Tag: Carbon Accounting

Blog post: Is 24/7 or Emissions First right for you? It depends on what you are trying to achieve.

Lee Taylor
Lee Taylor, REsurety's CEO, discussions Emissions First for clean energy leaders
Lee Taylor, Co-Founder and CEO


Authored by Lee Taylor, Co-Founder and CEO, REsurety


Clean energy leaders today agree clearly on one thing: annual MWh-based accounting was a phenomenally successful driver of our industry’s past success, but it is insufficient to meet the needs of our industry’s future – and our planet’s future.1 However, those same clean energy leaders have different proposals for what should replace annual MWh-based accounting. From these proposals two approaches have emerged: Hourly Energy Matching (the methodology advocated for by 24/7 proponents) and Carbon Matching (the methodology advocated for by the Emissions First Partnership).

Hourly Energy Matching asserts that buyers of clean energy should match their consumption with clean energy generation in both time and location. Carbon Matching advocates that buyers of clean energy calculate the induced carbon emissions of their consumption and then subtract the avoided carbon emissions of their clean energy procurement, with the goal of pursuing strategies for both consumption and generation, independently, to get to an end result of zero as fast as possible. In the corporate community, Google has led the charge on Hourly Energy Matching whereas the Emissions First Partnership (including Akamai, Amazon, General Motors, HASI, Heineken, Intel, Meta, Rivian, Salesforce, and Workday) has advocated for Carbon Matching.2

There is a perception by some that these two camps are in direct conflict. In reality, Carbon Matching and Hourly Energy Matching share a common long-term goal: a carbon-free grid. However, Carbon Matching and Hourly Energy Matching are two different strategies to achieve that goal and should be considered alternative – not mutually exclusive – options, each of which is an improvement over the status quo.

Hourly Energy Matching is an attempt to approximate the physical sourcing of clean energy. Said another way, Hourly Energy Matching is effectively a proxy for behind-the-meter co-location and temporal matching of clean energy generation and energy consumption. It is an effort to get most of the benefits of co-location without giving up the benefits of grid interconnection. Done correctly (more on this below), this strategy provides a tool to attempt to physically consume carbon-free energy.3

By contrast, Carbon Matching is an attempt to minimize carbon emissions as fast as possible. The basic premise is: our climate doesn’t care when and where carbon is emitted, it all goes into the same atmosphere and drives climate change. So Carbon Matching focuses on driving dollars to the projects and strategies that decrease overall carbon emissions as fast as possible, whether or not that results in consumption and clean energy generation occurring in the same time and location. For example: siting new load in a clean grid while siting new renewable generation in a dirty grid achieves faster decarbonization than co-locating load and generation in either one location.

Regarding the “done correctly” point above, I do have one significant bone to pick with the messaging to date by the Hourly Energy Matching camp. In many real world applications, Hourly Energy Matching has a significant “deliverability problem” that has thus far been downplayed or outright ignored. Here’s the problem: using grid connected projects as a “proxy” for co-location is only defensible if there are no material transmission constraints between the location of your generation and the location of your consumption. Just as transmission constraints drive dramatic price differences within a region, they also drive large differences in the carbon intensity of electricity within the same grid at the same time.

Hourly Energy Matching advocates acknowledge this and so define “deliverability” as existing between any two locations on the grid between which there is no material congestion. But, as a result of the complex and rapidly changing congestion patterns of modern grids, that means that whether or not generation in one location is “deliverable” to load in another changes every 5 minutes in many markets and can cause locations that are just a few miles apart to become non-deliverable. That reality presents challenges to the ease of Hourly Energy Matching’s implementation, so advocates have thus far taken a “let’s not let the perfect be the enemy of the good” approach and suggest using unjustifiably large geographic boundaries such as balancing authorities or the DOE’s geographic regions as approximations of deliverability.

