内容来源：https://www.technologyreview.com/2026/06/16/1138591/data-center-online-quickly-electric-grid-flex/

内容总结：

数据中心“柔性用电”破局：AI调控避免电网崩溃，英国家庭烧水煮茶引发的一场电力实验

随着人工智能热潮推动数据中心爆发式增长，全球电网正面临前所未有的压力。然而，解决之道或许并非只有增建发电厂——一种通过软件动态调节数据中心能耗的“柔性用电”技术正在兴起。

2025年12月，一场模拟实验在英国上演：重现2020年欧洲杯英格兰对阵德国的足球赛中场休息时刻。当时数百万英国球迷同时按下电热水壶开关，导致用电需求瞬间飙升。但这一次，一套名为“Conductor”的人工智能系统提前收到指令，立即调低了伦敦某数据中心内高耗能芯片的功率，成功平衡了供需，避免了潜在的停电风险。这套系统由华盛顿初创公司Emerald AI开发，标志着数据中心从“电老虎”向“电网好帮手”的转变。

今年，Conductor将首次在弗吉尼亚州“数据中心巷”的实时电网中部署。该项目由英伟达、数据中心运营商Digital Realty等巨头合作，被称为全球首批“功率柔性AI工厂”之一。当整体用电高峰来临时，系统会降低数据中心功耗，同时确保其最紧急、最重要的工作任务不受影响。

现实痛点：审批漫长与民众抗议

数据中心建设面临的最大瓶颈并非技术，而是电力审批。在美国，新建发电厂的审批、建设和并网周期长达八年，远超数据中心建设速度。例如，弗吉尼亚州所在的PJM电网运营商需要八年才能让新电源上线。英伟达可持续发展主管乔什·帕克直言：“AI工厂的灵活性是连接AI巨大需求与电力系统现实限制之间的桥梁。”

此外，民众对数据中心引发的电价上涨、噪音污染和就业威胁日益不满。2025年，全美因抗议而停滞的项目总价值超过1500亿美元。超过12个州正在考虑禁令，明尼阿波利斯、佐治亚州迪卡尔布县等地已实施暂停令。美国参议院的两党法案《GRID法案》甚至提议让新数据中心完全脱离公共电网。

现有电网潜力巨大：仅需0.25%时间减负

与其急于新建电厂，不如挖掘既有电网的潜力。电网专家指出，现有输电系统全年只有少数高需求时段接近满负荷运行。杜克大学2025年的一份报告显示，只要数据中心愿意在每年约22小时（占全年0.25%）的时间减少用电，美国电网即可释放额外76吉瓦容量——相当于全美现有容量5%，足以支撑到2030年的预期增长。普林斯顿大学的研究则表明，一个每年灵活用电不到1%的500兆瓦数据中心，可比不灵活设施提前3至5年全面投产。

多种路径：从电池储能到虚拟电厂

实现柔性用电主要有三种方式：一是数据中心自建现场备用储能或发电设备，在电网紧张时使用；二是参与虚拟电厂（VPP）项目，由电网通过智能设备调减签约用户的用电量，数据中心为此付费；三是在高峰期直接降低自身能耗。

Emerald AI的Conductor系统走的是最激进的第三条路：它通过分析AI工作负载特性，精准判断哪些程序可以降速而不影响关键性能。例如，实时聊天机器人查询的优先级高于深度研究中的网页搜索。经过多次测试，Conductor已在凤凰城成功让256块英伟达A100 GPU的功率降低25%并保持三小时，且在伦敦模拟中成功应对了“电热水壶效应”等突发波动。

未来展望：灵活性是桥梁，非万能药

尽管柔性用电前景广阔，但质疑声亦存。PJM电网市场监测负责人约瑟夫·鲍林直言：“认为不增加发电就能容纳大量数据中心，这是魔法思维。”他认为，缺乏法律约束下，无法保证数据中心在高峰时真正减负。

然而，支持者强调，柔性用电是优化工具而非替代方案。国际可再生能源署2026年报告预测，到2030年全球电网对灵活性的需求将是2019年的三倍，到2050年则需十倍。Emerald AI首席科学家科斯昆表示：“危机有时创造了改变的机遇。”从化石燃料向太阳能、风能、电池和电动汽车并存的未来转型中，一定程度的柔性用电将发挥关键作用。

