K\u00fcnstliche Intelligenz macht Strom zum entscheidenden Engpass in der Rechenleistung. Der Strombedarf von Rechenzentren wird sich bis 2030 voraussichtlich verdoppeln, und die Stromnetze k\u00f6nnen diese Last nicht schnell genug decken. Gasturbinen in unmittelbarer N\u00e4he von Rechenzentren sind eine der wenigen M\u00f6glichkeiten, schnell eine zuverl\u00e4ssige Stromversorgung zu gew\u00e4hrleisten. Daher verzeichnen Anlagenbauer wie Baker Hughes Rekordauftr\u00e4ge. Wir erkl\u00e4ren Ihnen, warum die Nachfrage real ist, warum Gas einen immer gr\u00f6\u00dferen Anteil daran gewinnt und wo der Engpass aktuell liegt.<\/p>\n
Rechenzentren, angetrieben durch k\u00fcnstliche Intelligenz, erh\u00f6hen den Strombedarf schneller, als die Stromnetze ihn decken k\u00f6nnen. Die Internationale Energieagentur prognostiziert, dass sich der weltweite Stromverbrauch von Rechenzentren bis 2030 auf rund 945 Terawattstunden verdoppeln wird, und die Wartelisten f\u00fcr neue Netzkapazit\u00e4ten sind jahrelang lang. Gasturbinen k\u00f6nnen in der N\u00e4he von Rechenzentren installiert werden und liefern eine zuverl\u00e4ssige, unterbrechungsfreie Stromversorgung in k\u00fcrzerer Zeit als ein Netzanschluss. Daher bestellen Hyperscale-Betreiber und -Entwickler diese in gro\u00dfen Mengen. Allein Baker Hughes bestellte im Jahr 2026 in einem einzigen Quartal Gasturbinen mit einer Leistung von 2,7 Gigawatt f\u00fcr Rechenzentren und mobile Stromversorgung.<\/p>\n
Das Ausma\u00df der Nachfrage macht dies zu einem strategischen Thema und nicht zu einem Nischenthema. Die Internationale Energieagentur prognostiziert in ihrer Analyse \u201eEnergie und KI 2025\u201c, dass sich der weltweite Stromverbrauch von Rechenzentren bis 2030 auf rund 945 Terawattstunden etwa verdoppeln wird, was knapp 3 Prozent des weltweiten Stromverbrauchs entspricht, und bis 2035 auf fast 1.200 Terawattstunden ansteigen wird.IEA, Energie und KI<\/a>Der Stromverbrauch von KI-orientierten Rechenzentren w\u00e4chst am schnellsten und verdreifacht sich in diesem Zeitraum etwa.<\/p>\n Diese Last ist nicht nur hoch, sondern auch konzentriert und konstant. KI-Training und -Inferenz laufen rund um die Uhr mit hoher Auslastung \u2013 ein deutlich anderes Profil als der \u00fcbliche kommerzielle Bedarf. Um diese Last zu decken, ist eine zuverl\u00e4ssige Stromversorgung rund um die Uhr erforderlich, nicht nur bei starken Schwankungen.<\/p>\n Die naheliegende L\u00f6sung, das Rechenzentrum ans Stromnetz anzuschlie\u00dfen, st\u00f6\u00dft auf ein entscheidendes Problem: Zeit. In vielen M\u00e4rkten betr\u00e4gt die Wartezeit f\u00fcr einen gro\u00dfen neuen Netzanschluss mehrere Jahre, und der Bau neuer \u00dcbertragungsleitungen dauert noch l\u00e4nger. F\u00fcr einen Hyperscale-Betreiber, der seine KI-Kapazit\u00e4ten schnellstm\u00f6glich bereitstellen will, bedeutet eine mehrj\u00e4hrige Wartezeit auf Strom eine mehrj\u00e4hrige Wartezeit auf Einnahmen.<\/p>\n Diese zeitliche L\u00fccke veranlasst Entwickler dazu, die Energieerzeugung vor Ort oder in unmittelbarer N\u00e4he zu planen. Die eigene Stromversorgung direkt am Geb\u00e4ude, hinter dem Z\u00e4hler, kann schneller erfolgen als das Warten in der Warteschlange f\u00fcr den Netzanschluss. Die Geschwindigkeit der Stromversorgung, nicht nur die Stromkosten, ist heute der entscheidende Faktor daf\u00fcr, wo und wie schnell ein Rechenzentrum gebaut werden kann.<\/p>\n Gasturbinen sind in dreifacher Hinsicht eine L\u00f6sung f\u00fcr Rechenzentren. Sie sind bedarfsgerecht steuerbar, d. h. sie laufen nach Bedarf und liefern die ben\u00f6tigte, konstante Leistung f\u00fcr KI-Rechenprozesse. Sie k\u00f6nnen in der N\u00e4he der Verbraucher platziert werden, wodurch Engp\u00e4sse im \u00dcbertragungsnetz vermieden werden. Und im gro\u00dfen Ma\u00dfstab lassen sie sich schneller implementieren als die meisten Alternativen mit der gleichen Kapazit\u00e4t. Die IEA erwartet einen Ausbau der Erdgaskapazit\u00e4t um rund 175 Terawattstunden, um den Bedarf von Rechenzentren, insbesondere in den Vereinigten Staaten, zu decken.IEA, Energiebedarf durch KI<\/a>).