莫迪恩指出，由於熱浪、局部空氣循環和機架溫度要求等因素的複雜相互作用，在許多地區，僅使用乾式冷卻器系統並不實用。因此，混合架構將有利條件下的自然冷卻與最高環境溫度下的機械冷卻相結合。當冷凝器溫度低、面積小或效率極高時，水冷式冷卻器和冷卻塔仍然是一個有吸引力的選擇。

市場促進因素

人工智慧處理能力的擴張正在增加園區範圍內的熱負荷。人工智慧基礎設施正在大規模地增加高密度運算能力，而其電力輸入最終會轉化為熱量。國際能源總署（IEA）預測，到2030年，人工智慧專用資料中心的電力消耗量將大幅成長。目前，人工智慧園區的規劃規模已從100兆瓦到吉瓦不等。因此，即使液冷技術可以降低閒置頻段的空氣需求，散熱設備的規模仍將與裝置容量成正比成長。此外，大型專案需要N+1冗餘等措施，導致散熱容量的安裝量超過穩態熱負荷。
流體溫度越高，系統越有可能在不使用壓縮機的情況下運作。冷卻迴路溫度的升高增強了乾式冷卻器、液體冷卻器和水側節熱器的動態優勢。 Munters指出，更高的流體溫度可以顯著延長熱量直接散發到周圍空氣中的時間。江森自控、特靈和施耐德電機正在將這一原理融入他們當前的AI工廠參考設計中。因此，在適宜的氣候條件下，對乾式和混合式散熱系統的需求將會增加，同時壓縮機的年度運作可以減少。
水資源限制正在加速乾式和混合式系統的應用。大規模蒸發冷卻系統可能需要大量的補充水和水處理基礎設施。因此，水資源可用性、授權和社區監管正在影響場地設計。江森自控2026年發布的空氣冷卻人工智慧工廠參考設計方案採用了無水廢熱利用，並取消了冷卻塔。施耐德電機最新的高密度參考設計方案採用隔熱乾式冷卻器，以平衡用水量和尖峰時段溫度性能。開發商在位置階段擴大將廢熱和水資源策略作為整體方案進行評估。
模組化參考設計正在推動設備標準化。熱力系統正向可重複使用的兆瓦級模組化組件轉型。施耐德電氣、特靈、江森自控和維迪沃等公司正在發布或部署檢驗的AI冷卻架構，這些架構將冷水冷卻器、乾式冷卻器、冷卻劑分配單元和控制系統整合在一個標準化的計算模組周圍。這縮短了專案設計時間，並有助於部署工廠預製的撬裝設備、模組化管道和預先整合控制系統。擁有可擴展平台和全球製造能力的供應商具有優勢，因為相同的AI參考架構可以在多個地區重複應用。

市場限制因素

主要限制因素是液冷溫度升高會降低每兆瓦的設備密度。較高的迴路溫度會導致更長的自然冷卻時間，這可以透過減少給定IT負載所需的冷卻器或乾式冷卻器的數量來部分抵消容量的增加。此外，散熱設計高度依賴氣候，這限制了全球標準化。在炎熱氣候下，乾式冷卻器可能需要更大或效率更低。冷卻塔的引進會帶來用水量和水處理的要求。機房可能面臨空間、噪音和循環方面的限制，尤其是在高密度都市區。營運商還必須在維護期間和極端天氣條件下保持冗餘，因此基於年平均氣溫的簡單最佳化無法實現。

促進因素
- 人工智慧導致的熱負荷增加
- 高溫液體冷卻迴路
- 水資源受限條件下資料中心的發展
- 模組化人工智慧工廠參考設計
抑制因子
- 每兆瓦散熱設備密度降低
- 基於氣候的設計要求
- 機械設備場地、噪音和再循環等方面的限制。
- 水、冷媒和監管方面的權衡

第11章競爭格局

價值鏈
冷卻器製造商
乾式冷卻器和液體冷卻器供應商
冷卻塔和混合散熱系統供應商
熱交換器和節熱器供應商
整合式人工智慧溫度控管基礎設施供應商

第12章：公司簡介

Johnson Controls
Trane Technologies
Carrier
Daikin Applied
Schneider Electric / Motivair
Vertiv
Modine / Airedale
Munters
STULZ
EVAPCO
Baltimore Aircoil Company
Guntner
Alfa Laval
Kelvion
Delta Electronics
Rittal
Mitsubishi Electric

第13章近期趨勢

第14章附錄

簡介目錄

Product Code: KSI-009297

The AI Data Center Heat Rejection Systems Market is estimated at USD 4.60 billion in 2026 and is projected to reach USD 13.17 billion by 2032, representing a CAGR of 19.2% during the forecast period.

