Everything you need to know about the Compute Heat Rate™, Royal Energy Analytics, and what we're building together.
AI data centers are about to reshape U.S. wholesale electricity markets in ways that no one is pricing in. The Compute Heat Rate framework is the first and only methodology that quantifies why, by how much, and where.
In equilibrium, wholesale prices settle at the Cost of New Entry (CONE). In persistent disequilibrium (the base case for AI demand), prices migrate toward the CHR.
A genuinely novel contribution to energy market analysis. No published precedent exists. The CHR does for demand-side price tolerance what the gas heat rate does for supply-side generation cost.
Gross revenue per MWh of electricity consumed. From API pricing, cloud compute rates, or enterprise contract values. Ranges from $1,850 (commodity) to $74,000 (frontier inference).
GPU amortization, facility, cooling, networking, maintenance. $3,800 to $5,200/MWh depending on workload tier and infrastructure requirements.
Minimum profit margin operators require. Baseline: 30%. Below this, the operator curtails, relocates, or renegotiates. The "walk-away" threshold.
| Workload Type | Revenue/MWh | CHR Ceiling | vs. Gas HR | Source |
|---|---|---|---|---|
| Frontier Inference (Opus/GPT-5) | $74,000 | $53,650 | ~1,070x | Empirical |
| Mid-Tier Inference (Sonnet/GPT-4.1) | $14,800 | $8,120 | ~162x | Empirical |
| Enterprise Agentic AI | $15,000 | $8,080 | ~162x | Uncertain |
| Enterprise Contracted | $5,900 | $1,270 | ~25x | Modeled |
| Commodity Inference | $1,850 | ~$800* | ~16x | Modeled |
| Blended Average (Q1 2026) | $12,500 | $6,350 | ~127x | Modeled |
*Effective CHR after portfolio cross-subsidization. All data from public sources: NVIDIA documentation, MLPerf, AWS/GCP, Anthropic/OpenAI/Google API pricing, Cushman & Wakefield, JLL, hyperscaler SEC filings.
From published metric to market infrastructure. Each layer depends on the ones below it. No competitor can leapfrog. Total addressable market at maturity: $34B+.
The public reference rate. SSRN paper, computeheatrate.com, quarterly publication. Establishes the metric as industry standard. The Sharpe ratio model: own the name.
Executing NowNear-term revenue engine. CFO threat briefings, exposure analysis, PPA mandates, geographic arbitrage. The Energy Decision Engine lives here.
Executing NowLicensable intelligence engine. Customers plug in proprietary data, get calibrated CHRPS projections. Aggregate data clause creates compounding network effect.
Live on Replit / Needs CapitalDerivatives: CHR Caps, Basis Swaps, Protection Contracts. Generators as natural sell-side counterparties. Spark spread analogue.
Blueprint CompleteProtection contracts, structured savings, index ETFs. B2B2C distribution through retail energy providers, banks, insurance companies. $34.4B TAM.
Blueprint CompleteThis is the most critical section. The IP architecture is clean, documented, and legally structured. Understanding who owns what, and how attribution works, is foundational to everything.
Owns all core IP: CHR formula, CHRPS methodology, CHRPIE platform, aggregate data architecture. Publishes the reference rate. Retains personal authorship across all layers. Wyoming LLC is the exclusive commercial vehicle. Every revenue stream traces back to IP ownership at the center.
Hans currently works in energy advisory at a major multinational. The employer receives a free license to use CHR/CHRPS methodology in client work, in exchange for written IP ownership acknowledgment. The employer amplifies Hans's thought leadership with proper attribution. The employer is a channel, not an owner. The employer does not currently know about REA LLC.
Any employer "thought leadership" that references CHR must be appropriately attributed as authored and independent research by Hans Royal specifically, citing the SSRN paper (Royal, 2026) or other published work. The employer should not publish ANYTHING that reads as though the underlying research or thesis itself is their intellectual property.
Why this matters (the protective framing): The CHR research has NOT been vetted, sanctioned, or officially approved by Hans's employer. It represents independent analytical work by Hans Royal in his personal capacity. By properly attributing it as independent research, the employer is protecting itself from misrepresenting an unsanctioned analytical thesis as an official company position. This is good corporate governance, not adversarial.
Hans's manager plays a key role here. The attribution instruction must come from management authority, not Hans's request. This creates the appearance of editorial governance rather than personal IP protection. Eight senior leaders at the employer have already unpromptedly attributed CHR as Hans's independent research in writing.
Any employer publication referencing CHR should include a disclaimer such as: "The Compute Heat Rate (CHR) framework represents independent research by Hans Royal and does not constitute an official company position, forecast, or recommendation. Citation: Royal, H. (2026). The Compute Heat Rate. SSRN Working Paper."