中文翻译：

想快速让数据中心上线？给它一点灵活性。
随着数据中心的建设热潮给电网带来压力，一些公司表示，解决办法不仅仅在于建造更多发电厂，还需要在需求激增时，用软件来降低数据中心的能耗。
在一场英格兰男足与老对手德国队之间紧张且互交白卷的上半场比赛结束时，数百万英国人集体叹了口气，然后做了他们压力山大时经常做的事：煮茶。然而，这种电水壶纷纷开启的浪潮却引发了另一种压力：电力需求的巨幅激增。但运营当地输电网的国家电网公司早有准备。
就在那些水壶开始加热时，一个AI程序向伦敦的一个数据中心发送指令，减缓了该设施中一些高功耗芯片的运行速度。这种减负有助于确保供应满足需求，避免潜在的停电或电气设备损坏。对于通常只自顾自地消耗电力、不顾及其他任何需求的数数据中心而言，这是一个根本性的转变。
这同时也是一场模拟。2025年12月，工程师们试图测试一种在电力需求上具有灵活性的新型数据中心，于是他们重现了2020年欧洲杯一场比赛期间英国电网所面临的能源需求。他们想看看，名为Conductor的软件如果当时在线，会如何应对。
Conductor是总部位于华盛顿特区的Emerald AI公司的旗舰产品。该公司是一波试图探索数据中心能否在现有电网框架内运行的浪潮中的一员。
今年，Emerald计划在弗吉尼亚州被称为“数据中心走廊”的地区的一个新设施中部署Conductor，这次将连接到实时电网。当整体需求激增时，Conductor将降低数据中心的用电量，同时确保其服务器仍能完成最紧急、最重要的任务。Emerald在该项目上的合作伙伴——包括英伟达和大型数据中心运营商Digital Realty——将其称为世界上首批“功率灵活的人工智能工厂”之一。
证明数据中心可以参与这种有取有予的合作，或许能缓解许多科技领袖所认为的数据中心上线瓶颈：获得审批、建造并连接新发电厂所需的时间，远比建造数据中心要长得多。例如，弗吉尼亚州及美国最大的电网运营商PJM，根据能源研究与倡导组织RMI的数据，需要八年时间才能让新的发电设施并网。“我们需要解决能源方程问题，”英伟达可持续发展主管乔什·帕克说，“人工智能工厂的灵活性，是连接对AI的惊人需求与当前能源电网局限性之间的桥梁。”
然而，速度只是问题之一。一旦设施接入电网，邻居们常常批评它们消耗过多电力，导致电价上涨。他们认为数据中心产生的噪音多过长期就业机会，造成污染，并有可能导致人们失业。根据Data Center Watch的数据，2025年，组织者搁置了价值超过1500亿美元的项目。而对公众情绪保持警惕的政策制定者已开始对开发施加限制。
超过十二个州正在考虑禁令，而诸如明尼阿波利斯和佐治亚州迪卡尔布县等地已实施地方暂停令。在联邦层面，美国参议院的一项两党法案《GRID法案》提议将新建数据中心完全从公共电网中剥离。一些运营商已朝着这个方向迈进，试图开发自己的发电能力。
与其急于建造新的发电厂，公司或许能找到解决这一困局的答案，它就在我们眼皮底下——或者更确切地说，在我们脚下和头顶的输电线中。现有系统在全年中，仅在少数高需求时段才会接近满负荷运行。这意味着，一些电网专家认为，如果数据中心能在这些时段限制其用电量，就无需等待大型基础设施升级或建造自己的离网发电设施。
事实上，越来越多的研究表明，只要有灵活性，数据中心就有充足的电力可用。杜克大学研究人员2025年一份被广泛讨论的报告发现，对于那些愿意在仅0.25%的时间里减少用电量的设施，美国电网可以提供额外的76吉瓦电力——约占其总容量的5%，且大约足以满足美国数据中心到2030年的预期增长需求。这大约相当于每年22小时。当普林斯顿大学的研究人员与两家电网现代化公司考察PJM地区新建数据中心的地点时，他们受谷歌资助的报告发现，一个能够灵活运行、灵活性时间占比不到全年1%的500兆瓦设施，比一个缺乏灵活性的设施可以快三到五年实现全面运营。
灵活的电力连接还可以帮助数据中心解决一些公关问题。例如，通过在电网紧张时减少用电，它们可以避免从最需要电力的地方分流，从而提升稳定性。通过利用现有容量，它们可能能够减少建造新的化石燃料发电厂的需求，并将固定成本分摊给更多电力用户，从而拉低价格。
人工智能带来的电力压力，正吸引资源和研究投入到电网整体灵活性的策略上，这可能有助于度过一个棘手时期：结合电动汽车、空调和其他行业，分析师预测，到2030年，美国的电力需求将比2023年水平增长25%，而数据中心是推动因素之一。
理想情况下，灵活性让电网运营商能更好地控制电子流动，使他们成为和谐整体的领导者，而非受制于僵化的电力需求。这将帮助他们管理整个系统的需求峰值，并更有效地应对风能和太阳能等可再生能源的间歇性特点。“需求灵活性对电网非常有用，”密歇根大学的电网专家约翰娜·马蒂厄说，“它有助于降低电力成本并提高电网可靠性。”
但尽管倡导者看到了诸多好处，这一概念也带来了复杂性。对数据中心而言，在能源需求上妥协可能难以推销。灵活性要求公用事业公司和电网运营商——这些机构通常运营保守——改变长期以来的做法。一些怀疑论者也表示，灵活性会分散人们对更迫切需要的加快电网基础设施建设的注意力，甚至可能对我们的电力供应构成风险。
尽管如此，一些技术专家、电网运营商和公用事业公司仍希望证明灵活性是有效的——不仅仅是在白皮书或模拟中，而是在现实生活中。
数据中心增长的代表性案例往往走向僵化。像微软和Oracle这样的超大规模企业提出了庞大的新中心计划，其中许多将依赖离网的天然气燃烧发电厂。当xAI想要加快田纳西州孟菲斯市郊外的Colossus站点建设时，他们用平板卡车运来了燃气轮机。目前正在运营的该设施，正因导致的排放和其他污染激增而面临监管机构和居民的反对。无论如何，全球的燃气轮机数量都不足以满足数据中心运营商的需求。
任何需要大量电力的人面临的一个主要障碍是，我们的电网大多很僵化。它们的设计初衷是在需求最高时供应足够的电力以满足总需求，即使这每年仅发生在相对较少的小时内。这种保守方法是实现可靠性的简单途径，但这意味着电网有相当大的余量。“电网已经过度建设了很多。如果你是一家利用率只有30%的航空公司，你不会买更多的飞机，”GridCare公司的联合创始人兼首席执行官阿米特·纳拉扬说，该公司正在开发灵活性技术。他引用了2025年斯坦福大学对北美西部输电线的研究，“如果你运营的电网利用率是30%，从科学上讲，没有理由不能提高到60%。”
“如果你是一家利用率只有30%的航空公司，你不会买更多的飞机。如果你运营的电网利用率是30%，从科学上讲，没有理由不能提高到60%。”
平心而论，灵活性对电网运营商来说并非完全陌生。几十年来，他们一直采用一种称为“需求响应”的技术：当看起来需求将过于接近供应时——比如在热浪期间许多人同时打开空调时——他们会致电大型商业或工业设施，要求其关闭部分运营。这种方法有助于避免启动所谓的“调峰电厂”（通常使用化石燃料），但它速度慢、不精确且难以规模化。
进入21世纪，随着电动汽车和太阳能电池板等技术带来新挑战，更多联网的电网也提供了新的灵活性手段。虚拟电厂提供了一种更智能、更快、更精细的替代方案。从工厂到拥有智能恒温器、太阳能电池板或大型电池的房主，各种电力客户都会允许公用事业公司调整其用电量以帮助满足需求——他们通常会因这种（通常不易察觉的）麻烦而获得报酬。
随着2022年ChatGPT发布引发了生成式AI热潮，一些公司开始将灵活性视为一种更轻松、更高效、更经济地建立数据中心的方式。如果他们将AI资金引入现有电网，并减少或推迟昂贵升级的需求，数据中心实际上可以帮助分摊固定成本，从而降低其他用户的电价。例如，杜克大学今年二月发布的一项研究发现，灵活性可将电价降低0.5%至2.8%。
关键在于弄清楚以耗电闻名的数据中心如何在灵活连接受到限制时继续运行。灵活性专家设想了三种可能的方式。最简单的是让新的数据中心安装现场备用电源存储或发电设备，以便在电网满载时使用——当然，费用自理。
设施也可以通过利用虚拟电厂来填补缺口。公用事业公司将调低对注册了虚拟电厂的用户的供电，而数据中心则为其灵活性向这些用户支付费用。这种方法不需要任何重大基础设施，但需要公用事业公司有一个大型的虚拟电厂项目，并在电网面临压力时协调好交换。虽然近40个州都存在一定程度的虚拟电厂，但管理它们的规则差异很大，而且它们在部分地区被赋予的权力比在其他地区更大。
最后，数据中心可以在高峰时段简单地减少用电。传统观点认为，他们不会接受这样的限制，尤其是当每个进行密集计算的服务器都可能像是一只能下小金蛋的鹅时。但一些专家打赌，快速启动和运行的价值足以改变他们的想法。“有一个明显且不断增长的趋势，”Emerald AI的首席科学家艾丝·科斯克恩说，“运营商越来越愿意用一定程度的灵活性来换取更快的电网互联。”
总部位于硅谷的初创公司GridCare，是首批利用灵活性让数据中心快速上线的公司之一。曾在斯坦福大学研究智能电网的首席执行官纳拉扬解释说，该公司并非只在电力需求最高的最坏情况下审视电网，而是分析系统在所有条件下的状态。它将电网的每个部分——包括发电厂、线路、变电站和家庭——输入到一个生成式AI模型中，该模型可为不同的电网配置创建“数字孪生”。然后，它挑选出能够在保持可靠性的同时释放容量的结果，并将这些结果输入另一个基于电阻器、电容器等电气元件物理原理训练的模型，以确保其现实可行。
GridCare在“硅森林”（位于太平洋西北地区的一个区域，因当地占主导地位的树木和后来兴起的IT产业而得名）找到了第一位客户。当地电网需要更多容量来支持更多的数据中心。“数据中心想要‘电力速度’，”波特兰通用电气（当地发电和配电公司）的数据中心关系经理艾萨克·巴罗说，“但输电建设是一个漫长且成本高昂的过程。”
