Research methodology

Where every number comes from.

Authoritative public sources, the current directory dataset, and configured feeds — combined into probability-scored research on AI data center energy risk.

Source detectedProbability movedDesk reviewedBrief ready

Primary Data Sources

Government & Regulatory

  • • Department of Energy (DOE): National energy consumption data, data center electricity projections
  • • Lawrence Berkeley National Laboratory (LBNL): Data center energy research and forecasts
  • • FERC: Federal energy regulations, Order 2023 interconnection rules
  • • State PUCs: Utility tariffs, rate cases, data center-specific regulations
  • • EIA: Energy Information Administration statistics and pricing data

Grid Operators (ISOs/RTOs)

  • • PJM: Interconnection queue data, capacity auction results, congestion pricing
  • • ERCOT: Real-time grid conditions, resource adequacy reports
  • • CAISO: Renewable integration data, transmission constraints
  • • MISO, SPP, NYISO, ISO-NE: Regional grid data and queue status

Industry & Financial

  • • Corporate filings: 10-K/10-Q reports from public data center operators
  • • Earnings calls: Management commentary on energy costs and expansion plans
  • • M&A databases: Transaction data for infrastructure deals
  • • Permit filings: Construction permits and environmental assessments

Update Frequency

Configured Feed Cadence

  • • News and press releases
  • • M&A announcements
  • • Regulatory filing alerts
  • • GCS-backed feed updates when storage is connected

Source-Dependent Updates

  • • Interconnection queue changes
  • • Tariff modifications
  • • Permit applications
  • • Weather and climate data where connected

Weekly Analysis

  • • Queue progression analytics
  • • Regional trend reports
  • • Policy change summaries
  • • Market sentiment indicators

Monthly Deep Dives

  • • Comprehensive market reports
  • • Regulatory landscape updates
  • • Infrastructure development tracking
  • • ESG metrics compilation

Analytical Framework

Risk Scoring Methodology

Our proprietary risk scores combine multiple factors:

  • • Grid Risk (40%): Queue position, interconnection delays, capacity constraints
  • • Regulatory Risk (30%): Current tariffs, proposed changes, political climate
  • • Energy Cost Risk (20%): Price volatility, renewable availability, demand charges
  • • Environmental Risk (10%): Water stress, extreme weather probability, carbon intensity

Predictive Models

Models and rules can be calibrated against historical datasets to forecast:

  • • Interconnection approval timelines
  • • Energy price trajectories
  • • Regulatory change probability
  • • Infrastructure build-out patterns

Data Quality Assurance

Validation Process

  • Multi-source verification for critical data points
  • Automated anomaly detection
  • Expert review of outliers
  • Historical backtesting

Transparency Standards

  • Source attribution for all data
  • Confidence intervals provided
  • Model assumptions disclosed
  • Change logs maintained

Key Differentiators

1. Evidence-First Research: Outputs should preserve source attribution, confidence, and assumptions so analysts can verify before acting.

2. Unified View: Grid, regulatory, financial, and environmental sources can be reviewed in a single risk framework.

3. Forward-Looking Intelligence: Beyond historical data, our models predict future conditions that may impact your investments.

4. Actionable Briefs: Raw data is transformed into research briefs tied to your portfolio and investment strategy where client data is connected.