{"id":1796,"date":"2026-06-10T15:51:06","date_gmt":"2026-06-10T15:51:06","guid":{"rendered":"https:\/\/trustedainews.com\/?p=1796"},"modified":"2026-06-10T15:51:06","modified_gmt":"2026-06-10T15:51:06","slug":"industry-groups-launch-ai-data-center-framework-amid-rising-power-needs","status":"publish","type":"post","link":"https:\/\/trustedainews.com\/?p=1796","title":{"rendered":"Industry Groups Launch AI Data Center Framework Amid Rising Power Needs"},"content":{"rendered":"<p>Industry Orgs Launch AI Data Center Framework for Rising Demands. 3 Min Read. A new framework from NEMA, ASHRAE, and PNNL unifies standards to address energy, cooling, and design challenges in power-intensive AI data centers.Getty Images. The rapid expansion of AI infrastructure is creating new challenges in power delivery, cooling, efficiency, and facility design, leading a consortium of industry organizations to develop standardized approaches to data center development.. The National Electrical Manufacturers Association (NEMA), American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), and Pacific Northwest National Laboratory (PNNL) this week released the AI Data Center Energy Performance Framework, a guide that brings together technical standards and operational best practices covering electrical systems, cooling infrastructure, energy management and facility operations.. The organizations said the framework is intended to provide a common reference for project developers, engineers, and facility managers responsible for supporting increasingly power-intensive AI workloads.. Standardizing AI Data Center Development. The AI Data Center Energy Performance Framework addresses energy sourcing, energy efficiency, thermal management, water use, resiliency, and operational performance across the data center lifecycle.. Related:Why AI Infrastructure Is Moving Toward 800 VDC Power. Areas covered include site selection and planning, integrated facility design, grid-interactive infrastructure, commissioning and performance validation, operations and maintenance, and retrofit and modernization projects.. NEMA senior vice president of strategy, technical, and industry affairs, Patrick Hughes, told Data Center Knowledge that one of the more consequential design shifts is from AC to DC power distribution.. \u201cToday\u2019s data centers are built around AC utility power,\u201d he said.. However, Hughes explained that the chain of conversions between the grid interconnection point, the step-down transformer, conversion to DC inside a UPS, conversion back to AC, and then conversion again to low-voltage DC when reaching the server rack requires significant effort to avoid energy loss.. \u201cThe efficiency case for high-voltage DC is strong,\u201d Hughes said.. The challenge is that the standards aren\u2019t yet in place for higher voltages, such as 800 VDC and up.. \u201cMuch of the industry is pursuing adapted solutions while waiting for clearer standards, safety frameworks, and customer demand signals,\u201d he said. \u201cThe framework helps to address that at a systems level.\u201d. Building the DC supply chain will hinge on stabilizing standards so suppliers can design, certify, manufacture, and install equipment with confidence.. ASHRAE, NEMA, and PNNL are leveraging their combined expertise to develop a cutting-edge AI data center framework, addressing critical challenges such as energy efficiency, scalability, and sustainability to support the industry\u2019s evolving needs.. Pressure to Accelerate Project Timelines. The publication of the new AI power performance framework comes as hyperscalers, colocation providers, and developers face growing pressure to accelerate project timelines while securing sufficient power capacity for AI infrastructure.. Related:EU: AI to Transform Data Center Operations \u2013 But Not Overnight. Industry attention has increasingly shifted toward \u201cspeed to power\u201d strategies, including alternative generation sources, microgrids, energy storage systems and other approaches designed to shorten the timeline between project approval and facility energization.. Hughes explained the framework is designed to connect existing standards, guidance documents, and deployment practices into a single operational resource intended to reduce uncertainty during planning, construction and ongoing operations.. \u201cToo many data center developers are working from proprietary internal standards,\u201d he said. \u201cBut it takes time for a data center developer to start from scratch on every project.\u201d. The document incorporates more than a dozen NEMA standards and guidance resources spanning energy storage systems, microgrids, transformers, switchgear, uninterruptible power supply systems, wire and cable, electricity metering, fire and life-safety equipment, insulating materials, and grounding and bonding systems.. Bridging Gaps in AI Data Center Standards. Hughes noted that data centers are using and managing energy in ways fundamentally different from what the codes and standards governing this type of infrastructure were designed to address.. Related:Riding the Wave: The Rise of Floating Data Centers. \u201cThe guidance connecting electrical and thermal management equipment to each other, and to the specific demands of AI data centers, has been fragmented across multiple organizations and multiple standards bodies,\u201d he said.. The framework is designed to address that fragmentation by bringing the thermal management expertise from ASHRAE, energy management, and grid integration expertise from PNNL, and the electrical equipment manufacturers\u2019 perspective from NEMA.. \u201cThe framework covers what an AI data center developer needs to make sound design considerations from planning and siting through commissioning, operations, and retrofit,\u201d Hughes said.. The framework can be accessed via ASHRAE\u2019s technical resources webpage.. Read more about:. About the Author<\/p>\n<p>\u00a0<\/p>","protected":false},"excerpt":{"rendered":"<p>Industry Orgs Launch AI Data Center Framework for Rising Demands. 3 Min Read. A new framework from NEMA, ASHRAE, and&hellip;<\/p>\n","protected":false},"author":2,"featured_media":1623,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-1796","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-center"],"_links":{"self":[{"href":"https:\/\/trustedainews.com\/index.php?rest_route=\/wp\/v2\/posts\/1796","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/trustedainews.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/trustedainews.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/trustedainews.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/trustedainews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1796"}],"version-history":[{"count":0,"href":"https:\/\/trustedainews.com\/index.php?rest_route=\/wp\/v2\/posts\/1796\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/trustedainews.com\/index.php?rest_route=\/wp\/v2\/media\/1623"}],"wp:attachment":[{"href":"https:\/\/trustedainews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1796"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/trustedainews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1796"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/trustedainews.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1796"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}