BLOG: Momentum builds for LME data as clean energy stakeholders focus on emissions reductions

Momentum is building around a smarter way to procure and invest in clean energy with the greatest decarbonization potential.


Gone are the days when a PPA would be signed based on price alone. Instead, today’s energy market participants are focused on understanding the entire impact of their procurement activity. One of the most critical metrics used by energy buyers in support of this is the amount of carbon emissions avoided by their specific project.


REsurety’s Locational Marginal Emissions tool, launched in July, helps buyers with this problem. Our tool measures the carbon emissions impact of each project at its particular node. At its launch, more than half a dozen sustainability leaders¹, including large energy buyers, investors, and advisors, had signed up to use the tool.

Nonprofits Align on Decarbonization Importance


The increasing focus on decarbonization is not just being driven by large, for-profit energy buyers or investors, however. 


This past July, RMI released a white paper that analyzed the strengths and weaknesses of hourly load-matching with renewable energy. Most notably, it recommended that while hourly load-matching strategies can be valuable in the long run, they must be balanced with a near-term focus on emissions impact.


It is a “science-based imperative to reduce emissions as fast as possible in the near term,” the paper says, and focusing on emissions impact is critical. While hourly matching strategies provide other important long-term benefits, such as supporting emerging technologies, those benefits must be balanced against the urgency of emissions reductions today.


On August 20, the World Resources Institute (WRI) published an issue brief advising energy buyers on best practices for procurement. “Some generators reduce emissions more effectively than others,” the brief says. In order to maximize the decarbonization impact, “buyers can factor emissions abatement potential directly into their procurement decisions and prioritization of projects.”

Electric Grid Operators Get On Board


The momentum behind decarbonization has also been visible in the form of engagement from market operators.


This past spring, M-RETs, a non-profit platform for tracking environmental attributes, announced plans to work with MISO, a system operator, along with Google and EnergyTag, on a program to enable the hourly tracking of RECs and the associated carbon emissions impact of each MWh of clean energy generation.


Most recently, PJM, another system operator, said they have plans to publish 5-minute marginal emissions rates for load nodes within its footprint. The grid operator’s move further demonstrates the momentum behind precise emissions data as being a key input into data-driven sustainability strategies.

Continuing the Momentum


Efficient decarbonization of the grid is an urgent need – that’s why we need accurate marginal carbon emissions data. At REsurety, we’re working to make LME data available everywhere, starting first with ERCOT, PJM and CAISO. We’ve also patented our technology so that we can be transparent about precisely how LMEs are calculated and what specific grid dynamics are considered to measure nodal emissions at the most granular level possible.


We’re thrilled that so many groups – large energy buyers and investors, non-profits, and grid operators alike – are rallying around the same idea, and have recognized that granular emissions data is a critical input into enabling an efficient energy transition. By calculating the carbon impact at each node in the grid, we can help ensure that each purchase of clean energy, siting of a facility that uses electricity, or investment in energy storage is done in a way that maximizes decarbonization potential.


We have a lot of work to do to mitigate the worst of climate change. Enabling sustainability programs and investments to focus on maximizing carbon abatement is a vital step.


Let’s get to work.



¹  Microsoft, Hannon Armstrong, Marathon Capital, Akamai Technologies, Quinbrook Infrastructure Partners, Broad Reach Power, and The Brattle Group


To learn more about REsurety’s Locational Marginal Emission data product and how it measures the carbon emissions avoided by each clean energy purchase or investment, visit or visit our FAQ. For questions and to learn how your company can purchase LME data, contact us at

Q2 2021 Lookback per REmap

1. Modeled Q2 PPA Performance Across Major Hubs

REmap’s new vPPA simulator feature allows users to backcast vPPA settlement at all project locations, enabling analysis of market performance through the lens of a generator or vPPA buyer. 


vPPA settlements represent the value (or cost) of the unit-contingent contract-for-difference hedge settlements that result from a virtual Power Purchase Agreement (vPPA) with a project.