Direct-to-chip liquid cooling moves heat efficiently from graphics processing units and central processing units into a technology cooling loop, but the heat still has to leave the facility. A coolant distribution unit transfers that load into a facility loop that ultimately rejects it through a chiller, dry cooler, cooling tower or hybrid system. This final step becomes more important as AI compute density rises because the quantity of heat per building increases even if room-level airflow declines. Facility cooling therefore shifts from large numbers of computer room units toward fewer, higher-capacity central thermal systems. AI also changes the temperature profile. Traditional chilled-water systems often operated around lower water temperatures to support air-cooled servers. Liquid-cooled AI hardware can tolerate much warmer coolant, allowing operators to raise facility-water temperatures and use dry coolers or economizers for more hours each year. Johnson Controls' 2026 AI-factory reference designs explicitly use high-temperature technology cooling loops to reduce water use and heat-rejection equipment. Trane and Schneider Electric are similarly designing around higher-temperature loops, dry coolers and adiabatic fluid coolers. The economic result is a shift in equipment mix rather than a simple increase in chiller capacity. Climate remains decisive. Dry coolers can reject heat without process water and eliminate cooling-tower water treatment, but their approach temperature rises with ambient conditions. Modine notes that heat waves, local air recirculation and mixed rack-temperature requirements can make dry-cooler-only systems impractical in many regions. Hybrid architectures therefore combine free cooling during favorable conditions with mechanical refrigeration for peak ambient temperatures. Water-cooled chillers and cooling towers remain attractive where lower condenser temperatures, compact footprint or very high efficiency justify water consumption.

Market Drivers

AI capacity growth increases thermal load at campus scale. AI infrastructure is adding large blocks of high-density compute capacity whose electrical input ultimately becomes heat. The International Energy Agency expects electricity consumption from AI-focused data centers to rise sharply through 2030. Current AI campuses are increasingly planned in 100 MW to gigawatt increments. Heat-rejection equipment therefore scales with deployed megawatts even when liquid cooling reduces white-space air requirements. Large projects also require N+1 or other redundancy, increasing installed heat-rejection capacity above the steady-state thermal load.
Warmer liquid loops expand compressor-free operation. Higher technology-cooling-loop temperatures improve the thermodynamic position of dry coolers, fluid coolers and waterside economizers. Munters notes that elevated liquid temperatures can substantially increase the number of hours in which heat is rejected directly to ambient air. Johnson Controls, Trane and Schneider Electric have incorporated this principle into current AI-factory reference designs. The resulting demand benefits dry and hybrid heat-rejection equipment while reducing annual compressor runtime in suitable climates.
Water constraints are accelerating dry and hybrid systems. Large evaporative cooling systems can require substantial make-up water and water-treatment infrastructure. Water availability, permitting and community scrutiny are therefore influencing site design. Johnson Controls' 2026 air-cooled AI-factory reference design describes zero-water heat rejection and elimination of cooling towers. Schneider Electric's latest high-density reference designs use adiabatic dry coolers to balance water use against peak-temperature performance. Operators increasingly evaluate heat rejection and water strategy together at the site-selection stage.
Modular reference designs are increasing equipment standardization. Thermal systems are moving toward repeatable multi-megawatt building blocks. Schneider Electric, Trane, Johnson Controls and Vertiv are all publishing or deploying validated AI cooling architectures that align chillers, dry coolers, coolant distribution units and controls around standardized compute blocks. This reduces project engineering time and supports factory-built skids, modular piping and pre-integrated controls. Suppliers with scalable platforms and global manufacturing are advantaged as the same AI reference architectures are repeated across multiple regions.

