The governing question is not what the tariff rate is. It is what the delivered cost of power is for a 100 MW, 500 MW, or 1 GW facility - and what contractual risk the utility imposes to deliver it. This page answers both. Markets are ranked. LLT severity is scored. Upcoming regulatory decisions are flagged. The map shows rates. This page shows decisions.
Breaking Jun 2026
Oregon Power Act: PGE files +29% data center rate hike
Portland General Electric has filed a 29% rate increase for data centers under Oregon's new Power Act, which creates a legally distinct DC customer class and requires the industry to cover the cost of new generation and transmission built to serve it. Residential customers get a 1.3% cut - confirming regulators' finding that DCs had been cross-subsidized by households. Hillsboro city council votes on a development moratorium Jun 9. PacifiCorp faces the same requirement by 2028, with OPUC initial ruling expected this summer. PGE Oregon LLT severity updated from 14 → 48. Market score revised from Tier 2 → Tier 3.
Source: The Oregonian, Jun 2026 · OPUC filing pending
▲ Top 5 Cheapest Markets
All-in at 85% LF · best available schedule
▼ Most Restrictive LLTs
Scored on take-or-pay, term, collateral, cost allocation
⚡ Regulatory Calendar
Upcoming decisions · latest: Oregon Power Act Jun 2026
Market Ranking · DC Site Selection Score
Composite score 0-100 across: all-in power cost (40%), LLT severity (25%), regulatory stability (20%), grid buildout (15%). Higher = better for data center operators. Click any row to open Tariff Tracker.
Methodology: Rate score inverted from ¢/kWh (lower rate = higher score). LLT severity from Risk Ledger protection scores. Regulatory stability from tension scores and recent rulings. Grid buildout from IRP filings and interconnection queue data. Scores are analytical estimates - verify independently before site selection decisions.
Estimated total annual power cost ($/yr) at 85% load factor for three facility sizes. Does not include capital costs, interconnection, or LLT collateral.
Facility size
Annual cost = all-in ¢/kWh × MW × 8,760 hrs × 0.85 LF. Does not include LLT minimum billing shortfall, collateral, or site-specific infrastructure charges. Indicative only - verify with utility.
Cost Stack Decomposition · How the Rate Is Built
For practitioners who evaluate utilities, a single ¢/kWh figure is insufficient. This shows what drives it: generation, transmission, distribution, demand charges amortized at load factor, and riders. Select a market to drill in.
Generation = base energy charge. Transmission = separate T charge or OATT adder where applicable. Distribution = D component or estimated split. Demand amortized = $/kW-mo × 12 ÷ (LF × 8,760) × 100. Riders = fuel cost recovery, environmental, and other mandatory adders. Sources: filed tariff PDFs, FERC Form 1, IRP filings.
Regulatory Pipeline · Upcoming Decisions
Forward-looking calendar of utility proceedings, rate cases, and LLT rulings expected through 2027. Each creates a binary risk event for DC developers in that territory.
Dates are best estimates from filed dockets, utility communications, and PUC scheduling orders. Regulatory proceedings routinely slip. Treat as signal direction, not a hard calendar. Track PUCO, NCUC, CPUC, and relevant PUC docket systems for current status.
Power markets intelligence · US Data Center Power Cost Map
Every data center deal is a power delivery deal.
The governing question: what is the all-in effective cost of grid power for a data center operator in each US utility territory - and what contractual restrictions does the utility impose to deliver it? This map answers the first question. The Tariff Tracker answers the second. The Risk Ledger answers both simultaneously.
Recent regulatory developments · Jun 2026: AEP Ohio DCT approved Jul 2025 (85% take-or-pay, 12-yr term) · Georgia PSC base rate freeze through 2028, 9,985 MW new gen certified Dec 2025 · Xcel Energy filed LLT Apr 2026: 100% new gen+tx cost allocation, ≥50 MW (PUC pending) · Duke Carolinas rate case Jan 2026 formalizing large-load tariff terms · PPL Electric $275M rate case settlement Mar 2026 includes DC tariff provisions · Wisconsin VLC tariff proposed: ≥500 MW full cost allocation - highest threshold in US.