The results below show modeled¹ vPPA settlement values (in $/MWh) from the energy buyer’s perspective over the course of Q2. For potential vPPA buyers, this data answers the question: “If I signed a vPPA at prices available today, how would it have performed this past quarter?” 


Modeled vPPA settlement outside of ERCOT generally resulted in a cost for the vPPA buyer, even assuming today’s competitive PPA prices². Within ERCOT, vPPA settlement favored the vPPA buyer, with settlement values surpassing $25/MWh at some Texas solar projects. The cost of purchasing renewable energy through a vPPA was greatest for energy buyers with a wind vPPA settling at SPP North Hub, SPP South Hub, or PJM AEP-Dayton Hub. Solar vPPAs were most costly for projects settling at PJM Eastern Hub or MISO Michigan Hub.

Q2 2021 Modeled vPPA Settlement for Energy Buyers
Figure 1: Q2 2021 Modeled vPPA Settlement for Energy Buyers. Values for locations/technologies with limited data are not shown or marked "NA".

¹ Results use REmap data for operating projects, which includes modeled and observed hourly generation and observed market prices. Cell values represent the project with the maximum, minimum, or median project settlement value to an energy buyer for the quarter.


² vPPA prices used are from the LevelTen Q2 2021 PPA Price Index, which reports on PPA bids by hub and technology type.

2. Coastal Texas Wind Projects Join the Rest of the Pack

Coastal wind projects in Texas tend to experience higher wind speeds in the afternoon hours, which typically aligns well with afternoon periods of high demand and high power prices. The ability to generate during high priced afternoon hours means coastal projects typically benefit from a positive shape (also known as covariance), whereas wind projects in the rest of Texas tend to experience negative shape (i.e., hours of high generation are negatively correlated with hours of high power prices). 


However, in Q2 2021, coastal projects were not quite as fortunate. Shape profiles throughout all of ERCOT were quite negative, including coastal projects. Projects directly along the coast experienced shape discounts of $7-9/MWh, in line with other projects throughout the state. Figure 2a puts that in context of other ERCOT projects in Q2 2020 and 2021.

Q2 2021 Average Shape Values for Operating ERCOT Wind Projects
Figure 2a: Q2 2021 Average Shape Values for Operating ERCOT Wind Projects. The range and distribution of shape values for operating wind projects in ERCOT in Q2 2020 & 2021. The arrow indicates where the shape value of coastal wind projects fell. Source: REmap.

As an example: Stella Wind Farm, a coastal project in Kenedy County, experienced -$7.36/MWh average shape in Q2 2021, while its prior 5 year average for the same quarter was $0.66/MWh


Why did coastal Texas wind projects not do well, relative to historical performance?


Continuing to use Stella Wind Farm as an example, we can review the hourly performance in REmap using the Hourly Data Explorer.

Figure 2b below shows the hourly data for Stella from April, a month in which the project’s shape value dropped to -$9.32/MWh. The top chart shows the hourly real-time hub price at ERCOT South and bottom chart shows the hourly observed energy from Stella over the entire month.

April 2021 Hourly Hub Price and Generation Data
Figure 2b: April 2021 Hourly Hub Price (top) and Generation Data (bottom). Source: REmap.

Looking at Figure 2b, we can identify two periods of elevated prices, on April 11th and 13th, when prices spiked to over $1800/MWh.


Zooming into the relevant period in Figure 2c, we can see the hourly alignment between price and generation for those days. During both high price events, generation was fairly low.

Hourly Hub Price and Generation Data for April 11th and 13th
Figure 2c: Hourly Hub Price and Generation Data for April 11th and 13th. Source: REmap.

3. Wide Basis Spreads for Wind Projects in Northern MISO

Last quarter, nodal prices for operating wind projects across North Dakota, Southwest Minnesota and Iowa continued a year-long trend of decline–with a precipitous drop. 


To use one project as an illustrative example, Emmoms-Logan Wind saw a -$17.30/MWh node-to-hub basis value in Q1 2021, which was among the lowest of any operating wind project in MISO that quarter. In Q2 2021, its node-to-hub basis plummeted to -$44.20/MWh³. 