Market Restraints

The main restraint is that rising liquid-cooling temperatures can reduce equipment intensity per megawatt. Warmer loops improve free-cooling hours and can reduce the number of chillers or dry coolers required for a given IT load, partially offsetting capacity growth. Heat-rejection design is also highly climate-specific, which limits global standardization. Dry coolers become larger or less effective in hot climates. Cooling towers introduce water use and treatment requirements. Mechanical yards can face space, noise and recirculation constraints, particularly in dense urban locations. Operators must also preserve redundancy during maintenance and extreme-weather conditions, preventing simple optimization around average annual temperature.

Technology and Segment Insights

Chiller-based systems represent the largest 2026 revenue pool because water-cooled and air-cooled chillers remain central to hyperscale and high-density data centers across a wide range of climates. The category includes centrifugal, screw and magnetic-bearing platforms with increasingly wide operating ranges and free-cooling integration. Water-cooled chiller plants often pair with cooling towers. Air-cooled units combine refrigeration and ambient heat rejection in one package.
Dry coolers and adiabatic fluid coolers are expected to grow fastest through 2032. Elevated liquid temperatures increase the number of climates and operating hours where compressor-free or low-compressor operation is feasible. Hybrid systems combine dry cooling with adiabatic assist or mechanical refrigeration for peak conditions. This makes them particularly attractive for global operators that want lower water consumption without sacrificing thermal headroom. Cooling towers remain important for high-efficiency water-cooled plants, especially in hot climates and sites where water is readily available.
Air-cooled chillers form a large revenue pool with strong growth. Their primary AI data center application is water-free refrigeration and peak-load heat rejection. Water-cooled chillers and cooling towers form the largest established architecture with strong growth. Their primary application is high efficiency and compact large-campus thermal plants. Dry and fluid coolers are fast-growing with the fastest growth. Their primary application is ambient heat rejection for warm liquid loops. Adiabatic and hybrid coolers are growing with very strong growth. Their primary application is lower water use with improved hot-weather performance. Waterside economizers and heat exchangers form an established support layer with above-average growth. Their primary application is increasing compressor-free cooling hours. Controls, integration and lifecycle services form a recurring service layer with strong growth. Their primary application is plant optimization, redundancy and performance management.
The market is segmented by heat-rejection architecture, cooling interface, project type, water strategy, customer type and geography. Heat-rejection architectures include air-cooled chillers, water-cooled chillers and cooling towers, dry and fluid coolers, adiabatic and hybrid coolers, waterside economizers and heat exchangers, and controls, integration and lifecycle services. Cooling interfaces include direct-to-chip liquid-cooled AI infrastructure, hybrid air-liquid data halls, conventional chilled-water AI environments, and two-phase and high-temperature emerging systems. Project types include greenfield AI factories, hyperscale and colocation expansions, brownfield AI retrofits, and sovereign and enterprise AI facilities. Water strategies include zero-water and dry heat rejection, low-water and adiabatic systems, evaporative and cooling-tower systems, and hybrid climate-optimized systems. Customer types include hyperscale cloud providers, neocloud and GPU-cloud operators, colocation providers, sovereign AI infrastructure, and enterprise and high-performance computing.
Chiller-based heat rejection remains the largest 2026 revenue pool across global AI campuses. Dry coolers and adiabatic fluid coolers are the fastest-growing heat-rejection architecture. Zero-water cooling is becoming a core design option for large greenfield AI factories. AI reference designs are scaling heat-rejection blocks from multi-megawatt to gigawatt campuses. North America leads spending through hyperscale, neocloud and large colocation development. Equipment density and modularity are becoming critical where sites have limited mechanical-yard space.