But calling something deliverable doesn’t make it so. For example, in renewables-rich Texas, out of the hundreds of operating wind farms only two would be considered deliverable to Houston if you used energy price differentials as an indicator of congestion – as many have proposed.4 And congestion is not just a Texas problem. In MISO in 2022, renewables were being curtailed 71% of the time as a result of local congestion.5 In summary: matching generation and consumption hourly while ignoring local transmission constraints is the definition of precision without accuracy – and Hourly Energy Matching advocates need to acknowledge this and ensure that the implementation of “deliverability” consistently avoids that outcome.6

In the end, as a buyer of power, you have a choice. Is your goal to attempt to physically consume local carbon free energy? And are you comfortable knowing that your dollars spent could very likely have abated carbon further and faster if deployed elsewhere? If so, then you should pursue an Hourly Energy Matching strategy.

Alternatively, is your goal to reduce overall carbon emissions as fast as possible? And are you comfortable with the fact that your choice may lead you to invest in projects that aren’t located in your backyard? If so, then you should pursue a Carbon Matching strategy.

Both strategies have their respective merits and it is important to note that they are not mutually exclusive. I can speak to this personally. I live in Massachusetts, which means I live in a house that gets (relatively) little sunshine and draws power from a (relatively) clean grid. Even so, I installed solar panels on my roof in order to source carbon-free energy for my own consumption. However, like many 24/7 strategies, my rooftop solar system is both expensive and exclusive. The implied cost of carbon underlying the RECs generated by my rooftop system translates to nearly $650 per metric ton of avoided carbon. And, residential solar isn’t a financial option for all homeowners and is no option at all for renters. While I still feel good about my decision to install solar, I recognize that this kind of behavior alone simply is not cost-effective nor scalable enough to stave off the worst effects of climate change. Given that, the majority of my time and effort go into our work at REsurety, where we provide the tools required to enable Carbon Matching throughout the clean energy ecosystem (from corporate procurement, to energy storage, to hydrogen development) – with the primary objectives of maximizing the speed with which we decarbonize the grid as a whole.

Have a question on this topic? We’re always happy to discuss so send us a note at [email protected].


1 For further reading or listening on this, see: Carbon Accounting Changes Could Lift Corporate Greenhouse-Gas Emissions, WSJ, May 2023. GHG accounting reform could change energy investment, The Interchange Podcast, July 2023. Going beyond megawatt hour matching, Climate Positive Podcast, July 2023.

2 The Emissions First Partnership states that it supports companies with hourly match goals, and its carbon matching approach can serve as a foundation for those goals (see EFP website).

3 I say “attempt” instead of “ensure” on purpose, because it’s not possible to trace electrons from generation to consumption across a grid. 24/7’s advocates agree with this: “We know from Kirchoff’s circuit laws that electricity generated in one spot cannot be directed to a specific user over the electricity grid. Once you put electricity on the grid there is no actual way to know ‘the energy from wind farm X is going to my data center Y.’” – Google’s Green PPAs

4 Many Hourly Energy Matching proponents have suggested that two locations could be considered “deliverable” if the Locational Marginal Price (“LMP”) at the generator location is within 10% of the (hourly-matched) LMP at the consumption location. Using trailing 2-year observed prices, only 2 wind farms in Texas have experienced LMP differentials of less than 10% to Houston Hub.

5 See Table 1 from MISO’s 2022 State of the Market report. Wind and solar were on the margin and as such set pricing in 68% and 3% of intervals, respectively.

6 For more detail on how local transmission can undermine or even reverse the carbon benefits of hourly matching, see REsurety’s white paper on this topic related to defining green hydrogen: Emissions Implications for Clean Hydrogen Accounting Methods.

White Paper: Carbon Confidence in Climate Finance, as published by HASI

“LME is an important tool in assessing individual projects because seemingly identical renewable energy projects can have drastically different impacts on avoided carbon emissions.”

White Paper: Carbon Confidence in Climate Finance, as published by HASI

CarbonCount is a decision tool that evaluates investments in U.S.-based renewable energy, energy efficiency, and climate resilience projects to determine how efficiently they reduce CO2 equivalent (CO2e) emissions per $1,000 of investment. CarbonCount produces a quantitative impact assessment for investments’ carbon avoidance by integrating forward-looking project assumptions, emissions factors, and capital investment.

This white paper explains why CarbonCount matters, why it’s being updated, the methodology behind it, and use cases. REsurety’s Locational Marginal Emissions (LME) data is also featured in the paper.

Learn more here, or download the full white paper below.

