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Data Center News > Blog > Design > PG&E’s Data Center-focused $73B Transmission Spend
Design

PG&E’s Data Center-focused $73B Transmission Spend

Last updated: October 6, 2025 5:54 pm
Published October 6, 2025
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PG&E’s Data Center-focused $73B Transmission Spend
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California utility Pacific Gasoline and Electrical Firm (PG&E) introduced plans to spend $73 billion by 2030 in a transfer that positions information heart collaboration on the coronary heart of next-generation grid sustainability efforts.

Based on studies, the corporate has recognized round 10 GW of latest electrical energy demand from information heart tasks over the following decade – equal to powering a number of million properties.

Knowledge facilities, particularly these supporting AI, require huge, uninterrupted energy. PG&E is tasked with reinforcing and increasing the transmission community to make sure grid stability and scale back the chance of blackouts as load intensifies.

Jennifer Cahill, affiliate vp, campus infrastructure integration lead at Black & Veatch, informed DCN that to keep away from compromising grid reliability, versatile interconnection fashions, improved forecasting instruments and coordinated funding throughout stakeholders are required.

“Simply as necessary is supporting infrastructure holistically from the beginning – aligning siting, allowing, transmission planning and power technique early within the growth cycle,” she stated.

Shifting Workloads

Cahill stated information facilities should additionally play an energetic function by leveraging demand response, on-site era, and dynamically shifting workloads to cut back peak utility load stress and help grid resilience.

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“This sort of built-in collaboration is crucial to make sure digital infrastructure progress doesn’t outpace the power methods that help it,” Cahill stated.

Alexander Harrowell, principal analyst of superior computing at Omdia, informed DCN that with most of the largest hyperscale and AI-driven information facilities deliberate for Northern California, PG&E kinds a “essential” a part of the equation.

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“If the principally hyperscale funding plans occur, they’ll ineluctably want substantial electrical energy,” he stated.

This stems from the facility calls for of contemporary AI {hardware}: 1.4 kW GPUs, 500W CPUs, and more and more power-hungry high-density networking gear.

“As long as AI methods are certain by reminiscence bandwidth in inference, we’ll want chips with very giant excessive bandwidth reminiscence ratios to help that, and the excessive bandwidth reminiscence is the actual driver of energy consumption,” Harrowell stated.

It might assist if it had been potential to “make AI compute-bound once more” by way of elementary improvements in mannequin design or a totally completely different chip structure, the analyst stated.

Grid Stability Challenges

Harrowell stated a key problem for grid operators is that AI workloads create significantly unstable electrical demand patterns.

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“Grid engineers like giant, heavy spinning equipment as a buyer as a result of its inertia stabilizes the system, computer systems doing AI work are inclined to hop between near most energy and far much less in a short time, and in lockstep,” Harrowell stated.

On the finish of every cross by way of the transformer, all of the GPUs in a cluster have to sync the brand new weights and activations, which suggests all-to-all community operations. Energy draw spikes and crashes happen concurrently throughout clusters, straining each the DC energy distribution and the grid exterior.

He notes that power effectivity has grow to be the first information heart efficiency metric, however the spiking load concern might be the nastiest within the brief time period and has options.

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“Each Nvidia and Google are pushing software program options that assist to even it out, and among the GPUs now have supercapacitors within the energy provide unit to this finish,” Harrowell stated.

Foundational Investments Required

Cahill explains that utility-level infrastructure investments are foundational to sustaining AI-driven information heart progress.

“As AI workloads surge, power availability and grid stability have gotten important constraints,” she stated.

With out strong upgrades in transmission, distribution and utility partnerships, even essentially the most superior amenities danger falling wanting operational and sustainability objectives.

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“These investments allow scalable energy supply, cooling innovation and modular enlargement – capabilities which can be important for unlocking the total potential of AI environments,” Cahill stated.

She stated for information facilities to proceed increasing to help the nation’s urge for food for AI, shut collaboration with utilities should be handled as a strategic precedence, not only a help operate. 

“The brand new demand forecasts that we’re seeing nationwide underscores the pressing have to steadiness fast progress with grid stability and regional power capability,” she stated. “Ageing infrastructure, lengthy interconnection queues and gear delays are already straining utilities.”

Therese Kerfoot, govt vp of technique at EdgeCore Digital Infrastructure, agreed that the investments underway are elementary to sustaining the expansion of California’s information heart business and, by extension, the tempo of innovation and technological development that retains the USA globally aggressive.

“PG&E understands the online constructive impression information facilities have on ratepayers, and we’re inspired by its efforts to strengthen system security and reliability whereas accommodating rising demand for renewable power,” she stated.

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She added that whereas information facilities fund the infrastructure instantly related to their load, there are broader system investments required to make sure reliability within the face of growing older transmission belongings, growing climate-related stresses, and the operational complexity of integrating giant quantities of renewable era.

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Contents
Shifting WorkloadsFoundational Investments Required
TAGGED: 73B, CenterFocused, data, PGEs, spend, Transmission
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