If we use Emmoms-Logan’s Q1 performance as a benchmark and compare it to the Q2 performance for other operating wind projects in these states, the sharp decline in basis becomes more obvious. Figure 3a below shows operating wind projects in MISO. The color scale denotes historical node-to-hub basis value for Q2 2021, and the dark red areas denote any project that experienced an average basis value lower than -$17.30/MWh.

Q2 2021 Node-to-Hub Basis for Operating Wind Projects in MISO
Figure 3a: Q2 2021 Node-to-Hub Basis for Operating Wind Projects in MISO. Average generation-weighted basis values calculated using Minnesota Hub. Source: REmap.

Figure 3b below shows the 12-month trailing basis for a handful of wind projects in Northern MISO, including Emmons-Logan, and illustrates that this trend has been over a year in the making, but dramatically accelerated in the past 12 months.

12-Month Trailing Generation-Weighted Basis for Selected MISO Wind Projects
Figure 3b: 12-Month Trailing Generation-Weighted Basis for Selected MISO Wind Projects. Source: REmap.

Basis has been a known issue for project owners and operators and is increasingly a concern for vPPA buyers and offtakers who can be directly or indirectly impacted by basis depending on contract terms. Price data, provided by REmap, provides one critical piece of the puzzle. REmap’s generation data supplies the second critical piece, enabling users to see how much generation occurred in each hour and giving visibility into the impact of basis on project settlement.

³ Basis values are generation-weighted at the hourly level and use Minnesota Hub pricing. Generation is modeled. Actual results may differ.

DEI @ REsurety

For REsurety to succeed in its mission to empower a clean energy-fueled future, we need an interdisciplinary team with different perspectives and backgrounds, where all team members are encouraged to contribute their voice. To support our commitment to fostering a diverse, inclusive culture both within our company and in the energy sector at large, REsurety launched a Diversity, Equity, and Inclusion (DEI) Team in March of 2020. The DEI Team’s primary goals are 1) to provide forums for education and open discussion, and 2) to hire and enable a diverse team.


REsurety’s DEI Team organizes monthly meetings to discuss topics relevant to DEI generally and within the energy and climate industry specifically. The main purpose of these meetings is to provide a safe forum for team members to discuss, debate and explore topics proposed by the DEI steering committee because of their impact. To date, topics have included the role of the Black Lives Matter Movement in advancing social justice, leading inclusive meetings, mitigating gender bias in the workplace and understanding the equity impacts of the February 2021 winter storm in Texas. 


The DEI Team also introduced a mentoring program that enables team members to accelerate their career development skills through long-term mentor relationships with more experienced colleagues. Mentees have used the mentoring program to work on their communication skills and to discuss paths to promotion within the company.


More recently, REsurety’s DEI Team has collaborated with our People Operations team to revise the company’s recruiting framework, with a focus on incorporating DEI principles into REsurety’s sourcing and hiring process. The revised framework provides guidelines and templates for interviewing committees to mitigate unconscious bias. It also includes a review of all new job descriptions prior to their being posted to ensure we maximize the diversity of candidates that will apply to the role.  


We are a mission-driven organization with large ambitions.  We can only deliver on our mission and our goals by attracting, retaining, and empowering a diverse and inclusive team – and one that feels both the opportunity and obligation to drive positive change in the world beyond our walls.


If you share our values and our ambitions, we hope to hear from you!