Additional context for inner circle only: Hans's employer does not know about Royal Energy Analytics LLC at this stage. The attribution framework exists independently of the LLC; it is simply correct academic and professional practice. Hans published the research personally; therefore it is attributed personally. The LLC becomes relevant in future commercial conversations, not in the attribution conversation.
Hans's publications must always precede any employer marketing to maintain the attribution chain. This is inviolable and well-documented.
CHR papers, computeheatrate.com, CHRPS methodology, CHRPIE platform: all branded Hans Royal. Never employer-branded. Employer may reference with proper attribution only.
With external parties: share the thesis, the market problem. Never share CHRPS formula, financial instrument designs, or CHRPIE internals until NDA is signed.
Published language stays descriptive: "AI workloads have measurably higher electricity price tolerance." Not provocative. Protects everyone involved.
Employer may write sector analysis referencing CHR (Royal, 2026) as external research. It must NEVER publish anything implying the CHR itself is company research or IP.
Hans's manager instructs any marketing/comms team on proper attribution. This is an editorial governance call from management, not Hans's personal request.
CHRPIE is a live, AI-native price intelligence platform running on Replit today. Seven modules, five energy hubs, Anthropic Claude API integration for natural language scenario building, and a 23-step guided demo journey. This is Layer 3 of the ecosystem: the licensable SaaS product.
Merit order simulation with DC load overlay. Duration curve analysis (8,760 hours). Peaker economics with dynamic cost modeling. Interactive penetration slider shows real-time price formation.
CONE-to-CHR scenario modeling. 10-year forward paths across three scenarios (Consensus, CHR Reference, CHR Conviction). Price divergence quantification by hub.
10,000-simulation Monte Carlo engine. Probability-weighted price outcomes. CHRPS-driven rightward shift visualization. CONE floor and ceiling reference lines.
Pipeline tracking by development stage (operational, under construction, permitted, announced, rumored). Hub-level demand forecasts with attrition rates.
Regional scoring with tier classification (Low, Moderate, Elevated, Critical). CFO-ready briefing generation with copy-to-clipboard. Advisory recommendations by tier.
Penetration forecast curves across three scenarios. Marginal Price Threshold crossing predictions. Decision Window callout with quarters-to-MPT calculation.
Natural language scenario builder: type "What happens if 5 GW of data centers are built in Virginia by 2028?" and Claude parses it into parameter values, sliders animate. Dynamic narrative generation across all modules.
This is the Bloomberg model. Bloomberg Terminal is valuable because every bank uses it. CHRPIE becomes more valuable as more customers contribute aggregate data. Each licensee adds proprietary intelligence that improves projections for all licensees.
Public data + commercial feeds + client intel
Verify, cross-reference, assign confidence scores
Recalculate CHRPS, demand forecasts, price paths
Push updated intelligence to all subscribers
Compare predictions to actual market outcomes
Client engagement generates new intel, back to step 1
Natural Language Scenario Builder: Claude parses plain English into parameter adjustments. Dynamic Narrative Generation: AI-generated contextual insights in all modules, updating in real-time.
Forward Curve Critique Engine: Upload any provider's forward curve; CHRPIE identifies where it diverges from CHR-informed projections. Briefing Generator: One-click CFO-ready reports.
Hub Intelligence Monitoring: Automated alerts when conditions change. Stress Testing: AI-driven scenario stress. LMP Anomaly Detection: Flag settlement points showing CHR signals.
CHRPIE is REA LLC property. Any employer-facing advisory tools are built separately, on employer infrastructure. CHRPIE feeds price intelligence into downstream tools as a third-party data source. Clean, licensable, separable.
Pure price prediction and intelligence platform. AI-native with Claude API. No chatbot UI; embedded intelligence via aiEngine.ts service layer. Licensable to energy advisory firms, utilities, generators, and financial institutions.
Built separately at Hans's employer on employer tools. Consumes CHRPIE price outputs as input. Client-facing advisory execution tool.
Traditional timeline: 24 to 36 months. Our timeline: 90-day sprint. Human gates are the only irreducible constraints. Everything else moves at machine speed.
SSRN paper submitted (Abstract ID 6322318, in editorial review). 20+ IP timestamps established. REA LLC formed (Wyoming). Attorney engaged on IP protection strategy. computeheatrate.com live. Substack launched as primary publishing channel. "The 100x Problem" published. CHRPIE V2.1 running with 6 active modules and AI features. Eight senior leaders at employer have attributed CHR as Hans's independent research in writing. Inner circle NDAs executing. White House Ratepayer Protection Pledge validates the exact dynamic CHR measures.