Load factor85%
Color by
All-in rate ¢/kWh
2.5¢5¢7.5¢11¢+
Green = cheapest. Red = most expensive. Dark = not tracked.
Large-load tariff
Active / approved
Pending review
Proposed / filed
None enacted
Market type
Regulated IOU
ERCOT deregulated
PJM T&D only
Data confidence
⬤ Filed tariff PDF
◎ Regulatory filing
○ FERC Form 1 / inferred
Cheapest market
-
Most expensive
-
Rate gap
-
cheap → expensive
LLTs active / pending
12 / 6
of 60 markets tracked
All-in rate: base energy + demand ÷ (LF × 730 hrs) + riders. ERCOT: TDSP delivery (PUCT confirmed) + ERCOT 2024 RT avg $26/MWh + REP margin. Sources: filed utility tariff PDFs, PUCT, IUC annual report, ERCOT IMM. Cross-link to Deals Tracker for power risk by transaction.
Power markets intelligence · Tariff Tracker
US Data Center Tariff Tracker
60 utility service territories · Rate schedules · LLT status · Effective $/kWh model · Click utility to navigate · Click schedule row to expand.
Utilities
60
top DC markets
Fully modeled
2
VA · GA filed tariff
Filed tariff data
8
VA·GA·IA·OR·NV·WI·TX×2
Rate range
2.6-11¢
all-in best schedule
LLTs active
15
utilities · 23 states (EEI May 2026)
Cheapest market
IA/VA
MidAmerican · Dominion
Ratepayer protection & DC expectations
Risk Ledger
Two-sided analysis of every major US DC power market. Left: mechanisms utilities use to protect ratepayers. Right: what data centers actually get in return. The gap between the two columns is the market signal.
⚠ Utility protection mechanisms
Instruments utilities use to prevent stranded cost exposure when large-load customers reduce or exit. Scored by stringency - how much financial and operational risk is transferred to the data center operator. Higher = more protection for ratepayers, more risk for operators.
◎ Data center expectations
What operators typically receive in exchange: rate certainty, interconnection speed, renewable content, and operational flexibility. Scored 1-5. Higher = more favorable to the data center operator. Tension score = mismatch between protection stringency and DC-friendliness.
Sort by
Market / utility
⚠ Ratepayer protection mechanisms
◎ DC expectations delivered
Tension
Min billing %
Term (yr)
Collateral
Cost alloc
LF floor
DR req
Rate certainty
Interconnect
Renewable
Flexibility
Protection stringency: ○ none · ● low · ●● moderate · ●●● high · ●●●● severe. DC scores 1-5 (higher = better for operator). Tension = protection stringency minus DC score average. Sources: filed utility tariffs, PUCO/SCC/PSC orders, FERC dockets.
Electron Economics · Primary Research Analytics
Power Market Analytics
The structural finding: the US power market for data centers has bifurcated into two regimes - low-rate, low-protection markets (Iowa, Virginia, ERCOT) where utilities want the load, and high-protection, constrained markets (AEP Ohio, Wisconsin, California) where utilities are managing the load they already have. The LLT adoption wave is not uniform: it tracks exactly the utilities that reached capacity constraints first.
Cumulative count of large-load tariffs filed, approved, or proposed. Inflection tracks capacity constraint saturation in key ISO territories.
Sources: utility rate case filings, PUC orders, press releases. Pending and proposed counted from filing date, not approval. 2026 count reflects filings through Jun 2026.
Protection vs. DC-Friendliness Quadrant
Each bubble = one utility. X = DC-friendliness score (1-5). Y = protection stringency (0-4). Bubble area ∝ all-in rate. Color = tension level. Ideal for DC operators: bottom-right.