Visit job postings

PRESS RELEASE: Sustainability Roundtable and REsurety Partner to Scale Renewable Energy VPPAs for SR Inc’s Member-clients

BOSTON, July 19, 2021 – Sustainability Roundtable, Inc (SR Inc), a leader in outsourced Environmental, Social and Governance management, and REsurety, a leading analytics company empowering the clean energy economy, today announced a partnership to facilitate the systemization and scaling of buyer-favorable renewable energy transactions for SR Inc’s Net Zero Consortium for Buyers (NZCB). SR Inc Member-clients, including Akamai Technologies, Autodesk, Biogen, Intuit, McKesson, MilliporeSigma, Synopsys, Uber and Wayfair, have helped make NZCB the leading platform for buyer-aggregated Virtual Power Purchase Agreements (VPPAs).  SR Inc’s buyer-favorable VPPAs have set the standard for mid-size companies who want to aggregate their buying power to drive market-leading pricing and contractual protections for offsite utility-scale renewable energy procurement and have been described as the “VPPA 2.0.” SR Inc will leverage REsurety’s Renewable Energy Market Analytics Platform (REmap) to assess the value and risk of renewable energy VPPA opportunities for NZCB Member-clients.


Today’s announcement formalizes an existing working relationship between the two companies that spans REmap and REsurety’s latest decarbonization impact data product, Locational Marginal Emissions (LME).


“SR Inc and Member-clients have been especially impressed by the outstanding quality and remarkable depth of REsurety’s data and analytics,” said Jim Boyle, CEO of Sustainability Roundtable, Inc. “Having SR Inc’s NZCB supported by REsurety’s data analytics as well as that from our other providers, helps NZCB companies accelerate towards their collective goal of helping to create more than a gigawatt of new renewable energy capacity before 2025.  Together we are helping to democratize the environmental and financial benefits of utility scale renewable energy, which was previously available only to the world’s largest companies that could cause utility scale projects on their own.”


REsurety’s REmap tool offers unparalleled visibility into project-specific performance for utility-scale solar and wind projects across the US. Key metrics shown include actual and modeled generation, earned pricing data, and simulated PPA settlement. Unlike other tools that assume average generation profiles or rely on 8760s as inputs, REmap combines project-specific modeled or actual generation with concurrent historical hourly price data to support better renewable energy procurement decisions. REsurety’s Locational Marginal Emission (LME) data tool measures the project-specific carbon impact associated with a renewable energy project – a first for the industry. REsurety’s innovative data-driven products will empower NZCB companies to address decarbonization goals confidently and cost-effectively.


“We are delighted to join forces with the Sustainability Roundtable team and their Member-clients to accelerate our collective path to a zero-carbon future. We believe that the best information – and the tools to act on it – is an essential foundation for the selection and management of clean energy procurement and SR Inc is a great platform to deliver that value and empower the clean energy buyer community,” said Lee Taylor, CEO of REsurety.


SR Inc is focused on providing NZCB Member-clients with the most accurate and comprehensive renewable energy project information available and looks forward to announcing more partnerships in the future.



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.  


With the world’s leading clean energy investors, advisors, buyers, and developers as clients and 7,000 MW of transactions closed, REsurety empowers clients to thrive in the dynamic, complex, clean energy-fueled future. Learn more at



About Sustainability Roundtable, Inc.


SR Inc is a leader in outsourced Environmental, Social and Governance (ESG) management missioned to accelerate the development and adoption of best practices in more sustainable business. SR Inc’s NZCB is a confidential buyers’ community that helps participants develop emissions reduction strategies and benefit from the economies of scale to shape market-leading procurements. SR Inc Member-clients have made SR Inc’s NZCB the leading platform for Buyer Aggregated Virtual Power Purchase Agreements. These “VPPA2.0s” are specifically tailored to the demands of high-credit, risk-averse, corporate buyers.  Learn more at



Read the full release here.

PRESS RELEASE: REsurety launches Locational Marginal Emissions data product to empower customers to measure and maximize how much carbon they cut through clean energy purchases

BOSTON, July 14, 2021 – REsurety announced today a new data tool, called Locational Marginal Emissions, created with Microsoft and built on the Microsoft Azure cloud platform, to help customers maximize decarbonization investments. Top clean energy buyers, investors, and advisors including Microsoft, Hannon Armstrong, Marathon Capital, Akamai Technologies, Quinbrook Infrastructure Partners, Broad Reach Power, and The Brattle Group will use the new data product from REsurety to measure and maximize the decarbonization impact of each dollar they spend on solar, wind, and energy storage.