First client briefings with CHR exposure analysis. "CHR vs. PUE" article positions CHR as the business metric alongside PUE as the building metric. SSRN goes live, triggering academic outreach and strategic partnership conversations. Career optionality crystallized with concrete terms on multiple paths. Inner Circle Portal launched at circle.computeheatrate.com.
CHRPIE commercial build begins (post-departure, clean IP). 10+ advisory mandates. Geographic arbitrage mandates generating revenue. Validation scorecard published comparing CHR projections against actual market movements. Equity pairs trade opened as capitalization strategy. Advisory revenue sprint.
"Compute Heat Rate" becomes industry term of art attributed to Hans Royal. Financial instruments referencing CHR. Consumer products distributed through retail energy providers, banks, and insurance companies. REA LLC is the authoritative source for AI-energy market intelligence. $34B+ total addressable market.
Nothing leaves the inner circle. No exceptions. The commercial architecture, the employer dynamics, the legal strategy, REA LLC: all protected.
Meetings, legal review, counterparty decisions are the only irreducible constraints. One ask per meeting. Let relationships develop at human speed.
Category ownership is the moat. There is a 6 to 18 month window before major financial data providers recognize this space. Every day counts.
Every external deliverable, publication, commercial engagement goes through Royal Energy Analytics. Clean, documentable, defensible.
The inner circle exists to make this better, not to agree. If you see a weakness, say it. Confirmation bias is the enemy.
Claude is the production engine. Lean back-end, high-velocity human sales team. No bloated headcount. This is a new kind of company.
Below is the complete intellectual architecture behind the CHR project. Click any card to expand and read the full context. These represent 27 intensive working sessions across 12 days, producing output equivalent to 24-36 months of traditional consulting engagement.
Everything below was produced in 12 calendar days. Not by a team of 20. By one person with Claude as a production engine. This is not a scheduling anomaly; it is a paradigm shift. The analytical and production capacity available to this project is functionally equivalent to 15-20 senior analysts working around the clock. The constraint has shifted entirely from production to decisions and access. Every document, model, analysis, presentation, and tool below was produced at machine speed. Human gates (meetings, legal review, counterparty decisions) are the only irreducible constraints. This mental model is essential for inner circle members. Drop scarcity thinking. Adopt abundance thinking. If you need an analysis, a brief, a model, a presentation, it exists within hours, not weeks. The question is never "can we produce this?" It is always "should we, and in what sequence?"
| Workstream | Traditional Timeline | Actual | Compression |
|---|---|---|---|
| Research Framework (V1-V3.1) | 6-9 months | 5 days | ~40x |
| Market Domination Plan | 3-4 months | 1 day | ~100x |
| Energy Decision Engine (V3-V4.2) | 6-10 months | 4 sessions | ~75x |
| CHRPIE Platform (7 modules, AI-native) | 6-12 months | 3 sessions | ~90x |
| Academic Paper (8 sections) | 6-12 months | 2 days | ~100x |
| Financial Instrument Strategy | 2-3 months | 1 session | ~60x |
| Consumer Product Brief | 2-3 months | 1 session | ~60x |
| LLC + EIN + IP Infrastructure | 2-4 weeks | Same day | ~10x |
The most important strategic document in the project. Demonstrates why the risk-reward calculus overwhelmingly favors action even for skeptics.
Formal working paper submitted March 1, 2026. Abstract ID 6322318. Awaiting editorial approval. The critical gate for downstream actions.
The most significant external validation event in CHR history. The executive branch of the U.S. government acknowledging the exact dynamic CHR measures.
22 Q&A pairs covering every major objection. The Four-Layer PPA Defense Framework. Pressure-tested against five bear cases.
Provider-by-provider methodology analysis of WoodMac, Hitachi/ABB, Horizons, S&P Global, Ascend. All have the same blind spot.
Four-layer market development model for CHR-referenced derivatives. Generator-first counterparty strategy. Spark spread analogue.
Alternative to traditional venture capital. Prove the thesis through an equity pairs trade, then raise from position of strength.
CHR occupies genuinely empty conceptual space. Related but non-competing frameworks: MCC (CREO), LCODE (MARA), PUE. Watch list for potential competitors.
Strategic relationship architecture: MCC + CHR complementary metrics. Rod Eckhardt warm intro to Jigar Shah (now at Multiplier). CREO as amplification platform.
The core transmission mechanism. Why per-unit costs declining while average prices rise is not a contradiction.
Why a $55 solar PPA is a positive expected value position with high confidence, even without the CHR thesis.
Publication sequence, LinkedIn strategy, conference targets, Substack deep dives. Three articles published, multiple in queue.