Power analysis for data centers is the process of evaluating electrical infrastructure capacity, utility reliability, interconnection timelines and costs, redundancy options, and energy procurement strategies for current or planned data center facilities. As AI workloads drive power requirements to unprecedented levels, power analysis has become the most critical factor in data center site selection and development feasibility.
A comprehensive power analysis for data centers includes: available utility capacity at the nearest substation, transmission and distribution infrastructure assessment, interconnection timeline and cost estimates, utility rate structures and tariff analysis, power purchase agreement (PPA) options, on-site generation capabilities (backup and prime power), renewable energy availability and integration options, and long-term power demand forecasting.
Power availability is the single greatest constraint on data center development today. In many markets, available power capacity has been fully allocated, with new utility capacity requiring 3-5 years of infrastructure buildout. AI has dramatically accelerated this power crunch — a single AI training cluster can consume as much power as a small town. Power analysis must identify not just current capacity but realistic timelines for capacity expansion.
Power represents 30-50% of ongoing data center operating costs and is often the largest capital expenditure in new development (utility interconnection, on-site electrical infrastructure). Power analysis directly impacts financial feasibility — the difference between $0.04/kWh and $0.08/kWh can determine whether a project achieves its target returns. AI-powered analysis tools can rapidly compare power economics across dozens of potential sites.
Data center site selection is the process of identifying and evaluating locations for new data center facilities based on power availability, fiber connectivity, water resources, zoning compatibility, natural disaster risk, labor markets, and tax incentive programs. With the explosion of AI compute demand, data center site selection has become one of the most competitive and time-sensitive activities in commercial real estate.
AI data center development refers to the full lifecycle of planning, designing, and constructing data center facilities optimized for artificial intelligence workloads. AI data centers have fundamentally different requirements than traditional facilities — higher power density per rack, more sophisticated cooling systems, and infrastructure designed for GPU clusters rather than conventional servers.
Data center due diligence is the specialized investigation process for evaluating potential data center sites and existing facilities. It goes beyond standard commercial real estate due diligence to include detailed analysis of power infrastructure, fiber connectivity, cooling resources, environmental constraints, and the regulatory landscape specific to mission-critical technology facilities.