<\/p>\n Dies ist keine Geschichte von Gas versus erneuerbaren Energien. Erneuerbare Energien werden voraussichtlich den gr\u00f6\u00dften Anteil des Bedarfs an neuer Rechenzentrumsenergie decken, beg\u00fcnstigt durch kurze Bauzeiten und niedrige Kosten. Allerdings m\u00fcssen erneuerbare Energien weiter ausgebaut werden, und Gasturbinen geh\u00f6ren zu den Technologien, die diese Rolle heute erf\u00fcllen. Die Folge ist ein sprunghafter Anstieg der Turbinenbestellungen. Baker Hughes buchte im ersten Quartal 2026 Gasturbinen im Wert von 2,7 Gigawatt f\u00fcr Rechenzentren und mobile Stromversorgung \u2013 Teil eines Rekordauftragsvolumens von 7,1 Milliarden US-Dollar im Bereich Industrie- und Energietechnologie.Rigzone<\/a>).<\/p>\n Mit der Verlagerung der Nachfrage hin zu Turbinen hat sich auch der Engpass verlagert. Die IEA stellt fest, dass die Lieferzeiten f\u00fcr neue Gasturbinen mittlerweile mehrere Jahre betragen \u2013 ein Angebotsengpass, der die Inbetriebnahme einiger Gaskraftwerke bis \u00fcber das Jahr 2030 hinaus verz\u00f6gern k\u00f6nnte. Anders ausgedr\u00fcckt: Die Bestellung einer Turbine heute garantiert keine Stromversorgung f\u00fcr morgen.<\/p>\n F\u00fcr Anlagenbauer ist diese Knappheit eine Chance. Deshalb erweitern Baker Hughes, GE Vernova, Siemens Energy und Mitsubishi Power ihre Produktionskapazit\u00e4ten und ihre Auftragsb\u00fccher reichen Jahre in die Zukunft. Baker Hughes peilt bis 2029 einen j\u00e4hrlichen Umsatz von rund 5 Milliarden US-Dollar mit Energiesystemen an und will seine Gasturbinenkapazit\u00e4t bis Ende 2028 gegen\u00fcber dem Stand von 2026 verdoppeln. Wer am schnellsten Turbinen bauen kann, sichert sich die Nachfrage.<\/p>\n F\u00fcr alle Anbieter in diesem Markt gilt: Die knappe Ressource ist schnell verf\u00fcgbare, zuverl\u00e4ssige Energie, nicht abstrakte Energie. K\u00e4ufer sind bereit, f\u00fcr Kapazit\u00e4ten, die die Stromversorgung beschleunigen, einen Aufpreis zu zahlen und sichern sich die Versorgung Jahre im Voraus. Dies ver\u00e4ndert die Positionierung und Preisgestaltung von Ausr\u00fcstung, Gasversorgung und Energiedienstleistungen.<\/p>\n Das erkl\u00e4rt auch, warum ein \u00d6lfeldserviceunternehmen wie Baker Hughes heute \u00fcber die digitale Wirtschaft spricht. Um zu verstehen, wie sich ein gro\u00dfer Energiekonzern genau an diese Nachfrage anpasst, lesen Sie unsere Analyse von Baker Hughes und der Machtwechsel<\/a>, und wie Chevron baut mit dem Projekt Kilby die Stromversorgung f\u00fcr Rechenzentren aus.<\/a>.<\/p>","protected":false},"excerpt":{"rendered":" K\u00fcnstliche Intelligenz l\u00e4sst den Strombedarf von Rechenzentren bis 2030 verdoppeln, w\u00e4hrend die Netzauslastung jahrelang anh\u00e4lt. Gasturbinen liefern schnell zuverl\u00e4ssige Leistung, weshalb Baker Hughes und andere Unternehmen Rekordauftr\u00e4ge verzeichnen. Hier erfahren Sie warum.<\/p>","protected":false},"author":12,"featured_media":3989,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"p54_article_data":"{\"meta\":{\"kicker\":\"Answer \u00b7 Data Center Power\",\"topics\":[\"Energy\",\"Analysis\"],\"title\":\"Why Are Data Centers Driving Demand for Gas Turbines?\",\"dek\":\"Artificial intelligence is turning electricity into the binding constraint on computing. Data center power demand is set to roughly double by 2030, and grids cannot connect that load fast enough. Gas turbines sited next to the data center have become one of the few ways to add firm power quickly, which is why equipment makers like Baker Hughes are booking record orders. Here is why the demand is real, why gas is winning a share of it, and where the bottleneck now sits.\",\"date\":\"30\/07\/2026\",\"readTime\":\"7 min read\",\"author\":\"Project 54 Research & Strategy\"},\"quickAnswer\":{\"q\":\"Why are data centers driving demand for gas turbines?