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Data centers can put pressure on electricity systems and water supplies, but a facility’s presence does not automatically raise every neighbor’s bill or deplete a local water source. The outcome depends on the utility tariff, who pays for new infrastructure, the cooling design, the facility’s water source, the power mix, and conditions imposed by local authorities.
National forecasts describe a possible scale of growth, not the impact of one proposed site. To assess a project, residents need its utility filings, water and sewer information, permitting record, and enforceable commitments.
Why the same data center can have very different local effects
A data center is a large, concentrated load on the electric grid. Servers run continuously, while cooling, power conditioning, pumps, lighting, and backup systems add to the facility’s demand. The grid must supply that load at the times it occurs, and the utility may need new substations, transmission, distribution equipment, generation capacity, or storage.
Those investments do not automatically become a charge on nearby households. Utilities recover costs under tariffs and other service agreements. A large customer may pay dedicated construction costs, demand charges, minimum bills, or other contributions. Alternatively, regulators may approve broader cost sharing. The details determine whether other customers face upward pressure, little change, or—under some circumstances—benefit from a larger customer helping spread fixed system costs.
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Water impacts follow a similar location-specific pattern. A facility may withdraw or consume water directly for cooling, while the power plants supplying its electricity can consume water indirectly. The amounts depend on cooling technology, weather, operating load, water source, generation technology, and local water conditions.
What the latest U.S. electricity forecasts actually say
Rapid growth, with a wide range of outcomes
A June 2026 update from Lawrence Berkeley National Laboratory estimates that data centers could account for 11.8% of total U.S. electricity use in 2030. Its modeled scenarios range from 9.5% to 15.3%. These are projections, not measurements of future consumption. The spread reflects uncertainty about computing demand, server deployment, efficiency, and how quickly planned facilities are built and connected.
The same update reports a 14% increase in U.S. data-center electricity use between 2023 and 2024. It attributes the growth primarily to more accelerated servers and rising computing demand. A national percentage cannot be converted directly into the expected load or price effect in a particular town: regional grids have different generation mixes, transmission constraints, tariffs, and queues for new connections.
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Historical context, and why the dates matter
| Source and period | Figure | How to interpret it |
|---|---|---|
| Lawrence Berkeley National Laboratory update, June 2026 | 11.8% of total U.S. electricity use estimated for 2030; scenarios of 9.5%–15.3% | Forward-looking scenarios, not observed 2030 consumption |
| Lawrence Berkeley National Laboratory update, 2023–2024 | 14% increase in U.S. data-center electricity use | Reported year-over-year growth for that period |
| U.S. Department of Energy release, December 2024 | 176 TWh in 2023, about 4.4% of U.S. electricity | Historical estimate |
| U.S. Department of Energy release, December 2024 | 325–580 TWh projected for 2028, approximately 6.7%–12% | An older forecast; the later 2026 update is the newer outlook |
The 2028 range should not be presented as a measured result or as a substitute for the newer 2030 scenarios. It remains useful only as historical context for how quickly estimates have changed.
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Will a data center raise my electric bill?
The mechanism is cost allocation, not proximity
A nearby facility can contribute to higher costs for other customers if the utility builds generation or delivery infrastructure and does not assign enough of those costs to the large customer. The risk is especially significant when construction is based on an optimistic load forecast and the expected demand never arrives, arrives late, or leaves behind underused assets. Customers can also face pressure when demand grows faster than available supply and the utility must procure expensive capacity.
Berkeley Lab’s policy analysis identifies four central design questions: fair allocation of system costs, protection against stranded investments, resource adequacy when demand exceeds supply, and risk sharing for newer energy technologies. These are regulatory questions; the existence of a data center alone does not establish that residential rates will rise.
What to look for in a utility filing
- Applicable tariff: Identify the rate schedule for large loads and any special service agreement. Check whether the customer pays a minimum bill, demand charges, connection fees, or dedicated facilities.
- Construction responsibility: Determine who pays for substations, transmission upgrades, distribution work, generation, storage, and interconnection studies.
- Load commitment: Look for binding minimum demand, take-or-pay provisions, deposits, exit charges, or other protections if the facility is delayed or cancelled.
- Forecast assumptions: Compare the proposed load with the utility’s approved forecast and the expected energization schedule. A maximum nameplate load is not the same as average demand.
- Rate-case treatment: Check whether regulators classify any investment as serving the individual customer or the broader system, and whether the allocation is subject to later review.
- Supply adequacy: Review how the utility plans to meet the added demand and whether new generation or transmission costs are assigned to the facility, all customers, or a defined customer class.
These documents can show who bears financial risk. They still may not predict the exact bill effect, because fuel costs, wholesale prices, weather, and other system changes also influence rates.
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How data centers use water directly
Cooling design controls the facility’s water demand
Servers convert most of the electricity they consume into heat. A cooling system must move that heat out of the building. Designs that evaporate water can provide effective cooling but consume water through evaporation and blowdown. Other designs reduce on-site water use by relying more on air movement, closed loops, heat exchangers, or mechanical refrigeration; those choices can increase electricity demand, capital cost, or both.
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There is no meaningful single “data-center water use” number without its context. A project’s disclosure should distinguish:
- Withdrawal: water taken from a utility, river, aquifer, or other source.
- Consumption: water not returned to the immediate source, often because it evaporates or is incorporated into waste streams.
- Average versus peak demand: a daily or annual average can conceal the maximum demand during hot weather or a high-computing period.
- Source and quality: potable, recycled, surface, or groundwater supplies have different costs and constraints.
- Local system context: the same volume can have very different consequences in a water-abundant system and a stressed basin.