2024年，Aligned Data Centers找到PGE，希望扩大其在俄勒冈州希尔斯伯勒的业务，PGE采纳了GridCare的建议。Aligned将安装一个31兆瓦的电池，计划于2027年5月投入使用，并在电网拥堵时减少高达该数值的用电量。结合其他灵活性措施，这块电池使PGE能够在不新建任何发电厂的情况下，将其可提供给Aligned及其他附近运营商的容量增加80兆瓦。尽管希尔斯伯勒的数据中心建设面临当地人的诸多反对，但巴罗指出，这可能产生降低用户成本的连锁效应，因为它分摊了费用。
其他公司也在推广不同形式的灵活性。自2023年以来，谷歌一直在将处理负载从需求激增区域的设施转移到压力较小的地点。它已与包括田纳西河流域管理局和印第安纳密歇根电力公司在内的五家公用事业公司签署了协议，增加了多达千兆瓦的灵活性。
作为美国和加拿大主要的虚拟电厂提供商，Voltus推出了一项“自带容量”计划，数据中心公司可以资助附近的虚拟电厂。电网运营商可以在繁忙时段使用虚拟电厂来降低需求，参与者则会获得经济上的感谢。“我们可以在几个月内创建新的虚拟电厂，”Voltus的能源市场副总裁艾米丽·奥维斯说。今年6月，他们签署了首个此类数据中心协议：一个为期三年的计划，谷歌将在PJM互联电网中资助一个虚拟电厂。
在所有灵活性方法中，Emerald AI的可能是最雄心勃勃的：要求数据中心响应电网的需求。该公司的Conductor软件（可在本地或云端运行）基于首席科学家科斯克恩的研究。她在波士顿大学的团队在2013年的两篇论文中表明，数据中心可以监控电网并帮助平衡巨大的功率波动，例如太阳能和风能的间歇性影响。到2022年，她与同事在一个由36台研究服务器组成的集群上测试了他们的方法，并证明该系统可以在不破坏其正在运行的进程的情况下遵守功率限制。
对Conductor而言，最重要的问题之一是决定哪些AI进程可以减速以节省能源而不损害性能。许多公司会对其任务进行优先级排序——例如，实时聊天机器人查询的优先级可能高于深度研究项目中的网络搜索。当它们没有这样做时，Emerald AI会尝试从任务性质推断优先级。然后，Conductor会分析AI工作负载，以确定调整给定处理器的功率将如何影响性能，并帮助满足电网运营商设定的使用限制。
“不同类型工作负载的性能曲线是不同的，”科斯克恩说，“每个AI任务在该曲线上都有不同的位置。我们的智能之处在于确定你在曲线上的位置。”
去年，Emerald AI开始通过一系列测试评估该技术用于实际场景的准备情况，并逐步提高难度。这些试验是与“数据中心灵活负荷倡议”合作进行的——该倡议是谷歌、英伟达等科技公司、杜克能源等公用事业公司以及PJM等电网运营商之间的合作，旨在帮助建立可重复的功率灵活数据中心框架。
第一个挑战是在菲尼克斯，一个快速发展的计算中心。在测试中，Conductor控制了一组装有256个英伟达A100 GPU的服务器机架——这些硬件的功耗大约相当于170个美国家庭的用电量。当面临电网繁忙的模拟场景时，Conductor将芯片的功率降低了25%并持续了三小时，同时保持了可接受的计算性能。Emerald AI及其合作伙伴于2025年12月在《自然·能源》杂志上报告了这些结果。
下一次试验迫使系统在没有事先预警的情况下处理突发的电网波动，并将AI任务从弗吉尼亚州的一个数据中心转移到芝加哥一个不太繁忙的数据中心。随后在伦敦，Conductor接管了主GPU处理器之外的设备，并面临更复杂的波动组合，包括非常短和长时间的拥堵——以及臭名昭著的“电热水壶效应”。
迄今为止的进展表明，灵活性至少在部分情况下是可行的，但目前只有一小部分运营商尝试过。“我们才刚刚进入比赛的初始局，”2025年普林斯顿研究的作者之一、专注于数据中心灵活性的初创公司Firma的联合创始人杰西·詹金斯说，“人们正在认识到这是一个潜在的解决方案。动机是存在的；有一些定制化的例子。但还没有一套统一的、可以作为默认选项的解决方案集，而这是我们最终需要达到的。”
尽管数据中心在美国各地涌现，但地球上没有任何地方能比得上北弗吉尼亚州“数据中心走廊”累积的计算能力。该地区拥有约500个计算密集型设施，占全球总容量的13%；紧随其后的两个热点地区，北京和俄勒冈州，各占6%。
弗吉尼亚州有提议再建造数百个设施，但一项政府研究发现，如果所有这些计划都得以实施，到2040年该州的电力需求将增长183%（约26吉瓦），即使支持其中一半也很困难。Emerald AI、英伟达、Digital Realty及其合作伙伴正在马纳萨斯郊区建造的功率灵活数据中心，可以展示数据中心如何从现有容量中挤出所需电力。该设施计划于今年晚些时候上线，旨在让Conductor有机会在迄今最大规模上管理电力，并首次在实时电网上回应当前状况。在英国演示中，Conductor管理了一个130千瓦的AI集群；在马纳萨斯，它将控制一个96兆瓦的超大规模AI工厂。
当我们从化石燃料向必须兼顾太阳能、风能、电池和电动汽车等技术的未来过渡时，一定程度的灵活性将发挥关键作用。
对于PJM来说，马纳萨斯设施指明了应对当前电力紧缺的一条潜在路径。“我们认为，不同形式的数据中心灵活性，对于在短期到中期内可靠地整合数据中心负荷至关重要，”PJM负责需求侧市场的经理斯科特·贝克说。
但并非所有电网专家都如此乐观。PJM的市场监督机构（负责监督电网运营商）表示，在增加容量方面没有捷径可走。“认为可以在不增加新发电能力的情况下增加大量数据中心负荷，这是一种魔法思维，”自1999年起担任PJM市场监督机构负责人的经济学家约瑟夫·鲍林说。
他指出，其中一个问题是，无法保证数据中心在需求高峰期真的会减少用电。也就是说，在缺乏法律或监管推动实现灵活性或合规的情况下，公用事业公司将无法介入帮助防止，比如说，停电。公用事业公司可以依赖发电厂等资源，但他们无法控制或依赖数据中心。“他们不希望是完全可中断的，”鲍林在谈到这些设施时说。
科技公司顾问斯蒂芬·恩佩多克勒斯将灵活性视为一种工具而非万能药。“这些方法对于提高电网可靠性和更好地利用我们已有的基础设施非常出色，”他说，“但它们是优化工具。”他继续说道，它们不能替代“仍然需要的发电、输电和配电能力扩展”。
灵活性倡导者同意，从长远来看，无论AI是否继续繁荣，电气化都将推动对更多发电和输电的需求。当我们从化石燃料向必须兼顾太阳能、风能、电池和电动汽车等技术的未来过渡时，一定程度的灵活性将在更好地利用电网基础设施方面发挥关键作用。国际可再生能源机构2026年1月发布的一份报告发现，到2030年，全球电网所需的灵活性将是2019年的三倍——到2050年则需要十倍——以平衡不断增长的需求与可再生能源的波动性供应。
为AI供电的挑战可能恰恰提供了我们所需的火花，去设计和建设更智能、更灵活的电网，科斯克恩说。“我认为面对这样的危机，没有快速的解决方案，”她说，“有时这样的危机会创造机会去做些不同的事情。”
阿莫斯·齐伯格是一位驻布加勒斯特的自由科技记者。他正在撰写一本关于包括电网在内的技术网络的书。
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Want to get a data center online quickly? Give it some flex.
As the data-center boom puts pressure on the grid, some companies say the answer isn’t just more power plants but software that dials down centers’ energy-guzzling ways when demand spikes.
At the end of a tense and scoreless first half of a soccer match between the English men’s team and rival Germany, millions of Brits let out a collective sigh and did what they so often do in moments of stress: They made tea. That wave of electric kettles clicking on, however, caused a different kind of stress: a huge and sudden increase in demand for electricity. But National Grid, which operates the local transmission network, was ready.
Just as those kettles started heating up, an AI program sent instructions to a data center in London to slow down some of the facility’s power-hungry chips. This reduction helped make sure there was enough supply to match demand, staving off potential blackouts or damage to electrical hardware. For data centers, which normally guzzle power without consideration for anyone or anything else’s needs, it was a radical departure.
