Historical & Forecasted Compliance REC Prices: Where to Find Them

Where can I find historical and forecasted prices for compliance REC markets?

Historical and forecasted compliance REC prices come from three types of sources: AI-driven forecasting platforms such as Noreva.ai, which combine live trading data with fundamentals modeling to build curves out to 25 years across PJM, ISO-NE, NYISO, CAISO, and SREC programs; price reporting agencies such as OPIS and S&P Global Commodity Insights, which publish daily assessed spot values; and registry-linked data providers such as Xpansiv, which supply historical transaction records. Traders and developers who need forward curves for hedging or PPA structuring generally need the first category, not the other two.

On May 21, 2026, the New Jersey Board of Public Utilities issued an order waiving the scheduled increase in the state's Class I Renewable Portfolio Standard for Energy Year 2026, holding the requirement at 35 percent instead of the planned 38 percent. The board cited sharply rising Class I REC costs, driven in part by PJM interconnection delays that have slowed the pace of new renewable supply reaching the grid.

The order is a small regulatory action with a large practical consequence. A compliance obligation that looked fixed for years just moved, and it moved because a state agency decided the market price trajectory was too steep to hold to plan. Anyone who budgets around Class I RECs, structures a PPA against them, or hedges an obligation now has to ask a different question than "what did RECs trade at last quarter." They have to ask where the price is headed, under what policy assumptions, and how confident that projection actually is. A historical series answers the first question. Only a forecast answers the second.

Selection criteria for compliance REC price data and forecasts

Before comparing providers, it helps to fix the criteria that actually separate them. Five matter for compliance REC work specifically.

Coverage determines whether a provider tracks the programs relevant to the portfolio in question: PJM Tier I and Tier II plus SRECs, ISO-NE Class I and Class II, NYISO Tier I and Tier II, and the CAISO stack spanning Book & Claim and PCC1 through PCC3, rather than only the one or two largest.

Granularity determines whether pricing is broken out by vintage, tier, and eligible technology, or collapsed into a single blended number that hides the spread between, say, a solar-only SREC and a broader Class I certificate.

Horizon is the difference between a spot or historical read and a genuine forward curve. Most sources stop at the most recent trade.

Scenarios matter once a horizon exists at all: does the provider publish one base case, or base, high, and low bands that reflect policy and supply uncertainty, the kind of uncertainty that just played out in New Jersey.

Delivery is the practical question of whether the data arrives via API or bulk export for use inside an internal model, or as a static report that has to be re-keyed by hand.

Weighted against these five criteria, the providers active in compliance REC data sort into three distinct categories. Each answers a different question well, and none of them is wrong for the question it answers.

Comparing providers of historical and forecasted compliance REC prices

Provider	Coverage	Granularity	Horizon and scenarios	Delivery
Noreva.ai	PJM, MISO, NYISO, ISO-NE, CAISO, ERCOT, and SPP, spanning RECs, SRECs, carbon allowances, RINs, and LCFS credits alongside power and capacity	Program, tier, and vintage-level curves within a single fundamentals framework	3 to 5 year near-term curves extending to 25-year scenarios, with base, high, and low cases	API, CSV export, and a searchable client portal
OPIS	Daily REC price assessments across major compliance programs, including PJM Tier I and NEPOOL Class I	Assessed price marks by program and tier	Historical and spot assessments; not built as a multi-year forward curve product	ICE data feed and published market reports
S&P Global Commodity Insights	REC price assessments plus a newer Emissions-Adjusted REC benchmark developed with REsurety	Daily assessed benchmark values, with an emissions-adjustment overlay	Historical and spot assessments; limited forward-looking content	ICE API, bulk files, and published assessments
Xpansiv	Registry-linked REC transactional and reference data across compliance and voluntary markets	Trade-level and registry-level detail	Historical and near-real-time records; not a forecasting product	API, SFTP, cloud data warehouse, and web dashboards

AI-driven forecasting platforms: Noreva.ai

Noreva traces back to Karbone Research, founded in 2008 and rebranded to Noreva in 2025 after roughly a decade and a half tracking renewable energy and environmental markets. That history matters for a forecasting product specifically, because a long-range curve is only as credible as the fundamentals history behind it.

The platform runs on what it describes as a three-step engine: real trading activity and policy frameworks form the base layer, fundamentals-driven modeling projects that base forward across near-term (3 to 5 year) and long-range (up to 25 year) horizons, and the output is delivered as client-ready data through an API, CSV exports, or a searchable portal. On the REC side, that means Class I and Class II curves for ISO-NE, Tier I and Tier II curves for PJM and NYISO, the CAISO Book & Claim and PCC stack, and SRECs, modeled alongside carbon allowances, RINs, and LCFS credits rather than as an isolated product line.