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White Paper: Making It Count

Updating Scope 2 accounting to drive the next phase of decarbonization

Authored by David Luke Oates, Senior Vice President of Power Markets Research, REsurety

Dr. Oates holds a Ph.D. in Engineering and Public Policy from Carnegie Mellon University and a Bachelor’s degree in Engineering Physics from Queen’s University, Canada.

Making it Count: Updating Scope 2 accounting to drive the next phase of decarbonization

EXCERPT: Corporations are increasingly focused on reducing their carbon footprints by decarbonizing the electric grid. While solar and wind energy development have rightly been a mainstay of these efforts, there is growing consensus that producing more clean energy alone isn’t enough. To maximize grid decarbonization, clean generation needs to occur at times and locations where its output displaces the highest-emitting resources. Consumption timing and location should be adjusted to minimize its carbon emissions via siting decisions, demand flexibility measures, and energy efficiency. And energy storage is needed to manage grid congestion and mismatches between clean supply and demand.

Effective carbon accounting frameworks can help coordinate these complex mitigation strategies by allocating emissions among the entities responsible for producing them. These accounting frameworks attempt to ensure that activities with more impact on actual emissions have more impact on carbon accounts. Given the large and increasing interest of investors, customers, regulators, and governments in corporate decarbonization initiatives, effective carbon accounting frameworks can encourage corporations to maximize their actual carbon reductions.

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The Enhancement and Standardization of Climate-Related Disclosures for Investors

Wind Energy

REsurety’s letter to the Securities and Exchange Commission Re: File No. S7-10-22, dated June 17, 2022

AN EXCERPT:

On behalf of REsurety, Inc., a leading analytics provider in the clean energy economy, we are writing in support of File No. S7-10-22: The Enhancement and Standardization of Climate-Related Disclosures for Investors. We also suggest two specific language refinements to improve the accuracy and transparency of Scope 2 emissions disclosures.

Anticipated Value of the Proposed Rule

For the last 10 years, REsurety has helped our clients understand the risks and value of buying and selling electricity from clean energy projects. Many of our clients develop renewable energy projects, have made voluntary public GHG reduction commitments, or own assets exposed to climate-related risk. The SEC’s proposal to require detailed climate-related disclosures has the potential to benefit our customers, as well as the public and the planet. By requiring disclosures from a large category of companies, the proposal protects investors from unintentional exposure to climate-related risk. By standardizing disclosure requirements and requiring attestation, the proposal can also help substantiate GHG reduction claims. In short, the proposed rule has the potential to increase efficiencies in capital markets, boost investor confidence and encourage companies to take effective climate action at scale.

Challenges with the GHG Protocol

While we strongly applaud the SEC’s aims, we are concerned about the pivotal role the GHG Protocol plays in the SEC’s proposal, particularly with respect to Scope 2 emissions disclosures. The proposed GHG emissions disclosure requirements are based “primarily on the GHG Protocol’s concept of scopes and related methodology”.1 The proposed rule cites the GHG Protocol Scope 2 Guidance as a methodological source for determining Scope 2 inventories.2

The GHG Protocol Scope 2 Guidance allows reporting entities to select from an extensive hierarchy of emissions factor data to calculate their footprints. Application of some of these emissions factors would result in footprints that differ materially from actual GHG emissions. For example, the current Scope 2 Guidance lists Renewable Energy Credits (RECs) as the highest-quality “emissions factor” data type but takes no position on where or when RECs are produced relative to their consumption. An entity consuming power in a coal-heavy grid could eliminate its Market-Based Scope 2 footprint by purchasing sufficient RECs from a very clean grid, even when such a purchase would have a negligible effect on actual GHG emissions.

By relying on average emissions factors, current Scope 2 guidance also risks sending signals to registrants that are at odds with the goal of reducing carbon emissions. Consider a registrant purchasing solar energy that mostly displaces coal generation, in a grid that also includes considerable baseload nuclear. Since the average emissions rate of this grid is much lower than the emissions rate of the displaced coal, the reduction in the registrant’s carbon footprint would not reflect the solar energy’s full carbon impact. As a result, the registrant may hesitate to contract for the solar energy in the first place, knowing that its actual carbon benefits could not be reported.

Read our full letter.