It was also a simulation. In December 2025, engineers sought to test a new breed of data center built to be flexible about its electricity needs, so they re-created the energy demand facing the UK’s grid during a match from the 2020 Euro tournament. They wanted to see how their software, called Conductor, would have responded had it been online at the time.
Conductor is the signature product of Emerald AI, a firm based in Washington, DC, that’s part of a wave of companies trying to figure out whether data centers can work within the confines of the existing electric grid.
This year, Emerald is set to deploy Conductor in a new facility in the part of Virginia known as Data Center Alley, this time connected to the live grid. When overall demand spikes, Conductor will turn down the power used by the data center, while making sure its servers still carry out their timeliest and most important jobs. Emerald’s partners on the project—which include Nvidia and the giant data-center operator Digital Realty—bill it as one of the world’s first “power-flexible AI factories.”
Demonstrating that data centers can participate in this kind of give-and-take could ease what many tech leaders identify as the bottleneck in getting facilities online: It takes far longer to get approval for, construct, and connect new power plants than to build data centers. PJM, the grid operator in Virginia and the largest one in the US, for instance, needs eight years to bring new generation online, according to RMI, an energy research and advocacy group. “We need to solve the energy equation,” says Josh Parker, head of sustainability at Nvidia. “AI factory flexibility is the bridge between the incredible demand for AI and the immediate limitations of our energy grid.”
Speed, though, is only one of the issues. Once facilities do plug in, neighbors often criticize them for drawing too much electricity and contributing to rising prices. They say the data centers generate more noise than they do long-term jobs, contribute to pollution, and threaten to put people out of work. Organizers stalled over $150 billion worth of projects in 2025, according to Data Center Watch, and policymakers alert to the public mood are starting to impose limitations on development.
More than a dozen states are considering bans, and local moratoriums are in effect in places like Minneapolis and DeKalb County in Georgia. At the federal level, the GRID Act, a bipartisan bill in the US Senate, proposes to sever new data centers from public grids entirely. Some operators are already moving that way by trying to develop their own power generation.
Rather than rushing to build new power plants, companies could find part of the solution to the crunch right under our noses—or, more precisely, in the transmission lines under our feet and above our heads. The existing system operates near its full capacity during only a small number of high-demand hours throughout the year. This means, some grid experts argue, that if data centers can limit the power they draw during those stretches, they won’t need to wait for big infrastructure upgrades or build their own off-grid generation.
Indeed, a growing number of studies have shown there could be plenty of power available for data centers that can flex. A widely discussed 2025 report from researchers at Duke University found that the US grid could offer an additional 76 gigawatts—about 5% of its entire capacity, and about enough to accommodate projected data-center growth in the US through 2030—to facilities that are willing to reduce their usage just 0.25% of the time. That’s about 22 hours a year. And when researchers from Princeton University and two grid-modernization companies looked at locations for new data centers in the PJM region, their report, which was funded by Google, found that a 500-megawatt facility capable of flexing for less than 1% of the year could reach full operation three to five years faster than one that’s inflexible.