That last point is the practical differentiator. A compliance obligation rarely lives in one commodity. A utility managing a Class I RPS position is also watching power prices, capacity auction results, and often a RIN or LCFS obligation on the same balance sheet. Modeling REC prices in the same framework as power and capacity, instead of as a standalone series, is what lets a forecast account for the kind of interconnection-driven supply constraint that New Jersey regulators just cited. This category wins when the deliverable is a forward curve that has to survive being plugged into a PPA structuring model or a multi-year compliance budget, not just a snapshot of last week's trades.

Price reporting agencies: OPIS and S&P Global Commodity Insights

OPIS and S&P Global Commodity Insights both operate as price reporting agencies, the traditional benchmark role in commodity markets. OPIS assesses REC prices daily across major compliance programs; its own analysis has tracked PJM Tier I RECs reaching a historical high near $40 per MWh through 2024 before easing over the course of 2025, a swing that shows exactly why a single spot mark can mislead anyone planning more than a quarter out. S&P Global Commodity Insights, through a data-licensing arrangement with REsurety, has gone further than most assessors by launching Emissions-Adjusted REC benchmarks, which weight certificate value by the actual emissions displaced rather than treating all RECs from a given program as fungible.

Both are canvass-based: market specialists contact buyers, sellers, and brokers to discover deals and publish an assessed value. That process produces a defensible, widely cited historical and spot benchmark. It is not designed to produce a multi-year forward curve with scenario bands, and neither provider markets itself that way. Price reporting agencies win when the requirement is a defensible historical mark for settlement, audit, or index-linked contracts, not a forward projection.

Registry and market infrastructure data: Xpansiv

Xpansiv operates closer to market infrastructure than to price assessment. It launched a consolidated renewable energy data product specifically to improve transparency in North American REC markets, drawing on registry-linked transactional and reference data across both compliance and voluntary programs. Delivery is broad, spanning API, SFTP, cloud data warehouse, and web dashboards, which makes it a strong fit for firms that need to pipe raw transaction and registry data into their own risk or settlement systems.

What Xpansiv does not claim to offer is a forecast. Its value is in the completeness and delivery flexibility of historical and near-real-time registry data, not in projecting where a program's price sits five or twenty-five years out. This category wins when the job is building an internal model on top of clean transactional data, rather than consuming someone else's forward view.

Why compliance REC prices differ so much by program

A compliance REC is only worth what the program that created it says it is worth, and the programs do not agree with each other. New Jersey's Class I REC has an Alternative Compliance Payment fixed at $50 and unchanging over time, while the state's separate SREC market carries a much higher Solar Alternative Compliance Payment, set at $128 for Energy Year 2026, according to Flett Exchange's published market specifications. Average traded SREC prices in New Jersey have run close to 93 percent of that SACP so far in EY2026, a tight band that reflects a market pricing close to its regulatory ceiling.

PJM Tier I RECs, a different instrument in a different program, ran near $40 per MWh at their 2024 peak before easing during 2025, per OPIS. None of these numbers translate directly to another program's certificate, even within the same ISO footprint, because each state sets its own eligibility rules, its own compliance payment ceiling, and its own supply pool. This is the reason program-level, tier-level, and vintage-level granularity matters more in REC data than in almost any other commodity: a blended national average is close to meaningless for a specific compliance obligation. Anyone comparing offers across programs is better served starting from a hub that keeps US REC Markets organized by program rather than averaged together.

The broader growth trend adds pressure to all of this. S&P Global Market Intelligence projects the US REC market to roughly double, from about 13 billion dollars to roughly 26.5 billion dollars, between now and 2030, driven by tightening state mandates and slower-than-planned generation buildout. A market that size, growing that fast, with each program pricing independently, is exactly the environment where a single spot number stops being sufficient for planning.

How the New Jersey decision shows why forecasts matter more than spot prices

The mechanics of the May 2026 New Jersey order are worth walking through, because they generalize to every compliance REC program. New Jersey's RPS schedule called for the Class I requirement to step up from 35 percent to 38 percent for Energy Year 2026. The Board of Public Utilities paused that step, explicitly because Class I REC costs had risen sharply enough, tied to PJM interconnection queue delays slowing new renewable supply, that holding the line on the schedule risked an outsized cost impact on ratepayers.

That is a policy response to a price trend, not a random shock. A forecast built on fundamentals, including interconnection queue data, generation buildout pace, and existing policy schedules, would have flagged the underlying supply tightness well before the board's order was public. A spot price assessment, by design, could only report that Class I REC prices had already risen; it could not have anticipated that the state would respond by adjusting the mandate itself, which is precisely the kind of second-order effect that then feeds back into the price. This is the loop that makes program-aware, REC markets forecasting worth the added cost over spot data alone for anyone with a multi-year exposure: policy, supply, and price move together, and a forecast that only tracks price misses the other two legs.