\",\"a\":\"Data centers, driven by artificial intelligence, are adding electricity demand faster than grids can supply it. The International Energy Agency projects global data center electricity use will roughly double to around 945 terawatt hours by 2030, and connection queues for new grid capacity stretch for years. Gas turbines can be installed next to a data center to deliver firm, always on power on a shorter timeline than a grid connection, so hyperscale operators and developers are ordering them in volume. Baker Hughes alone booked 2.7 gigawatts of gas turbines for data centers and mobile power in a single quarter in 2026.\"},\"takeaways\":[\"The International Energy Agency projects data center electricity demand will roughly double to about 945 terawatt hours by 2030, with AI focused data centers growing fastest.\",\"Grid connection queues run for years, so on site or near site generation is often the fastest way to power a new data center.\",\"Natural gas is expected to supply a large share of the new load, expanding by around 175 terawatt hours to meet data center demand, notably in the United States.\",\"Gas turbines deliver firm, dispatchable power that matches the constant, high load profile of AI computing, unlike weather dependent renewables on their own.\",\"The bottleneck has shifted to the turbines themselves: lead times now stretch several years, which is why equipment makers are booking record order books and expanding capacity.\"],\"sections\":[{\"id\":\"demand\",\"q\":\"How much new electricity do data centers actually need?\",\"h\":\"A demand curve that doubles\",\"p\":[\"The scale of the demand is what makes this a strategic issue rather than a niche one. The International Energy Agency, in its 2025 Energy and AI analysis, projects that global electricity consumption from data centers will roughly double to around 945 terawatt hours by 2030, just under 3 percent of world electricity, and rise toward 1,200 terawatt hours by 2035 (IEA, Energy and AI<\/a>). Electricity use from AI focused data centers grows fastest of all, roughly tripling over the period.\",\"That load is not just large, it is concentrated and constant. AI training and inference run around the clock at high utilisation, which is a very different profile from ordinary commercial demand. Meeting it requires firm power that is available every hour, not just when the wind blows or the sun shines.\"]},{\"id\":\"grid\",\"q\":\"Why not just connect to the grid?\",\"h\":\"The queue is the problem\",\"p\":[\"The obvious answer, connect the data center to the grid, runs into a hard constraint: time. In many markets the queue to secure a large new grid connection stretches for several years, and new transmission takes even longer to build. For a hyperscale operator racing to deploy AI capacity, a multi year wait for power is a multi year wait for revenue.\",\"That timing gap is what pushes developers toward on site or near site generation. Building your own power next to the building, behind the meter, can be faster than waiting in the interconnection queue. Speed to power, not just cost of power, is now the deciding factor for where and how fast a data center can be built.\"]},{\"id\":\"gas\",\"q\":\"Why gas turbines specifically?\",\"h\":\"Firm power on a shorter timeline\",\"p\":[\"Gas turbines fit the data center problem on three dimensions. They are dispatchable, meaning they run on demand and provide the firm, constant power AI computing needs. They can be sited next to the load, avoiding the transmission bottleneck. And at scale they can be deployed faster than most alternatives that deliver the same firm capacity. The IEA expects natural gas to expand by around 175 terawatt hours to help meet data center demand, notably in the United States (IEA, Energy demand from AI<\/a>).