Indirect water use from electricity generation
The power used by a data center can create an additional water footprint at power plants. Generation technologies and fuels use water in different ways, and the effect depends on where the electricity is produced rather than simply where the data center is located. A comparison that adds direct facility use to power-sector use should state the boundary, source data, and accounting method. Otherwise, direct and indirect figures can be mistaken for the same impact.
Why water and energy efficiency can conflict
Reducing on-site water use is not always equivalent to reducing total environmental impact. The February 2026 California policy report from UC Berkeley notes that more water-efficient cooling strategies usually use more energy. That extra electricity can increase the facility’s indirect water use at power plants, depending on the generation mix, and can add to grid demand.
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- reduces potable-water demand by using recycled or non-potable supplies;
- limits peak withdrawals during hot or drought-sensitive periods;
- uses a cooling system appropriate to the local climate and water stress;
- reduces electricity consumption enough to offset any indirect water consequences; and
- includes monitoring and reporting that can be audited after operation begins.
What California’s water-governance findings show
The February 2026 California report finds that existing reporting requirements do not provide a clear view of data-center water use, sources, efficiency, or impacts. The problem is not necessarily that every facility lacks data; it is that information is inconsistent and difficult to compare across projects.
The report identifies three practical levers: siting facilities in lower-water-stress locations, selecting the cooling system carefully, and using recycled water where feasible. It also emphasizes that local communities bear many development impacts and that local governments decide whether projects may be built and under what conditions.
California-specific findings should not be treated as a national measurement. Other states and water systems may use different disclosure rules, permitting procedures, or definitions of consumption. For any location, the relevant water provider and basin authorities must be consulted.
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Local effects extend beyond the utility meter and the cooling tower. The available evidence does not establish a national net-benefit or net-harm conclusion for jobs, tax revenue, housing, noise, traffic, or property values. Those outcomes require project-specific records and enforceable commitments.
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| Issue | What residents should verify |
|---|---|
| Electric infrastructure | Substation, transmission, distribution, and generation upgrades; construction schedule; and who pays under the tariff or service agreement |
| Water and sewer capacity | Provider capacity, source, peak demand, drought restrictions, wastewater handling, and the difference between withdrawals and consumption |
| Land use and permitting | Zoning decision, environmental review, public-hearing record, conditions of approval, and monitoring requirements |
| Taxes and incentives | Tax agreements, exemptions, public infrastructure contributions, duration, and performance conditions |
| Operations | Backup generation, fuel storage, noise controls, construction impacts, emergency planning, and complaint procedures |
| Transparency | Whether operating water, energy, and compliance data will be reported publicly and in a comparable format |
Listing an issue does not prove that a project will cause it. It identifies the evidence needed before a community can make a defensible judgment.
A step-by-step method for investigating a proposed site
- Obtain the planning file. Read the application, site plan, environmental or permitting documents, zoning staff report, and public comments.
- Identify the water provider and sources. Ask whether supply is potable, recycled, surface, or groundwater; request capacity analyses and peak-demand estimates.
- Request the cooling specification. Seek the expected withdrawal and consumption, annual and peak figures, blowdown or wastewater plans, and the technology’s energy implications.
- Find the electric filing. Review the tariff, interconnection study, service agreement, minimum billing, demand charges, deposits, and construction-cost allocation.
- Compare forecast and commitment. Distinguish maximum potential load from contracted or scheduled load, and check what happens if the project is delayed or downsized.
- Check enforceability. Separate statements in marketing materials from permit conditions, contracts, reporting duties, penalties, and other obligations that regulators can enforce.
- Track cumulative effects. Ask whether other large loads are planned in the same utility territory or water system and whether analyses account for them together.
- Follow operations after approval. Compare actual reported water and electricity use with approved limits and investigate unresolved complaints through the responsible agencies.
How to compare two proposals or locations
Use the same boundaries and definitions for every project. A comparison that uses annual water consumption for one facility and peak withdrawal for another can produce a misleading ranking.
| Comparison axis | Questions to ask |
|---|---|
| Electric tariff and cost allocation | Are dedicated upgrades paid by the customer? Are minimum bills, demand charges, deposits, or exit protections included? |
| Grid risk | What load is firm, when will it arrive, and who bears the risk of stranded assets or inadequate supply? |
| Direct water | What are withdrawal, consumption, peak demand, source, cooling technology, and wastewater requirements? |
| Indirect water | What generation supplies the electricity, and what assumptions define the power-sector water footprint? |
| Local governance | Which permits apply, what conditions are enforceable, and will operating data be disclosed? |
| Community commitments | Are water reuse, infrastructure funding, backup-generation controls, mitigation, and reporting written into binding documents? |
Claims that deserve extra caution
- “The project will use a fixed amount of water every year” is incomplete without the source, weather assumptions, peak demand, and withdrawal-versus-consumption definition.
- “The facility will raise everyone’s electric bill” skips the tariff and cost-allocation analysis needed to establish who pays.
- “The facility will be carbon- or water-neutral” may rely on accounting boundaries that exclude indirect power-sector effects or future grid changes.
- “National data-center demand is X percent, so this town will need Y infrastructure” treats a scenario-based national estimate as a local load study.
- “The project will create a net economic benefit” requires documented tax terms, employment estimates, public costs, and local evidence; it cannot be inferred from the building’s size.
Making a defensible local judgment
The strongest analysis connects four records: the utility’s approved tariff and infrastructure plan, the water provider’s capacity and source information, the project’s cooling and operating commitments, and the local government’s permitting conditions. National electricity forecasts explain why these questions are becoming urgent, while California’s reporting findings illustrate why transparent, comparable local data matters.
A data center may bring a large customer and new investment, but it can also create financial and resource risks if costs, water demands, or underused infrastructure are shifted to the public. The answer for a particular community is found in the contracts, engineering assumptions, permits, and monitoring requirements—not in the facility’s name or national growth statistics.
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