We love talking with anyone who shares our goals of more accurate carbon impact measurement and the tools to maximize that impact – so please contact us at [email protected] if you have any questions or want to connect and discuss.

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Footnotes:

[1] Proposed Rule, §I.D.2.

[2] Proposed Rule, §II.G.2.c (p. 195). The proposed rule also cites the EPA’s guidance on Indirect Emissions from Purchased Electricity, which is highly similar to the GHG Protocol Scope 2 guidance. See §II.G.1.b. (p. 160)


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Carbon Accounting with the Greenhouse Gas Protocols: Successes and Emerging Challenges

David Luke Oates
David Luke Oates, author of Carbon Accounting with the Greenhouse Gas Protocols: Successes and Emerging Challenges
David Luke Oates

By David Luke Oates, SVP of Power Markets Research, REsurety

The Greenhouse Gas Protocol is a foundational component of modern climate standards. It is incorporated into the Task Force on Climate-Related Financial Disclosures’ (TCFD) guidelines for voluntary climate disclosures1, as well as the Science-Based Targets Initiative’s (SBTi’s) recommendations for aligning corporate targets with climate goals.2 It has also largely been paralleled in the U.S. Security and Exchange Commission’s recent proposed rule on climate disclosures.3

The GHG Protocol has achieved considerable success in providing a common framework for voluntary disclosures. But it is now a fairly outdated standard, and its flaws are becoming more impactful and problematic. The GHG Protocol Corporate Standard was originally released in the early 2000s, with updated Scope 2 guidance released in 2015. The nearly seven years since that release have featured dramatic increases in corporate clean energy purchases and interest in accurate corporate climate disclosures.4 There is now growing interest in updating the GHG Protocol and addressing some of its shortcomings.

At REsurety, we spend much of our time helping buyers and sellers of clean electricity to manage their financial risks and achieve their decarbonization goals. We are particularly interested in ensuring that Scope 2 accounting is as effective as possible. Today, the GHG Protocol Scope 2 Guidance has two major flaws: 1) it does not ensure that all actual carbon emissions are accounted for across entities and 2) it often doesn’t create the right incentives for entities interested in decarbonization. 

On the first item, the GHG Protocol’s Market-Based method for Scope 2 accounting allows reporting entities to apply REC purchases to cover their consumption at an emissions rate of 0 tons/MWh. It also allows entities to account for their grid consumption by applying a simple-average emissions rate. This average emissions rate reflects the same clean energy claimed through REC retirements, effectively double-counting the impact of clean energy and contributing to under-reporting of emissions.5 While this double-counting may have been of little concern a decade ago, the volume of today’s clean energy purchases make it a more serious problem.

On the second item, by relying on average emissions rates with low temporal and spatial granularity, current Scope 2 guidance risks send the wrong signals to entities interested in decarbonization. Consider an entity purchasing solar energy that mostly displaces coal generation, in a grid that also includes considerable baseload nuclear. Since the average emissions rate of this grid is much lower than the emissions rate of the displaced coal, the reduction in the entity’s carbon footprint would not reflect the solar energy’s full carbon impact. In general, the activities achieving the greatest amount of decarbonization are not fully rewarded under the current GHG Protocol, creating a misalignment of incentives. We think there is an opportunity to fix both of these problems.

Governments and corporate entities have recently made ambitious climate mitigation commitments. Truly delivering on these commitments will require a modernized set of carbon accounting rules to align incentives and avoid double-counting. We believe that a revised Scope 2 carbon accounting framework based on granular marginal emissions data can help address some of the shortcomings we mentioned above. We look forward to sharing more details on potential solutions to these challenges in the months to come.

In the interim, we love talking with anyone who shares our goals of more accurate carbon impact measurement and the tools to maximize that impact – so please contact us at [email protected] if you have any questions or want to connect and discuss.