\",\"This is not a story of gas versus renewables. Renewables are expected to supply the largest single share of new data center demand, helped by short build times and low cost. But renewables need firming, and gas turbines are one of the technologies filling that role today. The result is a surge in turbine orders. Baker Hughes booked 2.7 gigawatts of gas turbines for data centers and mobile power in a single quarter of 2026, part of a record 7.1 billion dollars of Industrial and Energy Technology orders (Rigzone<\/a>).\"]},{\"id\":\"bottleneck\",\"q\":\"Where is the bottleneck now?\",\"h\":\"The turbines themselves\",\"p\":[\"As demand has shifted to turbines, the constraint has moved with it. The IEA notes that lead times for new gas turbines now stretch several years, a supply crunch that could delay commissioning of some gas fired capacity beyond 2030. In other words, ordering a turbine today does not guarantee power tomorrow.\",\"For equipment makers, that scarcity is the opportunity. It is why Baker Hughes, GE Vernova, Siemens Energy and Mitsubishi Power are expanding manufacturing capacity and why their order books now reach years into the future. Baker Hughes is targeting roughly 5 billion dollars of annual power systems revenue by 2029 and doubling its gas turbine capacity from 2026 levels by the end of 2028. Whoever can build turbines fastest captures the demand.\"]},{\"id\":\"means\",\"q\":\"What does this mean for energy suppliers and sellers?\",\"h\":\"Sell speed to power\",\"p\":[\"For anyone selling into this market, the lesson is that the scarce resource is firm power delivered quickly, not energy in the abstract. Buyers will pay a premium for capacity that shortens their time to power, and they will lock in supply years ahead to secure it. That reshapes how equipment, gas supply and power services should be positioned and priced.\",\"It also explains why an oilfield services name like Baker Hughes now talks about the digital economy. To understand how a major energy company is repositioning around exactly this demand, read our analysis of Baker Hughes and the power pivot<\/a>, and how Chevron is building power for data centers with Project Kilby<\/a>.\"]}],\"media\":{\"image\":{\"src\":\"https:\/\/projectfifty4.com\/wp-content\/uploads\/2026\/07\/data-center-power-demand-operations.jpg\",\"label\":\"Engineers reviewing live data on an operations wall, the kind of always on computing load that is driving data center power demand.\",\"credit\":\"Project 54\"},\"infographicLabel\":\"FIG.54 \/ DATA CENTER POWER \/ GAS TURBINE DEMAND \/ REV 1.0\"},\"poll\":{\"q\":\"What will be the biggest constraint on data center growth to 2030?\",\"options\":[{\"id\":\"power\",\"label\":\"Access to firm power\",\"insight\":\"The IEA sees data center demand doubling by 2030 while grid queues stretch for years. Firm power, not chips, is emerging as the binding constraint.\"},{\"id\":\"turbines\",\"label\":\"Equipment lead times\",\"insight\":\"Gas turbine lead times now run several years. The bottleneck has moved from the grid to the factory floor that builds the turbines.\"},{\"id\":\"grid\",\"label\":\"Grid and transmission\",\"insight\":\"New transmission takes many years to permit and build, which is exactly why developers are turning to behind the meter generation.\"},{\"id\":\"cost\",\"label\":\"Cost of energy\",\"insight\":\"Cost matters, but for AI operators racing to deploy, speed to power is often worth more than the cheapest electron.\"}],\"note\":\"The common thread is time. Every constraint on the list is really a constraint on how fast firm power can be delivered.\"},\"faq\":[{\"q\":\"Why are data centers driving demand for gas turbines?\",\"a\":\"AI is pushing data center electricity demand up faster than grids can supply it, with the IEA projecting a roughly doubling to around 945 terawatt hours by 2030. Grid connection queues stretch for years, so operators use gas turbines sited next to the data center to add firm power on a shorter timeline. Baker Hughes booked 2.7 gigawatts of such turbines in a single quarter of 2026.