Grid Intelligence
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Underwrite a power project on what the market actually paid.

Grid Intelligence helps developers, IPPs, utilities and infrastructure investors screen projects, quantify nodal risk and value offtake using measured ISO settlement data.

Built for acquisition diligence, greenfield siting, PPA structuring and portfolio risk review.

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01 Find

Find projects worth underwriting.

Screen projects across curtailment, congestion, basis risk, capture price, interconnection risk, market revenue and REC value. Reweight the ranking live for the objective being underwritten.

Scoring uses measured market data where available. Modelled assumptions are labelled wherever they appear.

02 Underwrite

Move from a candidate to an investment case.

Build P10, P50 and P90 returns with capex, fixed and variable opex, tax credits, capacity factor, price assumptions and project-specific risk.

Assumptions stay visible and adjustable rather than baked into a single number.
What this answers What is the project worth, and which assumptions drive the downside?

03 Structure

Structure the contract around the risks that move value.

Value physical PPAs, VPPAs and Alberta CfDs with capture price, generation shape, basis and curtailment carried through the economics.

Physical PPA and VPPA valuation.
Alberta contract-for-differences, settled against the province-wide pool price.
What this answers Which contract structure survives the shape and basis risk this project actually carries?

04 Quantify grid risk

See where a project's realised price separates from the hub.

Analyse day-ahead and real-time prices by hub, zone and settlement point. Identify basis exposure, negative-price hours, congestion and capture-rate risk before capital is committed.

Nodal and hub basis, by settlement point.
Spark-spread economics for dispatchable assets, against realised power and gas history rather than a flat heat-rate assumption.
Why this matters A project can show an attractive annual average price while capturing a discount during the hours it actually generates.

05 Value flexibility

Value flexibility at the node.

Model charge and discharge schedules against real hourly prices, quantify curtailment absorbed, and estimate storage value under location-specific conditions.

Dispatch is optimised against the measured day-ahead curve. Revenue estimates derived from that dispatch are labelled as estimates.

06 Stress the system

Stress the system before the project reaches operation.

Test renewable output, thermal availability, load, congestion and curtailment across an ERCOT network model built from real substation locations and settlement points.

Optimal power flow across the network graph.
Curtailment under adjustable system conditions.

Locational prices

Where price separates, and by how much.

Binding corridors

Which transmission paths constrain first.

Curtailment and scarcity

Where output is lost and where load sheds.

System cost

Total dispatch cost under each scenario.

Network results are model output, not market settlements, and are labelled as such in the platform. Transmission relief and capacity expansion studies run on the same model.

07 Assess demand growth

Underwrite against where demand is going.

Map operating and pipeline data-centre load, EV growth, generation headroom and queue depth to understand future pressure on local power markets.

Data-centre load set against generation headroom and renewable queue depth, by zone.
The same ranking engine applied to Alberta's pool-price market.
Historical data, published operator forecasts and modelled scenario output are distinguished throughout. No forward price is presented as a prediction.

08 Methodology

Built on measured data.

Not a forecast vendor's estimates. Hourly settlement prices, generation, dispatch, load and interconnection queues, loaded from each operator's own published feeds and reconciled against them.

4markets — ERCOT, CAISO, PJM, Alberta
600+ GWactive interconnection capacity tracked
Every requestin the ERCOT, CAISO and PJM queues
ERCOTCAISO PJMAESO EIANREL
Every dataset is reconciled against its source before it reaches the platform — row counts, known reference values and daylight-saving transitions are checked on load. Where a number is modelled rather than measured, the interface says so.

Markets

ERCOTTexas · nodal
CAISOCalifornia · nodal
PJMMid-Atlantic · nodal
AESOAlberta · single pool price
Alberta settles one province-wide pool price and publishes no nodal prices, so any locational price shown for Alberta is model output, not a market settlement.

Pricing

Per user, billed monthly.

Every plan includes the full price, generation, load and interconnection-queue history for all four markets. The difference is the modelling layer on top.

Basic

Starting at $500 / month
Single user
  • ERCOT, CAISO, PJM and Alberta price history
  • Nodal, hub and zonal DA/RT prices
  • Congestion, basis and negative-price analysis
  • Generation mix, zonal load and degree days
  • Interconnection queue and project screening
  • PPA valuation and capture-rate analysis
  • CSV export
  • Network modelling engine
  • Scenario and stress testing
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Most complete

Pro

Starting at $1,500 / month
Per user
  • Everything in Basic
  • ERCOT network model and OPF
  • Curtailment and congestion simulation
  • Transmission relief and capacity expansion studies
  • Battery dispatch and arbitrage valuation
  • Heat rate and spark spread options
  • Data centre and load growth stress testing
  • Scenario comparison and export
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Enterprise

Let's talk
Pricing based on markets, seats and deployment requirements
  • Everything in Pro
  • Team seats and shared workspaces
  • Your own forward curves and assumptions
  • API access
  • Additional markets on request
  • Onboarding and support
Talk to us
The platform is live and in active development. We are onboarding a small number of teams at a time so each one gets direct support during setup.

Data sources

Modelled outputs are labelled as such throughout the platform.