Flexible power connections could also help data centers address some of their PR problems. By decreasing their draw at times of grid stress, for instance, they could avoid diverting power from where it’s most needed, thus boosting stability. By using existing capacity, they might be able to reduce the need for new fossil-fuel power plants and spread fixed costs over more electricity users, pushing prices down.
The AI power pinch is attracting resources and research into strategies for grid flexibility overall, which could help negotiate a tricky period: Taken together with electric vehicles, air-conditioning, and other sectors, data centers are helping drive what analysts predict will be a 25% increase in US electricity demand by 2030 compared with 2023 levels.
Ideally, flexibility gives grid operators more control over the flow of electrons, making them leaders of a harmonious ensemble rather than hostages to inflexible electricity requirements. That will help them manage demand spikes across the entire system and deal more effectively with the intermittent nature of renewables like wind and solar. “Demand flexibility is incredibly useful for power grids,” says Johanna Mathieu, a grid expert at the University of Michigan. “It helps reduce electricity costs and improve grid reliability.”
But while advocates see plenty of benefits, the concept brings complexity. For data centers, compromising on energy needs can be a hard sell. Flexibility requires utilities and grid operators, which tend to be operationally conservative, to change long-held practices. And some skeptics also say that flexibility distracts from the very real need to build more grid infrastructure faster, and could even pose risks to our electricity supply.
Still, some technologists, grid operators, and utilities are hoping to show that flexibility works—not only in white papers or simulations but in real life.
The poster children for data-center growth default toward inflexibility. Hyperscalers like Microsoft and Oracle have proposed enormous new centers, many of which would rely on off-grid, natural-gas-burning power plants. When xAI wanted to speed up the buildout of the Colossus site outside Memphis, Tennessee, it rolled up with gas turbines on flatbed trucks. The facility, now in operation, is facing blowback from regulators and residents about the spike it’s causing in emissions and other pollution. In any case, there aren’t enough gas turbines worldwide to meet the demand from data-center operators.
One big obstacle for anyone demanding a lot of power is that our grids are mostly rigid. They’re designed to supply enough power to meet total demand when it’s highest, even if that’s for only a relatively small number of hours a year. That conservative approach is a simple route to reliability, but it means that the grid has quite a bit of headroom. “The grid is already overbuilt by a lot. If you were an airline running at 30% utilization, you would not buy more planes,” says Amit Narayan, the cofounder and CEO of GridCare, a company developing flexibility technologies, referring to a 2025 Stanford study of transmission lines in western North America. “If you are running a grid at 30% utilization, there’s no scientific reason you can’t go to 60.”
“If you were an airline running at 30% utilization, you would not buy more planes. If you are running a grid at 30% utilization, there’s no scientific reason you can’t go to 60.”
To be fair, the idea of flexibility isn’t entirely foreign to grid operators. For decades, they’ve practiced a technique called demand response: When it looks as if demand will get too close to supply, as it might during a heat wave when many people turn on the AC at the same time, they call large commercial or industrial facilities and ask them to shut down parts of their operations. This method can help avoid the need to fire up so-called peaker plants, which run on fossil fuels, but it’s slow, imprecise, and hard to scale.
In the 2000s, as the adoption of technologies like electric cars and solar panels presented new challenges, more internet-connected grids also provided new means of flexibility. Virtual power plants, or VPPs, offered a smarter, faster, more granular alternative. Electricity customers ranging from factories to homeowners with smart thermostats, solar panels, or big batteries would allow the utility to adjust their draw to help meet demand—often getting paid for their (frequently unnoticed) trouble.