\"},{\"q\":\"How much electricity will data centers use by 2030?\",\"a\":\"The International Energy Agency projects that global data center electricity consumption will roughly double to around 945 terawatt hours by 2030, just under 3 percent of world electricity, and rise toward 1,200 terawatt hours by 2035. AI focused data centers grow fastest, tripling over the period.\"},{\"q\":\"Why not use renewables to power data centers?\",\"a\":\"Renewables are expected to supply the largest single share of new data center demand because they are cheap and quick to build. But AI computing needs firm, around the clock power, and renewables on their own are weather dependent. Gas turbines provide the firming capacity that keeps the load supplied at all hours, so the two are used together rather than as alternatives.\"},{\"q\":\"How long does it take to get a gas turbine for a data center?\",\"a\":\"Lead times have lengthened significantly. The IEA notes that turbine deliveries for new gas fired plants now face lead times of several years, which could delay some commissioning beyond 2030. That scarcity is why equipment makers are expanding manufacturing capacity and booking multi year order backlogs.\"},{\"q\":\"Which companies make gas turbines for data centers?\",\"a\":\"The main suppliers include Baker Hughes, GE Vernova, Siemens Energy and Mitsubishi Power. Baker Hughes booked a record 7.1 billion dollars of Industrial and Energy Technology orders in the second quarter of 2026, including 2.7 gigawatts of gas turbines for data centers and mobile power, and is targeting roughly 5 billion dollars of annual power systems revenue by 2029.\"}],\"newsletter\":{\"eyebrow\":\"The P54 Energy Growth Brief\",\"title\":\"Revenue architecture, engineered, for energy B2B\",\"body\":\"Join energy leaders getting our weekly analysis of how the industry's biggest players build growth, and what it means for how you sell and market. No noise, just the strategy behind the moves.\",\"cta\":\"Subscribe\"},\"related\":[{\"title\":\"Baker Hughes and the Power Pivot\",\"topic\":\"Industry Leader\",\"href\":\"\/insights\/baker-hughes-data-center-power-strategy-2026\/\"},{\"title\":\"Chevron Starts Selling Power, Not Barrels: Inside Project Kilby\",\"topic\":\"Industry Leader\",\"href\":\"\/insights\/chevron-microsoft-project-kilby\/\"},{\"title\":\"SLB's Digital Reinvention\",\"topic\":\"Industry Leader\",\"href\":\"\/insights\/slb-schlumberger-digital-oilfield-services-strategy-2026\/\"},{\"title\":\"ADNOC and XRG: A Bet on Gas, Chemicals and AI Power\",\"topic\":\"Industry Leader\",\"href\":\"\/insights\/adnoc-xrg-gas-chemicals-ai-bet\/\"}],\"listenTime\":\"Listen: 12 min\"}","p54_faq":"","p54_media":"","p54_comments_enabled":"","footnotes":""},"categories":[92,125],"tags":[],"class_list":["post-3990","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analysis","category-strategy"],"acf":[],"_links":{"self":[{"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/posts\/3990","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/comments?post=3990"}],"version-history":[{"count":1,"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/posts\/3990\/revisions"}],"predecessor-version":[{"id":3991,"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/posts\/3990\/revisions\/3991"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/media\/3989"}],"wp:attachment":[{"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/media?parent=3990"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/categories?post=3990"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/projectfifty4.com\/de\/wp-json\/wp\/v2\/tags?post=3990"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Die Warteschlange ist das Problem<\/h2>\n
Feste Macht in k\u00fcrzerer Zeit<\/h2>\n
Die Turbinen selbst<\/h2>\n
Verkaufe Geschwindigkeit an Leistung<\/h2>\n