Buying clean energy is a means to an end: decarbonization. While many corporations have committed to achieve carbon neutrality or “net-zero” by a certain date, the methods for measuring and maximizing progress have been limited by a lack of data. To date, carbon measurement tools have relied on regional averages, which can materially over- or under-estimate the carbon impact of a specific clean energy project.


The new Locational Marginal Emissions data tool from REsurety addresses this problem.


REsurety’s patent-pending Locational Marginal Emissions technology calculates the carbon emissions at each node on an electric grid with hourly granularity. This helps decision-makers understand how much each specific clean energy procurement, load-siting, or energy storage decision contributes to their decarbonization goals.


Corporations can more precisely and strategically address their net-zero and carbon-free goals by using Locational Marginal Emissions to more accurately measure how much carbon is being avoided by their specific clean energy projects, as well as to better measure how much carbon is emitted as result of their electrical load.


“Locational Marginal Emissions solve the need for transparent and accurate carbon impact data,” said Lee Taylor, CEO of REsurety. “It’s what corporate ESG leaders want to know: how many tons of carbon emissions are actually avoided by the clean energy they’re buying.”


“We can play a key role in fully decarbonizing the grid,” said Brian Janous, GM of Energy and Renewables, Microsoft. “To do it the fastest and the most cost-effectively, we need to be able to understand the carbon impact of each MWh coming from a specific wind, solar, or storage plant. We want to make sure that the clean energy we’re helping to bring onto the grid has the maximum environmental benefit. REsurety’s Locational Marginal Emissions data gives us the transparency we need to make climate-wise investments.”


Sustainability leaders who will use the new data tool range from tech companies to investment banks and impact investors.


Climate investment firm Hannon Armstrong will use Locational Marginal Emissions to further enhance its sustainability investment screen for clean energy assets. “Understanding the carbon impact for all current and future portfolio projects is central to our purpose as a climate positive investor. LMEs offer precision that previously did not exist in the marketplace, and we are pleased to incorporate this innovative and complementary data set alongside our CarbonCount® methodology,” said Rich Santoroski, Chief Analytics Officer.


Marathon Capital, an industry-leading investment bank and advisor, plans to use Locational Marginal Emissions to support their clients. “We are eager to apply this data-driven approach to empower our clients to invest in projects with the largest carbon-reducing impact,” said Joan Hutchinson, Managing Director of the Offtake Advisory group.


David Scaysbrook, Managing Partner of Quinbrook, said, “REsurety is tackling a fundamental data gap we have all been grappling with. Reducing carbon emissions by deploying impactful renewables at scale lies at the core of our work at Quinbrook. Using LMEs will help us be even more discriminating in the investments we make, and it will assist us, our investors, and our offtake customers to create accurate carbon assessments that both track our ‘value add’ and meet increasing reporting obligations.”


REsurety VP of Power Market Research Dr. David Luke Oates and Dr. Kathleen Spees of The Brattle Group co-authored a white paper earlier this year that introduced the new Locational Marginal Emissions approach. “Increasingly, electricity systems that are decarbonizing will face grid pockets of clean energy ‘saturation’ where developing more clean energy will offer diminishing decarbonization value. LME data will offer policy makers and consumers the information they need to shift program dollars to where it can make the greatest impact,” said Dr. Spees.


Akamai Technologies, a leading provider of solutions that protect and deliver digital content, plans to use Locational Marginal Emissions to improve measurement of emission reductions derived from renewable energy investments. “In order to achieve our 2030 sustainability goals, which include powering 100% of global operations with renewable energy, we need transparency and accuracy in measuring our emissions,” says Mike Mattera, Director of Corporate Sustainability. “REsurety’s LMEs provide us with an extra level of confidence in our calculations.”