Competitive and Strategic Outlook

The market is led by large thermal-equipment suppliers with the manufacturing scale to support multi-megawatt and campus-level projects. Johnson Controls, Trane, Carrier and Daikin Applied compete across centrifugal, screw, magnetic-bearing and air-cooled chiller platforms. Schneider Electric and Vertiv integrate heat rejection with coolant distribution, facility power and AI reference architectures. Modine and Airedale, Munters and STULZ compete strongly in data-center-specific cooling, including free-cooling and dry-cooler solutions.
Heat-rejection specialists remain important where projects require dry coolers, closed-circuit coolers, cooling towers or hybrid systems at scale. EVAPCO, Baltimore Aircoil Company and Guntner offer broad air-side and evaporative heat-rejection portfolios. Alfa Laval and Kelvion participate through plate heat exchangers and fluid-cooling systems. Delta Electronics and Rittal add integrated data-center thermal infrastructure. Competitive advantage increasingly depends on capacity density, ambient operating range, free-cooling capability, water consumption, modularity, refrigerant profile, controls and the ability to guarantee performance under rapidly changing AI thermal loads.
North America is the largest market for AI data-center heat-rejection systems. The United States combines the world's largest hyperscale and neocloud investment base with rapid adoption of liquid-cooled accelerator infrastructure. Large campuses increasingly require central heat-rejection plants in the tens or hundreds of megawatts. This creates demand for multi-megawatt chillers, dry coolers, towers, pumps, heat exchangers and controls. Northern Virginia, Texas, the Midwest and western U.S. markets present very different climate and water conditions. This makes the region a major deployment environment for both evaporative and water-free architectures.
The supplier ecosystem is also concentrated in the region. Johnson Controls, Trane, Carrier and Daikin Applied provide large chiller platforms and AI-specific reference architectures. Modine's Airedale business is expanding high-capacity air-cooled and free-cooling chillers. EVAPCO and Baltimore Aircoil Company participate in dry, evaporative and hybrid heat-rejection equipment. Vertiv and Schneider Electric integrate facility heat rejection with liquid-cooling and power systems. This is increasingly important as hyperscalers procure validated end-to-end AI infrastructure rather than isolated mechanical components.
North American growth is also influenced by water and grid constraints. Dry cooling and air-cooled chillers reduce on-site water consumption but can increase fan or compressor power during high ambient conditions. Water-cooled systems can deliver high efficiency but require make-up water, treatment and permitting. Through 2032, operators are expected to use a broader mix of hybrid designs. These include dry coolers for most annual hours with chillers or adiabatic assist for peak conditions. Brownfield sites will add modular heat-rejection capacity where existing plants cannot support new liquid-cooled AI clusters.
Europe benefits from cooler climates in many major data-center hubs and strong incentives around water and energy efficiency. This supports dry cooling, economization and heat-reuse-compatible architectures. Asia Pacific combines very large AI infrastructure growth with wide climate variation. This creates demand for both high-efficiency water-cooled plants and air-cooled or hybrid systems. The Middle East is emerging as a major greenfield AI market where extreme ambient temperatures favor robust mechanical cooling and carefully engineered hybrid rejection systems.
Recent developments confirm accelerating market activity. In September 2026, Munters outlined next-generation two-phase AI cooling architectures that can enable warmer return temperatures and substantially more compressor-free heat rejection. In July 2026, Johnson Controls released an absorption-chiller AI-factory reference design aimed at reducing cooling electrical demand by using waste heat from on-site power generation. In July 2026, Schneider Electric released an AMD MI455X AI data-center reference design using liquid-to-liquid coolant distribution units and adiabatic dry coolers. In May 2026, Johnson Controls introduced an air-cooled AI-factory reference design targeting zero on-site cooling water and lower annual cooling energy. In May 2026, Trane expanded AI-factory reference designs combining chillers, dry coolers and waterside economizing across 250 MW and 1 GW deployments. In February 2026, Carrier introduced the AquaEdge 30CF air-cooled centrifugal chiller for data-center reliability and high-density thermal loads. In February 2026, Vertiv announced a dry-cooler-based heat-rejection architecture for NxtGen AI's Blackwell infrastructure deployment in India. In January 2026, Modine and Airedale launched TurboChill 3+MW, combining air-cooled heat rejection and expanded free-cooling operation for AI data centers.

Conclusion

The AI data center heat rejection systems market is growing rapidly as AI compute density and campus scale increase. Growth is driven by AI thermal load, warmer liquid cooling loops, water-constrained development and modular AI factory reference designs. Chiller-based systems form the largest revenue pool. Dry coolers and adiabatic fluid coolers are the fastest-growing architecture. Zero-water cooling is becoming a core design option for greenfield AI factories. North America leads spending. Europe, Asia Pacific and the Middle East offer region-specific opportunities. Falling heat-rejection equipment intensity per megawatt, climate-specific design requirements and mechanical yard constraints remain the key restraints. The market is projected to grow from USD 4.60 billion in 2026 to USD 13.17 billion by 2032 at a CAGR of 19.2%.