Scores from Risk Ledger primary research. Protection: average of 6 mechanisms (min billing, term, collateral, cost alloc, LF floor, DR). DC score: average of rate certainty, interconnect, renewable, flexibility.
Rate Component Decomposition · Selected Markets
Stacked bars showing base energy, demand amortized at 85% LF, and riders. Demand component is the primary driver of market differentiation.
Markets selected for analytical contrast: cheapest regulated, ERCOT, highest protection, and highest rate. Full dataset in Tariff Tracker.
Rate Sensitivity to Load Factor · Key Markets
How much does all-in rate change across 50-98% load factor? High demand-charge utilities (Georgia, Wisconsin) are most sensitive. Iowa and Virginia least sensitive.
Sensitivity = (all-in at 50% LF) − (all-in at 98% LF). Higher sensitivity = demand charge dominates. Lower sensitivity = energy charge dominates. Demand-heavy utilities penalize low-utilization operators most.
Market Regime Matrix
60 utility markets classified on two axes: rate competitiveness vs. LLT stringency. Quadrant placement indicates operator risk profile.
Rate tier: Low (<5¢), Mid (5-7.5¢), High (>7.5¢). LLT stringency: None / Low (no LLT or minimal), Moderate (pending/proposed), High (active, ≥85% min billing or full cost alloc). Quadrant = operator siting signal.
Energy vs Demand Decomposition · All 33 Markets
Stacked bars showing what fraction of each market's all-in rate comes from base energy (dark green), demand charges amortized at 85% LF (mid green), and riders (amber). The white % label shows demand share when it exceeds 50% — these markets punish low utilization hardest.
All 33 US markets. Sorted low → high all-in rate at 85% LF. Georgia Power and Oregon PGE are outliers: energy charge is trivially small but demand + riders dominate. Markets where demand > 50% of total are most sensitive to load factor variation.
Load Factor Penalty · Rate Swing 98% → 50% LF
How much does your all-in rate increase if load factor drops from 98% to 50%? Demand-heavy markets (Georgia, Wisconsin, Oregon) are severely punished. Iowa and Virginia are demand-light — rate barely moves.
Swing = all-in at 50% LF minus all-in at 98% LF. Markets with high demand charges ($/kW-mo) have large swings because demand amortization is inversely proportional to LF. A 500 MW DC underperforming at 50% LF pays an extra $40–90M/yr in demand-heavy markets.
LLT Severity Fingerprint · Component Breakdown
Each bar shows which of 6 protection mechanisms drives a utility's LLT severity score. Some markets are restrictive on one dimension (Wisconsin: demand charge), others on multiple (AEP Ohio: take-or-pay + term + collateral).
6 components: min billing % (dark red), contract term (amber), collateral requirement (orange), generation/tx cost allocation (dark), LF floor (brown), demand response (light green). Top 16 markets by severity score. Total = LLT Severity Index 0–100.
Every US market. X = all-in rate ¢/kWh. Y = LLT severity 0–100. Bubble size = market score (larger = better). Color = tension level. Bottom-left is ideal; top-right should be avoided.
Bubble size proportional to DC site selection score (0–100). Tension: green = low, amber = moderate, red = high, dark red = extreme. All tracked US markets. Iowa and Grant PUD anchor the bottom-left ideal zone. Wisconsin and AEP Ohio occupy the top-right danger zone.
Market Treemap · All 33 Markets by Score
Area = site selection score (larger = better). Color = tension level. Rate label shown inside each cell. A quick visual of the entire US DC power market landscape.
Cell area proportional to site selection composite score. Color: green = low tension (DC-friendly), amber = moderate, red = high, dark red = extreme. Rate shown in ¢/kWh at 85% LF. Grant PUD and Iowa dominate by area — highest scores, lowest tension.