“Broad Reach Power is proud to join this group of industry leaders as an early adopter of the Locational Marginal Emissions tool,” said Paul Choi, EVP of Origination at Broad Reach Power, an owner/operator of utility-scale wind, solar, and energy storage power projects. “With a storage pipeline exceeding 14 GW, granular carbon emissions data will be crucial to ensure we more efficiently reduce carbon emissions while increasing grid reliability.”


REsurety’s Locational Marginal Emissions data is available for projects in ERCOT and will be available for other U.S. markets later this year. To learn how your company can better measure and maximize the carbon impact of your clean energy investments or purchases, contact

WHITE PAPER: Friends Don’t Let Friends Use 8760s

A new white paper from REsurety, with contributions from Hannon Armstrong, a leading investor in climate solutions, offers an in-depth analysis into how using an “8760” energy model can lead to significant errors in revenue modeling — topping 30% in some high renewable penetration markets.


An “8760” (also known as a “typical meteorological year,” or “TMY”) is the expected typical generation for a given wind or solar project for each of the 8,760 hours in a non-leap year. Despite their widespread use in the renewable energy industry, using an 8760 to project financial performance can lead to significant errors in revenue modeling.

Fill out the form below to access the white paper.


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Who were the “winners” & “losers”? An analysis of wind projects in Texas’ 2021 deep freeze

Until recently, comprehensive granular data about which individual power plants were generating during the February deep freeze in Texas didn’t exist. As a result, most analysis to date has focused on aggregate fleet performance (such as our analysis of wind and solar performance given local weather conditions) or the meteorological conditions that caused the event. While limited project outage information was available from ERCOT, the hour-by-hour performance of each plant had not been made public – until now.


Hourly project-level generation data is released by the Texas grid operator on a 60-day lag, which means that February information was just released recently. Each month, our market intelligence tool REmap processes this data from the grid operator, making it easy to visualize and assess project-level performance with a couple of clicks.


In this analysis, we’ll take a closer look at the project-level hourly performance data and seek to identify key trends and takeaways from that granular dataset. We will focus on wind projects, as solar projects were widely known to have performed or overperformed relative to expectations.


This article analyzes the performance of wind projects in all of ERCOT. For individual project consultation and to understand what the February 2021 event means for your projects, either in development or already operating, speak to our REmap team today. 



Top Generators


To start, we want to highlight the high performing wind projects in ERCOT’s fleet. We’ll look at this by the project’s net capacity factor, that is, how much energy the project contributed to the grid adjusted for the size of the project. Here, we are focusing on performance during the deep freeze, so from February 11 through February 19.


Figure 1. Top 10 performing ERCOT wind projects 2/11-2/19, by capacity factor.



Top Revenue Makers


While generating essential megawatt-hours was critical to supporting the grid during the winter storm, another important topic is the financial impact of the event.


It is hard to overstate the impact of the February 2021 winter storm on power markets. Power prices were at or near $9,000/MWh for nearly 100 hours, leading to a cumulative price that was over 10 times that of the prior “extreme” market event in August 2019.


Figure 2. Observed cumulative power prices at ERCOT North Hub in different months.


Overall, the financial “winners” were those projects that generated during the highest-price hours (the hours in which scarcity conditions elevated power prices). It is important to note, however, that the high value of generation during high priced events is often shared, in whole or in part, with the offtaker of the project as a result of contract-for-difference hedge settlements (in all its various flavors: vPPA, pgPPA, PRS, P99 Hedge).


Let’s look at the highest value projects across Texas at each major hub.


Figure 3. Top 5 performing wind projects in February 2021, by region, ranked by generation-weighted real-time price at the hub.


What’s common across Texas is that the around-the-clock (ATC) price of power in February 2021 exceeded $1,500/MWh. After that, what should stand out is that wind projects across South Hub were best-positioned to generate valuable energy and capture record-high prices. Projects at North Hub experienced a significant shape discount, while the best projects at West Hub experienced a more neutral shape relative to the around-the-clock (ATC) price. 