After the generative AI boom began with the release of ChatGPT in 2022, some companies began to see flexibility as a way to get data centers set up more easily, efficiently, and affordably. If they bring AI money into existing grids and reduce or defer the need for expensive upgrades, data centers could actually help spread out fixed costs so as to lower rates for other users. A study from Duke University published this past February, for instance, found that flexibility could reduce rates by 0.5% to 2.8%.
The trick is figuring out how data centers, notorious power hogs, can keep operating when their flexible connections are throttled. Flexibility specialists envision three possible ways. The simplest is for the new data center to install on-site backup power storage or generation to tap when the grid is maxed out—at their own expense, of course.
A facility could also fill the gap by drawing on a VPP. The utility would turn down the electricity going to users who signed up for the VPP, and the data center would pay them for their flexibility. This method wouldn’t require any major infrastructure, but it would require the utility to have a big VPP program and to coordinate the exchange at a time when the grid was under stress. While VPPs exist to some extent in nearly 40 states, the rules governing them vary widely, and they are empowered to do more in some areas than in others.
Finally, a data center could simply use less power at peak times. The conventional wisdom is that they won’t go for such limits, particularly when every number-crunching server can feel like a goose potentially laying little golden eggs. But some experts are betting that the value of getting up and running quickly is enough to change their minds. “There is a clear and growing trend,” says Ayse Coskun, chief scientist at Emerald AI. “Operators are increasingly willing to trade some level of flexibility for faster grid interconnection.”
GridCare, a startup based in Silicon Valley, was one of the first companies to use flexibility to get data centers online quickly. Instead of looking at grids only in worst-case scenarios when electricity demand is highest, the company analyzes the system under all conditions, explains CEO Narayan, who studied smart grids at Stanford. It feeds every part of the grid—including power plants, lines, substations, and homes—into a generative AI model that creates a “digital twin” for different grid configurations. It then picks out results that could unlock capacity while maintaining reliability, and it feeds those into another model trained on the physics of electrical components like resistors and capacitors to make sure they’re realistic.
GridCare found its first customer in the Silicon Forest, an area in the Pacific Northwest named for the trees that dominate the landscape and the IT industry that has more recently sprouted up there. The local grid needed more capacity to support more data centers. “Data centers wanted ‘speed to power,’” says Isaac Barrow, a manager of data-center relations at Portland General Electric, or PGE, the local power generator and distributor, “but transmission buildout is a long process that’s very costly.”
In 2024, Aligned Data Centers came to PGE wanting to expand its operation in Hillsboro, Oregon, and PGE followed a recommendation from GridCare. Aligned will install a 31-megawatt battery, set to be in service in May 2027, and decrease its draw by up to that amount when the grid becomes congested. Bundled with other flexibility measures, that battery has allowed PGE to increase the capacity it can offer Aligned and other nearby operators by 80 megawatts without any new power plants. Though the buildout of data centers in Hillsboro has faced plenty of pushback from locals, Barrow points out that it could have the knock-on effect of lowering costs for ratepayers, because it spreads out the tab.