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Footnotes:

[1] See p. 21, Implementing the Recommendations of the Task Force on Climate-related Financial Disclosures, October 2021

[2] See p.3, SBTi Criteria and Recommendations, Version 5.0, October 2021

[3] See §I.D.2. (p. 40), The Enhancement and Standardization of Climate-Related Disclosures for Investors, SEC Proposed Rule, File No. S7-10-22

[4] U.S. corporate clean energy purchases grew from 1.2 GW/year in 2014 to over 11 GW/year in 2021. See Clean Energy Buyers Association Deal Tracker

[5] While this double-counting could theoretically be corrected by applying the residual mix emissions rate to all parties’ grid consumption, this approach is not feasible in many jurisdictions. Calculating the residual mix emissions rate depends on visibility into all private contracts for RECs between counterparties, something that individual reporting entities aren’t able to provide. In jurisdictions (such as the U.S.) where residual mix emissions rates are not available, current GHG Protocol guidance is to apply the average emissions rate to grid purchases. See GHG Protocol Scope 2 Guidance §6.11.4


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High-resolution carbon emissions data now available for PJM Mid-Atlantic power grid

Adam Reeve

New data empowers wind, solar and energy storage projects and load centers to accurately calculate their carbon impact

BOSTON, March 17, 2022 – REsurety announced today the expansion of its breakthrough Locational Marginal Emissions (LME) carbon data tool to the PJM power grid in the U.S. Mid-Atlantic region. Previously available only in Texas’s ERCOT grid, the expansion of the data set into PJM results in a dramatic increase in the number of locations for which the high-resolution emissions data is available, with now nearly 15,000 distinct locations served. It’s also the first time that REsurety will be releasing data at the five-minute level, which is particularly valuable for understanding the impact of storage on the PJM grid. The company intends to scale LMEs to the rest of the United States and internationally.

Adam Reeve, senior vice president of software, REsurety

The Locational Marginal Emissions data set measures marginal carbon emissions rates at each node on the grid, enabling insight to the impact of each specific clean energy project site or load location. This capability allows project developers, investors, and corporations to accurately understand the carbon impact of their activities.

“This data is critical for efficiently decarbonizing the grid, as we can now see the impact of specific projects and activities on system-wide emissions,” said Adam Reeve, Senior Vice President of Software, REsurety. “By understanding the carbon emissions impact of specific technologies at specific locations, we can ensure that clean energy strategies are more precisely targeted to where they can have the biggest impact.”

Reeve continued, “We are especially excited about what this means for the value proposition of energy storage. While many people intuitively understand that storage is a necessary technology for decarbonization, historically the industry has lacked the tools to measure its impact accurately.

“But with this level of nodal granularity, we can measure the impact of specific storage projects on the grid during both charging and discharging. We can see, for example, how some projects charge when the marginal generator is clean, and then discharge when the marginal generator is dirty, avoiding a significant amount of carbon emissions in the process.”

“We can also see how other storage projects, unfortunately, can actually increase system emissions. It’s not a one-size-fits-all technology. Where you site energy storage and how you schedule its dispatch can mean the difference between significant increases or decreases in carbon emissions. This data empowers investors and storage operators to measure and maximize their carbon reduction impact.”

Recognizing the value of marginal carbon emissions data, PJM started publishing marginal emissions rates at load node locations starting in January, 2021. REsurety’s data set builds on that initial step in a number ways, including by extending the data set to cover generator nodes and correcting anomalous data points (or outliers) with values consistent with the actual topology of the transmission grid. REsurety also leverages its own models to extend the nodal data back several years, enabling analysis of longer-term market trends.

The resulting LME data set takes into account real-time grid congestion, actual emissions rates by each generator unit, and the physical power flows throughout the system. The data set is available via an API and being integrated into REsurety’s other software tools.

“LMEs can be used to measure the carbon impact of any sustainability strategy – whether it is focusing on local procurement, 24/7 matching, or maximizing your carbon emissions impact,” said Reeve. “We’re excited for this high-resolution emissions data to enable better measurement and decision-making across the board.”

REsurety’s Locational Marginal Emissions data is currently available in ERCOT and PJM, and will be available for other markets later this year. To learn how your company can better measure and maximize the carbon impact of your clean energy initiatives, contact us at [email protected].

About REsurety
REsurety is the leading analytics company empowering the clean energy economy. Operating at the intersection of weather, power markets, and financial modeling, we enable the industry’s decision-makers to thrive through best-in-class value and risk intelligence, and the tools to act on it. For more information, visit www.resurety.com or follow REsurety on LinkedIn.

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