The highest realized value was achieved by Peyton Creek Wind Farm, with a generation-weighted realized hub price that exceeded $2,000/MWh



Congestion Impacts in ERCOT South


Not only did Peyton Creek Wind Farm benefit from valuable generation at the hub level, it also benefited from limited node-to-hub congestion (also known as “basis”). The project is located between Houston and Corpus Christi, with few wind projects nearby to compete for valuable transmission capacity. Many of the other highest-value ERCOT South wind projects are all located in a relatively congested area further south, and experienced materially worse grid congestion.


Figure 4. Node to hub basis (in $/MWh) in February 2021 across Texas wind projects.


Figure 4 shows that basis impacts varied widely across the ERCOT region during the winter storm. Positive basis (dark green) indicates that a project observed a higher LMP at the project node than the price at the hub. This is generally in the project’s favor, as offtake agreements usually settle at a hub. Any positive basis then is upside for the project, while negative basis implies a loss for the project.


Although most of ERCOT experienced relatively minimal node to hub basis during the winter storm, projects in the ERCOT South region saw significant basis impacts. When wind speeds are high and projects are generating, it’s not uncommon for projects in South Texas to suffer from congestion-related impacts.


To understand what was happening in ERCOT South it is helpful to dive one level deeper. Figure 5 shows the hourly price and generation data for a coastal Texas wind project, Cameron Wind, that saw significant negative basis during the event. The middle chart highlights the difference between the nodal and hub price at one specific hour on February 17th — almost -$4,700 — and the bottom chart shows the observed hourly generation. 


Figure 5. From top to bottom: real-time hourly price (project node in red, ERCOT South hub in green), node-to-hub basis, and generation for Cameron Wind in South Texas for February 13-20, 2021.



Unprecedented Variability


While coastal Texas wind projects fared the best (see Figure 3), there was considerably more variability in their financial performance in February 2021 than during past events. Figure 6 shows historical real-time shape in dollars per megawatt-hour from August 2019 to February 2021 for several wind projects along the coast of south Texas. 


Figure 6. Historical shape (in $/MWh) from August 2019 to February 2021 for various coastal Texas wind projects.


Figure 6 shows these projects all performed similarly during the extreme price event in August 2019, but diverged materially in February 2021. Several coastal Texas wind projects saw extreme negative shape values in February 2021, a dramatic divergence from the August 2019 event. The negative shape values are likely due to poor operating performance during high-priced periods. 


Poor Performers


The worst revenue and shape values were seen by the wind and solar projects that were offline for the duration of the high priced event. These projects were unable to generate — whether due to operating decisions, transmission constraints, or other reasons — when electricity was most in demand and power prices at their highest. (Analysis of hourly data shows, for example, that Big Spring Wind Power generated zero megawatt-hours between February 10th and February 19th.) As such, their generation-weighted value is significantly lower than the around-the-clock price of power at the hub. These projects were heavily concentrated in West Texas. 


Figure 7. Lowest performing wind projects in February 2021, by region, ranked by generation-weighted real-time price at the hub.



Learn More 


The deep freeze in Texas was an unprecedented event in ERCOT’s history. Granular analysis of projects in the region gives visibility into which projects benefitted from the period of extreme market conditions and which projects didn’t. Going forward, as the focus of generators and policy-makers alike shifts towards resilience, having visibility into this performance data will become more important than ever.


REmap is REsurety’s market analytics platform, an interactive tool that allows users to quickly and accurately understand the impacts of weather and power markets on the value of renewable energy projects. To learn more, visit or contact us at



A similar version of this post appeared in Windpower Monthly.

Modern Decarbonization Strategies Depend on Modern Carbon Impact Data

Purchasing renewable energy is a means to an end: decarbonization. Yet, renewable energy projects are not all equal when it comes to cutting carbon. 


At REsurety, we’re developing a new carbon impact measurement tool called Locational Marginal Emissions (LMEs) that measure carbon emission reductions at the granular level: the electrical node where the carbon-free energy is injected into the grid. 