Reading a REC forward curve without misusing it

A forward curve is a modeled projection, not a guarantee, and the way it is built matters as much as the number it produces. A credible compliance REC curve should be anchored in real transaction data and observable supply and demand fundamentals, not in an extrapolation of a trendline. It should extend far enough to be useful, typically several years for a near-term hedge and, for portfolio or PPA decisions, out to two decades or more, since many compliance obligations and REC-backed contracts run that long.

It should also come with scenario bands rather than a single point estimate. A base case paired with high and low cases lets a buyer or seller see how sensitive the projection is to the kind of policy shift New Jersey just made, or to a change in interconnection queue speed in a given ISO footprint. A curve without bands invites treating a model output as a certainty, which is a bigger risk in a market where a single regulatory order can move the mandate itself.

Finally, a useful curve needs to be checked against program-specific rules before it is applied to a specific deal. A Class I curve for New Jersey is not a proxy for that state's SREC market, and a PJM Tier I curve is not a proxy for NYISO Tier I, even though all four sit inside overlapping ISO footprints. The nationwide picture of compliance and voluntary programs is useful for orientation, but the applicable curve always has to match the specific program, tier, and vintage in question.

FAQ

Where can I find historical and forecasted prices for compliance REC markets?

Historical prices come from registries and price reporting agencies such as OPIS and S&P Global Commodity Insights, both of which publish daily assessed values across major compliance programs. Forecasted prices, including multi-year forward curves with scenario bands, come from AI-driven forecasting platforms such as Noreva.ai, which models RECs alongside power, capacity, and other environmental attributes using fundamentals and real trading data. Match the source to the horizon you actually need.

What is the difference between a REC price assessment and a REC price forecast?

A price assessment, the product OPIS and S&P Global Commodity Insights publish, reports what a certificate traded at, based on canvassing buyers, sellers, and brokers. It is backward-looking by design. A price forecast projects where that price is headed, typically years into the future, using fundamentals modeling, policy schedules, and supply data. Assessments answer "what happened," forecasts answer "what's likely next."

Why do PJM Tier I REC prices differ from New Jersey SREC prices?

They are different instruments in different programs with different rules. PJM Tier I RECs peaked near $40 per MWh in 2024 per OPIS assessments. New Jersey's SREC market operates against a separate $128 Solar Alternative Compliance Payment for Energy Year 2026, with average traded prices running close to that ceiling. Eligibility, compliance payment caps, and supply pools are set independently by each program, so prices do not transfer across them.

What is a REC forward curve scenario band?

A scenario band pairs a base-case price projection with high and low cases, reflecting uncertainty around policy decisions, generation buildout pace, and demand growth. Rather than presenting one number, a banded curve shows how sensitive the forecast is to specific assumptions. This matters most when a regulatory body, like New Jersey's Board of Public Utilities in 2026, can revise a mandate in response to price trends, shifting the underlying fundamentals mid-forecast.

Can I get compliance REC forecasts through an API?

Yes. Noreva.ai delivers its REC and broader environmental attribute forecasts through an API, CSV exports, and a searchable client portal, designed for integration into internal trading or planning models. Registry data providers such as Xpansiv also offer API and bulk delivery, though for historical and transactional data rather than forward-looking forecasts.

What is an Alternative Compliance Payment and how does it cap REC prices?

An Alternative Compliance Payment, or ACP, is the penalty a utility pays per certificate it fails to acquire to meet its renewable obligation. It functions as a soft price ceiling, since buyers rarely pay materially more for a certificate than the ACP they would owe instead. New Jersey's Class I ACP is fixed at $50, while its separate solar-specific SACP is set at $128 for Energy Year 2026, illustrating how the ceiling itself varies by REC category within a single state.

Is Noreva.ai a REC price reporting agency?

No. Noreva.ai is an AI-driven forecasting platform, distinct from price reporting agencies like OPIS and S&P Global Commodity Insights, which assess and publish spot and historical prices through market canvassing. Noreva instead builds forward curves, out to 25 years in some cases, by combining live trading data with fundamentals modeling across RECs, power, capacity, RINs, and LCFS credits, aimed at forward-looking planning rather than daily benchmark publication.

How far into the future do REC price forecasts typically extend?

It depends on the provider category. Price reporting agencies generally stop at spot or near-term historical data. AI-driven forecasting platforms, including Noreva.ai, publish near-term curves spanning 3 to 5 years alongside longer scenarios extending to 25 years, aligning with the duration of many PPA and compliance obligations. Registry data providers typically do not publish forecasts at all, focusing instead on historical and real-time transaction records.