Rate vs Protection Stringency · All 33 Markets
X = all-in rate ¢/kWh. Y = average protection stringency (0–4 from Risk Ledger). Color = LLT status. Bubble size = site selection score. Bottom-left quadrant = ideal (cheap + low protection).
Protection stringency = average of 6 Risk Ledger protection mechanism scores (0–4 each). All 33 US markets plotted. Labeled markets: notable anchors of each quadrant. LLT color: green = active, amber = pending, teal = proposed, grey = none.
Axes normalized to 0–1. Rate score: inverted ¢/kWh (higher = cheaper). LLT: inverted severity (higher = less punitive). Regulatory: 0–20 component of site selection score. Grid: 0–15. DC-friendliness: Risk Ledger DC expectations score. Iowa polygon anchors all five axes near maximum.
Power Cost Trajectory · 2023–2030
Projected all-in ¢/kWh for key markets based on filed rate cases, approved increases, and announced trajectories. Dashed = projected. Solid = confirmed.
Projections: Grant PUD +9.5%/yr (commission policy through 2036). Georgia Power base frozen 2028, FCR floats. AEP Ohio escalator from DCT. PGE Oregon Power Act +29% base + annual reassessment. Iowa MidAmerican flat (EAC adjusts). Sources: filed rate cases, commission orders, utility IRPs.
Cross-Subsidy Signal · Rate Shift at DC Tariff Adoption
When a utility adopts a DC-specific tariff, residential rates move in the opposite direction. The spread is the cross-subsidy that existed before the tariff. Wider bar = larger prior subsidy.
Operator Risk Exposure Matrix · Annual Power Cost by Market × Facility Size
Each cell = estimated annual power cost ($M/yr) at 85% load factor. Color intensity = cost magnitude. Use as a first-pass site selection filter — red cells are markets where power cost dominates the P&L.
Annual cost = all-in ¢/kWh × MW × 8,760 hrs × 0.85 LF. Does not include LLT minimum billing shortfall, collateral, or site-specific infrastructure. LLT collateral can add $30–150M upfront for 500 MW facility depending on market. All-in rates at 85% LF per main tracker data.
Open Rate Case & LLT Docket Gantt
Active regulatory proceedings affecting DC power cost. Each bar = filing date → expected ruling. Color = risk direction for DC operators.
Dates from filed dockets and commission scheduling orders. Regulatory proceedings routinely slip 3–6 months. "Expected" column = analyst estimate, not commission commitment. Track individual PUC docket systems for live updates.
Market Momentum · Regulatory Direction Score
Each market scored -5 (rapidly tightening) to +5 (actively DC-friendly) based on the last 18 months of regulatory activity. Arrow = direction of travel.
Momentum score = weighted sum of: new LLT filings (-), LLT approvals with punitive terms (-), rate freezes (+), economic development riders (+), no LLT despite DC growth (+), moratorium discussions (-). 18-month window Jan 2025 – Jun 2026.
Regulatory Signal Timeline · 2024-2026
Key utility regulatory actions affecting data center power cost and access. Color = direction of change for DC operators.
Sources: utility press releases, PUC orders, state legislative filings. Green = DC-favorable outcome. Red = DC-restrictive. Amber = neutral/pending. All filings primary research - no third-party data subscriptions.
Electron Economics · International Markets
International DC Power Markets
5 Tier 1 markets: Ireland, Netherlands, Sweden, UK, Singapore. All-in effective rates converted to US¢/kWh at current FX. Market structure, LLT status, and regulatory risk assessed on the same framework as US utilities.
The structural finding: European markets are 2–4× more expensive than the best US markets on absolute power cost. Sweden (SE1 north) is the only international market competitive with Virginia or Iowa. Singapore is expensive but constrained by island geography — there is no alternative. Ireland and the Netherlands are price-restricted and physically constrained. The UK is gas-linked and politically uncertain. For greenfield hyperscale economics, the US remains dominant.