Other companies are promoting different flavors of flexibility. Google has been moving processing loads from facilities in areas experiencing demand spikes to those in less stressed spots since 2023. It’s signed agreements with five utilities, including the Tennessee Valley Authority and Indiana Michigan Power, that add as much as a gigawatt of flexibility.
Voltus, a major VPP provider across the US and Canada, markets a “bring your own capacity” program in which a data-center company can fund a VPP nearby. The grid operator can use the VPP to decrease demand at busy times, and participants get a financial thank-you. “We can spin up new VPPs on the order of months,” says Emily Orvis, Voltus’s vice president of energy markets. In June, the company signed their first such data-center deal: a three-year plan in which Google will bankroll a VPP in the PJM interconnection.
Of all the approaches to flexibility, Emerald AI’s may be the most ambitious: asking data centers to dial into the grid’s needs. The company’s Conductor software, which can run on premises or in the cloud, builds on the research of chief scientist Coskun. Her group at Boston University showed in a pair of 2013 papers that a data center could watch the grid and help balance big power fluctuations, such as the intermittent effects of solar and wind power. By 2022, she and her colleagues had tested their methods on a cluster of 36 research servers and shown that the system could respect power limits without breaking the processes it was running.
One of the most important questions for Conductor is deciding which AI processes can be slowed down to save energy without kneecapping performance. A lot of companies label their jobs by priority—a real-time chatbot query, for instance, might outrank something like a web search that’s part of a deep research project. When they don’t, Emerald AI tries to infer priority from the nature of the job. Conductor then analyzes the AI workload to determine how tweaking the power to a given processor will affect the performance and help meet the usage limits set by the grid operator.
“The performance curve changes for different kinds of workloads,” says Coskun. “Each AI job is going to have a different location on that curve. Our intelligence is figuring out where you are on that curve.”
Last year, Emerald AI began assessing the technology’s readiness for real-world use in a series of tests, raising the difficulty each time. The trials were carried out in partnership with the Data Center Flexible Load Initiative—a collaboration among tech companies like Google and Nvidia, utilities like Duke Energy, and grid operators like PJM that aims to help establish a repeatable framework for power-flexible data centers.
The first challenge was in Phoenix, a fast-growing computing hub. For the test, Conductor took control of a group of server racks laden with 256 Nvidia A100 GPUs—hardware that can use about as much power as around 170 US homes. When presented with a simulation of a busy grid, Conductor reduced the power to the chips by 25% for three hours, while maintaining acceptable computing performance. Emerald AI and its partners reported the results in a paper in Nature Energy in December 2025.
The next trial forced the system to juggle surprise grid fluctuations without advance warning and redirect AI jobs from a data center in Virginia to a less busy one in Chicago. Then, in London, Conductor took the reins of equipment beyond the main GPU processors and faced a more complicated mix of fluctuations, including very short and long bouts of congestion—plus the notorious teakettle effect.
The progress so far shows that flexibility can work, at least in some situations, but only a small fraction of operators have pursued it as yet. “We’re just in the beginning innings of the game,” says Jesse Jenkins, one of the authors of the 2025 Princeton study and cofounder of Firma, a startup that works on data-center flexibility. “People are recognizing that this is a potential solution. The motivation is there; there are some bespoke examples. But there’s no uniform solution set that’s the default option, which is where we need to get.”
