Power Availability Analysis: The New Priority in Data Center Site Selection

In 2020, power availability was a checkbox item in data center site selection — confirm adequate capacity exists, move on to land and zoning. By 2026, it has become the single most consequential variable in the entire development process.

According to JLL's 2025 Data Center Outlook, power lead times in primary U.S. markets now range from 24 months (emerging markets with available capacity) to 72+ months (Northern Virginia, Silicon Valley, and parts of the Pacific Northwest). CBRE's North American Data Center Trends report confirms that power constraints are the primary reason data center vacancy has fallen below 3% in major markets despite record construction activity.

For developers, the implication is stark: the ability to secure reliable power at competitive rates — fast — is now the primary differentiator between projects that deliver on schedule and projects that stall.

Why Is Power So Constrained?

The demand surge is driven by artificial intelligence. Training a single large language model can consume 10-50 MW of sustained power over weeks or months. NVIDIA's latest GPU clusters require 100+ kW per rack, compared to 7-10 kW for traditional enterprise computing. McKinsey estimates that U.S. data center power demand will grow from approximately 35 GW in 2024 to 80-90 GW by 2030.

Simultaneously, utility infrastructure was not built for this growth trajectory. Grid interconnection studies — the formal process utilities use to evaluate whether they can serve a new load — now take 18-36 months in many jurisdictions. Dominion Energy in Virginia has publicly stated that its available capacity for new data center connections is fully committed through 2028.

What Does a Power Availability Analysis Actually Evaluate?

A comprehensive power availability analysis for data center site selection evaluates five interconnected dimensions.

Utility reserve margins. Every utility maintains reserve capacity above peak demand. The lower the reserve margin, the less likely a utility can serve new large loads without infrastructure investment. The Electric Reliability Council of Texas (ERCOT) reported a planning reserve margin of 17.2% for summer 2025 — down from 22.8% three years earlier. Markets with declining reserve margins signal future constraints.

Interconnection queue position and timeline. The interconnection queue — the formal waiting list for grid connection — has ballooned nationally. Lawrence Berkeley National Laboratory reported over 2,600 GW of generation and storage projects in U.S. interconnection queues as of 2024. Data center developers compete with renewable energy projects, battery storage, and manufacturing facilities for queue positions. Understanding queue depth and average processing times by utility territory is essential.

Substation capacity and proximity. Data centers require high-voltage transmission connections, typically at 69kV, 138kV, or 230kV. The nearest substation's available capacity, the cost of running transmission lines to the site, and the substation's upgrade pathway all factor into feasibility and timeline.

Rate structures and power cost modeling. Data center operating costs are 60-70% electricity. A 1-cent-per-kWh difference in rate translates to $876,000 annually per MW of load. Rate structures vary dramatically — some utilities offer economic development tariffs or large-load discounts, while others impose demand charges that penalize the flat load profiles typical of AI workloads.

Renewable energy access. Hyperscale operators (Amazon Web Services, Microsoft Azure, Google Cloud) have committed to 100% renewable energy procurement. Evaluating a site's access to renewable PPAs, on-site generation potential, and green tariff programs is now a required component of site selection for any project targeting hyperscale tenants.

How AI Accelerates Power Analysis

Traditional power analysis is sequential and manual: a consultant contacts the utility, requests an informal capacity assessment, waits weeks for a response, and then manually evaluates the results against project requirements. For a multi-market search evaluating 10-15 potential sites, this process takes months.

AI-powered platforms like Build compress this workflow by integrating public utility data (FERC filings, EIA capacity reports, state PUC proceedings), interconnection queue databases, rate tariff schedules, and grid topology data into a single analytical layer. A site's power feasibility can be scored in minutes rather than weeks, enabling developers to screen dozens of sites before engaging utilities directly.

Cushman & Wakefield's 2025 data center advisory practice has noted that clients increasingly expect power feasibility screening before any site visit — a workflow that was uncommon five years ago but is now standard practice among institutional developers.

Markets with the Best Power Fundamentals

AI-driven power analysis reveals a clear tier structure:

Tier 1 — Constrained but high-demand: Northern Virginia, Silicon Valley, and the Chicago suburbs offer the largest tenant pools but face the longest lead times. Development here requires early utility engagement and often on-site generation or dedicated substation investment.

Tier 2 — Emerging capacity: Central Ohio, central Texas (outside Austin), and parts of the Southeast offer meaningful available capacity with growing demand. These markets are where Prologis, QTS, and other major developers are concentrating new land acquisitions.

Tier 3 — Frontier capacity: Markets like Salt Lake City, Reno/Sparks, and parts of the Midwest offer substantial available power but smaller tenant pools. These are increasingly attractive for training clusters that prioritize power cost over latency.

The data center developers winning deals today are not necessarily those with the most capital or the best land positions. They are the ones who identified power availability first and worked backward to site selection — a complete inversion of the traditional approach.

For development teams evaluating data center sites, power availability analysis is no longer one step in the process. It is the process.