FX rates used: EUR/USD 1.09 · GBP/USD 1.27 · SGD/USD 0.74 · SEK/USD 0.096 · Updated Jun 2026. All rates converted to US¢/kWh for comparability with US tracker.
International vs US Markets · All-in Rate Comparison
Same methodology as US tracker: all-in effective ¢/kWh at 85% load factor. International rates converted from local currency at Jun 2026 FX.
US rates from main tracker. International: best available large industrial or DC-specific rate where distinct. Ireland/NL/UK: wholesale + network + levies for large industrial customer. Sweden SE1: hydro-advantaged northern zone. Singapore: EMA regulated non-household tariff Q2 2026. Rates are indicative — exact large-load contracts are negotiated and confidential. FX: EUR/USD 1.09, GBP/USD 1.27, SGD/USD 0.74, SEK/USD 0.096.
International Regulatory Pipeline
Active proceedings and policy changes affecting DC power costs and access in Tier 1 international markets.
Electron Economics · Long-range Fundamentals Model
US Data Center Capacity Forecast to 2040
This is a first-principles model, not an extrapolation of analyst consensus. The forecast is built from underlying demand drivers: AI compute scaling laws, hardware efficiency trends, PUE trajectory, non-AI baseline load, grid supply constraints, and regulatory friction. The formula is fully disclosed. The weights are closed — they represent analytical judgement anchored to published hardware roadmaps, Epoch AI compute scaling data, and FERC 2025 load actuals. Scenario modifiers adjust weights multiplicatively. The 2040 range reflects genuine uncertainty, not false precision.
Open Formula — Calibrated Closed Weights (v3.1) · 7 backtest anchors: 4 pass ✓, 3 scope-explained △ (LBNL/Goldman include BTM enterprise; model tracks grid-connected). Scenarios: Base 412 GW · Accelerated 497 GW · Constrained 338 GW · High Efficiency 126 GW by 2040.
US DC Installed Capacity Forecast · 2020–2040 · Fundamentals Model
Four scenarios driven by compute growth, hardware efficiency, grid buildout rate, and LLT friction. Weights calibrated v3: FERC/LBNL/Goldman Sachs historical anchors + EE primary research (Substack: OpenAI Energy, Gas Turbines, Who Wears the Risk, Tariff Lottery). Shaded band = Accelerated (497 GW) to Constrained (338 GW) range. High Efficiency (126 GW) shows efficiency-driven demand reduction. Base = 412 GW. Grid binding from 2029.
High Efficiency scenario: models a Jevons-limited future where hardware efficiency gains outpace compute demand growth — the only scenario where the grid constraint fully relaxes before 2035. In this scenario, compute demand continues at base rates but 30% better hardware efficiency means ~70% less power growth — the 'soft landing' outcome. Result: ~126 GW by 2040, the lowest of all scenarios.
Forecast Decomposition · 2040 vs 2025
Waterfall showing each driver's contribution to the 2025→2040 change. AI compute demand (net of efficiency) is the dominant positive driver. PUE improvement partially offsets. LLT friction and grid ceiling are the binding constraints.
Decomposition uses base scenario weights. AI compute net of efficiency = gross compute growth minus hardware efficiency offset, with Jevons rebound applied. Grid constraint shown as the residual gap between unconstrained demand signal and grid ceiling.
Driver Trajectories · Gross Compute vs Efficiency vs Net Demand
All three indexed to 2025 = 1.0×. The gap between gross compute growth and hardware efficiency is the net demand multiplier. Jevons rebound prevents efficiency from fully closing the gap.
Gross compute grows faster than efficiency in all scenarios except High Efficiency. The Jevons rebound parameter determines how much of each year's efficiency gain is "spent" on running more compute rather than reducing power draw. Historical rebound in computing: ~0.6–0.7 (broadly consistent with Jevons 1865 original coal analysis).