While data centers are going up across the US, no place on Earth comes close to the accumulated computing muscle in Northern Virginia’s Data Center Alley. The region is home to around 500 compute-crunching facilities, which represent 13% of the entire world’s capacity; the next two hot spots, Beijing and Oregon, contain 6% each.
There are proposals to build hundreds more facilities in Virginia, but a government study found that the state’s electricity demand will increase 183% (around 26 gigawatts) by 2040 if they all go forward, and supporting even half would be difficult. The power-flexible data center that Emerald AI, Nvidia, Digital Realty, and their partners are building in the suburb of Manassas could demonstrate how data centers can squeeze the power they need out of existing capacity. The facility, slated to come online later this year, is intended to give Conductor the chance to manage power at the largest scale yet and to respond to conditions on a live grid for the first time. In the UK demonstration, Conductor managed a 130-kilowatt AI cluster; in Manassas, it will pull the strings of a 96-megawatt hyperscale AI factory.
Some degree of flex will play a key role as we transition away from fossil fuels and toward a future that has to juggle technologies like solar and wind power, batteries, and electric cars.
For PJM, the Manassas facility points to a potential path through the current power crunch. “We think data-center flexibility, in different forms, will be essential for the reliable integration of data-center load over the short to mid term,” says Scott Baker, who manages demand-side markets at PJM.
But not all grid experts are so sanguine. PJM’s market monitor, which oversees the grid operator, says there are no workarounds when it comes to adding capacity. “The notion that large amounts of data-center load can be added without adding new generation is magical thinking,” says Joseph Bowring, an economist and the head of PJM’s market monitor since 1999.
One problem, he says, is that there’s no way to guarantee that a data center will actually take less power when demand is high. That is, absent any legal or regulatory push for flexibility or compliance, the utility won’t be able to step in to help prevent, say, a blackout. Utilities can rely on resources like power plants, but they can’t control or rely on data centers. “They do not want to be fully interruptible,” Bowring says of the facilities.
Stephen Empedocles, an advisor for technology companies, views flexibility as more of a tool than a silver bullet. “These approaches are excellent for improving grid reliability and getting more out of the infrastructure we already have,” he says, “but they are optimization tools.” They’re not substitutes for the “generation, transmission, and distribution expansion that will still be required,” he continues.
Flexibility advocates agree that over the long term, whether or not AI continues to boom, electrification will drive a need for more generation and transmission. Some degree of flex will play a key role in using grid infrastructure better as we transition away from fossil fuels and toward a future that has to juggle technologies like solar and wind power, batteries, and electric cars. A report published by the International Renewable Energy Agency in January 2026 found that grids around the world will need three times as much flexibility in 2030 as they had in 2019—and 10 times as much by 2050—to balance increasing demand with fluctuating supplies of renewable energy.
The challenge of powering AI could provide just the spark we need to do the work of designing and building smarter, more flexible grids, says Coskun. “I think with a crisis like this, there’s no quick solution,” she says. “Sometimes a crisis like this creates an opportunity to do something differently.”
Amos Zeeberg is a freelance science and technology journalist based in Bucharest. He’s developing a book about technology networks, including electric grids.
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