Key Benefits of this Report

Insightful Analysis: Detailed market insights across regions, customer segments, policies, socio-economic factors, consumer preferences, and industry verticals.
Competitive Landscape: Understand strategic moves by key players to identify optimal market entry approaches.
Market Drivers and Future Trends: Assess major growth forces and emerging developments shaping the market.
Actionable Recommendations: Support strategic decisions to unlock new revenue streams.
Caters to a Wide Audience: Suitable for startups, research institutions, consultants, SMEs, and large enterprises.

What Businesses Use Our Reports For

Industry and market insights, opportunity assessment, product demand forecasting, market entry strategy, geographical expansion, capital investment decisions, regulatory analysis, new product development, and competitive intelligence.

Report Coverage

Historical data from 2021 to 2024, Base year 2025, and Forecast years from 2026 to 2032
Growth opportunities, challenges, supply chain outlook, regulatory framework, and trend analysis
Competitive positioning, strategies, and market share evaluation, and trade analysis
Revenue growth and forecast assessment across segments and regions
Company profiling including strategies, products, financials, and key developments

1. Executive Summary

1.1. Market Opportunity and Key Findings
1.2. Heat-Rejection Architecture Transition
1.3. Principal Revenue Pools

2. Market Overview

2.1. From Chip Heat Capture to Facility Heat Rejection
2.2. Elevated Temperature Liquid Cooling
2.3. Climate and Water Constraints
2.4. Mechanical Refrigeration and Free Cooling
2.5. Hybrid and Modular Thermal Plants

3. Market Size and Forecast, 2026-2032

3.1. Global Market Revenue
3.2. Annual Growth Analysis
3.3. Greenfield versus Retrofit Demand
3.4. Heat-Rejection Content per MW

4. Market by Heat-Rejection Architecture

4.1. Air-Cooled Chillers
4.2. Water-Cooled Chillers and Cooling Towers
4.3. Dry and Fluid Coolers
4.4. Adiabatic and Hybrid Coolers
4.5. Waterside Economizers and Heat Exchangers
4.6. Controls, Integration and Lifecycle Services

5. Market by Cooling Interface

5.1. Direct-to-Chip Liquid-Cooled AI Infrastructure
5.2. Hybrid Air-Liquid Data Halls
5.3. Conventional Chilled-Water AI Environments
5.4. Two-Phase and High-Temperature Emerging Systems

6. Market by Project Type

6.1. Greenfield AI Factories
6.2. Hyperscale and Colocation Expansions
6.3. Brownfield AI Retrofits
6.4. Sovereign and Enterprise AI Facilities

7. Market by Water Strategy

7.1. Zero-Water / Dry Heat Rejection
7.2. Low-Water / Adiabatic Systems
7.3. Evaporative / Cooling-Tower Systems
7.4. Hybrid Climate-Optimized Systems

8. Market by Customer Type

8.1. Hyperscale Cloud Providers
8.2. Neocloud and GPU-Cloud Operators
8.3. Colocation Providers
8.4. Sovereign AI Infrastructure
8.5. Enterprise and High-Performance Computing

9. Regional Market

9.1. North America
- 9.1.1. United States
- 9.1.2. Canada
9.2. Europe
9.3. Asia Pacific
9.4. Middle East and Rest of World

10. Market Dynamics

10.1. Drivers
- 10.1.1. Growth in AI Thermal Load
- 10.1.2. Warmer Liquid Cooling Loops
- 10.1.3. Water-Constrained Data Center Development
- 10.1.4. Modular AI Factory Reference Designs
10.2. Restraints
- 10.2.1. Falling Heat-Rejection Equipment Intensity per MW
- 10.2.2. Climate-Specific Design Requirements
- 10.2.3. Mechanical Yard, Noise and Recirculation Constraints
- 10.2.4. Water, Refrigerant and Regulatory Tradeoffs