Sensitivity Analysis · Impact on 2040 Forecast of ±Weight Variation
Each parameter varied ±15–30% independently, all others held at base. Width of bar = total GW swing on 2040 forecast. Shows which weights matter most — and therefore where the analytical disagreements about the future are highest-stakes.
AI compute growth rate is the dominant uncertainty — a ±20% change in the near-term growth rate produces the largest swing in 2040 output. Hardware efficiency and Jevons rebound are the second-tier uncertainties. LLT friction matters less at the national level than at the per-market level because regulatory friction redirects rather than destroys demand. PUE trajectory is the most predictable parameter — physical limits are well-understood. Demand signal at 2040: ~481 GW unconstrained; ~412 GW after LLT friction; grid delivers ~412 GW in base case.
Model Backtest · Fitted vs Historical Anchors 2014–2025
Calibrated model output vs independent external anchors. Grey band = LBNL 2024 plausible range. Orange dots = FERC/LBNL confirmed actuals. Model uses dual-rate historical CAGR: 7% (2014-18) → 18% (2018-23) → 24% (2023-25) reflecting observed acceleration phases.
Historical anchors: LBNL 2024 US DC Energy Usage Report (TWh→GW using utilization factors); FERC 2025 State of Markets (50 GW end-2025, 24% CAGR 2020-2025). Residual gap at 2014-2018: LBNL includes behind-the-meter enterprise load not captured in FERC grid-connection data. Post-2025 model fit vs Goldman Sachs: 65 GW (2027) vs ~76 GW operational estimate — difference is definitional: Goldman includes behind-the-meter enterprise (~15% of total) which our grid-connected model tracks separately via btm_bypass variable. Adding BTM estimate (~4 GW by 2027) gives ~69 GW vs Goldman ~76 GW (−9%). Grid becomes binding 2029+.
Electron Economics · Developer Intelligence
LLT Collateral Requirements
Upfront capital commitments, financial assurance requirements, and minimum billing structures across all tracked utilities. The collateral requirement is often larger than the rate differential — and belongs on the balance sheet, not in the operating model.
The $750M question: Dominion Virginia GS-5 requires $1.5M/MW upfront — $750M for a 500 MW facility at contract execution. Virginia also enacted a $0.011/kWh DC consumption tax effective Jul 1 2026 (~$41M/yr at 500 MW). ERCOT is not zero — SB6 financial security, site control, and interconnection cost obligations apply to ≥75 MW loads, with PUCT finalising rules. Iowa and the PNW PUDs require zero.
Facility size
Capital Impact at Selected MW · Upfront Collateral Requirement
Hard-dollar $/MW requirements only. Negotiated structures (Ameren, Evergy, AEP Ohio, Consumers MI) use 2-year minimum bill projections as collateral — actual exposure typically $50–200M+ for 250 MW facilities.
Sources: VA SCC final order Nov 25 2025 (GS-5 $1.5M/MW); Virginia budget act (DC tax $0.011/kWh Jul 1 2026); CPUC Advice 2018-E Apr 2026 (Xcel CO $600K/MW). Negotiated: Ameren/Evergy/Consumers = 2yr projected min bills. All figures at contract execution — pre-construction.
Collateral Matrix · Tracked Utilities
Full collateral, minimum billing, term, and exit fee structures. Capital impact at selected facility size — toggle above to recalculate.
Utility / Tariff
LLT
Collateral Type
$/MW
Capital Impact
Min Billing
Term
Notes
Oregon PGE (Power Act Jun 2026): no upfront cash — 100% distribution network upgrade costs at interconnection + 30-yr term for ≥220 MW. · Wisconsin We Energies: financial security terms TBD pending revised tariff; Oracle legal challenge Jul 2026. · ERCOT utilities: SB6 (Jun 2025) applies to ≥75 MW — not a traditional LLT but real capital obligation. PUCT approved centralized evaluation Jul 2026. FERC Jun 18 show-cause orders excluded ERCOT.