The T² Decision Stack: A Field Guide to the New Compute Order

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Disclaimer:

This article provides methodological frameworks and decision-making tools for energy infrastructure evaluation and project execution. Example calculations are based on reasonable assumptions and industry-typical parameters, designed to illustrate framework logic rather than serve as investment advice for specific projects. Actual applications require adjustment of parameters based on project-specific conditions.

MERIT™ evaluation framework provides more precise project ratings and is available through professional consulting.

Summary

The field guide translates energy-compute theory into an actionable methodology for decision-makers. It defines how site selection, storage deployment, and contract design together determine the true cost, resilience, and sovereignty of large-scale compute infrastructure. The playbook replaces traditional ROI models with a ten-dimensional T² evaluation framework that quantifies location quality across grid access, policy stability, flexibility, transparency, and community acceptance—revealing risks that simple energy-price comparisons overlook.

Beyond evaluation, it demonstrates how energy storage transforms from a cost center into a sovereignty engine, improving both project returns and systemic flexibility. Subsequent sections show how poor PPA design can erase those gains, detailing clause-level strategies to control inflation, volume, and termination risk.

It teaches investors, policymakers, and operators how to turn incomplete spreadsheets into full-stack decisions—bridging economics, engineering, and governance in the era of the new compute order.

Opening: The Hidden Cost of Incomplete Evaluation

A cautionary tale in site selection

Consider a typical scenario that plays out across energy infrastructure projects: Two candidate locations for a 100MW data center, both appearing attractive on paper.

Location A (traditional favorite):

• Electricity price: $35/MWh — lowest in region
• Renewable energy mix: 85% — excellent ESG profile
• Tax incentives: 10-year full exemption — compelling economics
• Traditional ROI model shows: $15M annual savings

Location B (traditional runner-up):

• Electricity price: $46/MWh — 31% more expensive
• Renewable energy mix: 78%
• Tax incentives: Standard rates only
• Appears significantly costlier

Any competent CFO would select Location A. The spreadsheet is clear: lower energy costs, better green credentials, superior tax treatment.

The fatal blind spot: load flexibility

What the traditional evaluation missed was a critical operational dimension — the grid's ability to accommodate variable loads without penalty. This isn't about peak capacity; it's about dispatch flexibility, congestion management, and the real-time balancing mechanisms that determine operational costs beyond the energy commodity price.

When we apply a comprehensive evaluation framework that captures this dimension:

The hidden cost emerges:

Location A's poor flexibility score translates into operational reality:

• Imbalance volume (grid cannot accommodate variations): ~8% of total load
• Penalty rate (regional typical): $8/MWh
• Annual hidden cost: 100MW × 8,760h × 90% load factor × 8% imbalance × $8/MWh = $5.0M per year

This single overlooked factor consumes 83% of the tax savings that made Location A attractive.

Location B's calculation:

• Imbalance volume: ~2%
• Penalty rate: $5/MWh
• Annual hidden cost: $0.8M per year

20-year Total Cost of Ownership:

• Location A: $720M (cheap energy) + $60M (hidden costs) = $780M
• Location B: $850M (expensive energy) + $10M (hidden costs) = $860M

The supposedly "expensive" location is only 10% more costly when all factors are considered — and carries significantly lower risk (higher scores in regulatory stability and flexibility).

This is not bad luck. This is what happens when evaluation frameworks are incomplete.

The difference between $780M and $860M may seem manageable. But consider the compounding effect:

• If Location A faces policy reversal (high subsidy dependency, unstable regulatory environment)
• If grid upgrade costs materialize (low initial capacity score)
• If PPA counterparty defaults (inadequate risk assessment)

The "savings" evaporate, replaced by crisis management and stranded costs.

Who Should Read This — And Where to Start

This playbook is structured for three distinct audiences, each with different entry points:

If you are a policymaker: → Start with Part 1 (understand how enterprises evaluate your jurisdiction) + Part 4 (recognize systemic risks). Your question: "How can we make our region attractive for large-scale energy infrastructure investment?" Our answer: It's not just about low electricity prices or generous tax breaks. It's about comprehensive T² sovereignty — the full spectrum of factors that determine project viability and risk.

If you are a corporate executive: → Follow the complete path: Part 5 (execution roadmap) → Part 2 (storage strategy) → Part 4 (risk management). Your question: "We need to deploy 500MW of compute capacity in 18 months. Where do we start?" Our answer: Start with Phase 1 evaluation using the frameworks in this playbook, then progress systematically through design, contracting, and execution.

If you are an investment manager: → Focus on Part 1 (asset screening) + Part 2 (storage returns) + Part 3 (contract structures). Your question: "How do we identify infrastructure arbitrage opportunities and evaluate asset quality?" Our answer: Look beyond surface-level metrics. The highest returns often come from jurisdictions with improving T² trajectories, not just those with currently high scores.