What becomes clear when working at this level of granularity is that one clean energy project can have dramatically more carbon abatement impact than another – even when they are located just a few miles apart. For example, we assessed the Locational Marginal Emissions of two otherwise comparable solar projects in west Texas and found that one displaces twice the carbon emissions as the other. 


Our team sees better measurement of carbon impact as an urgent need. Over 300 companies have joined the RE100 initiative, committing to 100% renewable energy. These companies have increasingly turned to virtual Power Purchase Agreements (vPPAs) to meet their sustainability targets. But when a corporation purchases off-site renewable energy through a vPPA to offset a portion or all of its energy usage, it typically measures its carbon impact in megawatt-hours (MWh) which – depending on the project – can dramatically over- or underestimate the true carbon impact of that project’s operations.


A shift is now underway from 100% renewable to carbon zero – which is quite a different goal. Renewable purchases are easy to measure, while measuring the carbon they eliminate has been challenged by a lack of data. 


Nevertheless, two dozen tech firms and environmental groups appealed to the Biden Administration to adopt a 24/7 Carbon-Free energy approach like the one Google is employing to achieve “clean energy every hour, every day, everywhere.” In March, the Administration in its American Jobs Plan agreed to apply that standard to federal buildings.


More recently, on Earth Day 2021, President Biden doubled down on the U.S. carbon-cutting commitment, promising world leaders to put the U.S. on a path to cut its carbon emissions in half by 2030.


The ultimate goal is clear: to reduce our carbon emissions as quickly and cost-effectively as possible to avoid further impacts of climate change. Which projects get us there the fastest and at the lowest dollar per ton avoided to date has been far from clear. As Google – which initiated the 24/7 Carbon-Free initiative in 2017 – has highlighted, the necessary data to track progress accurately “is generally unavailable.” We believe that LMEs solve that problem.


Our new white paper, “Locational Marginal Emissions: The Force Multiplier for Amplifying the Carbon Impact of Clean Energy Programs,” co-authored by Dr. David Luke Oates of REsurety and Dr. Kathleen Spees of The Brattle Group, dives into exactly why some renewable energy projects mitigate more carbon than others, and may thus be a better investment decision for meeting sustainability goals. “LME-based accounting can form the basis of more cost-effective public policies and corporate sustainability strategies,” Spees says, “by guiding the development of clean energy projects that maximize the carbon abatement value of every program dollar spent.”


The name Locational Marginal Emissions comes from the power-price corollary: Locational Marginal Price the cost to serve one MWh of incremental load at a given location. In other words: if you’re going to consume one incremental MWh at that location, what generator or set of generators is that energy going to come from, and how much does that “marginal” generator need to be paid to produce that incremental MWh? 


The Locational Marginal Emissions metric uses the same fundamental concept, but it incorporates the marginal generator’s emissions rates. By calculating the LME, we can accurately measure the carbon impact, or the emissions reductions, of generating clean power at any given moment at any given location on the grid. 


Referring back to our example of the two west Texas solar projects, when we analyzed the data for those otherwise comparable projects, we found that available transmission led to one project displacing coal in the peak of the day’s sunshine, while transmission constraints resulted in the other causing the curtailment of another nearby solar project.


Cumulative carbon emissions avoided by two wind projects and two solar projects in Texas show just how much carbon emissions avoided by renewable energy vary, even within a given sub-region on the ERCOT grid.



The Need is Pressing


Tackling climate change at a massive scale requires us to maximize the carbon impact of every dollar spent on clean energy. And not every megawatt or megawatt-hour is created equal. We need transparency around the actual carbon emissions avoided by a given renewable energy project in order to select and invest in renewable energy projects with the greatest carbon-reducing impact on a dollars-per-ton basis. 


We are not alone – companies and their stakeholders are calling for more accountability around their sustainability targets and investments, ensuring that the scale of their impact matches the scale of their good intentions.


Right now we’re working on what these corporate ESG leaders have been asking for: clearer, more transparent answers on how many tons of carbon emissions are actually avoided by the renewable energy projects they’re buying energy from.



Data-driven insights made possible by Locational Marginal Emissions will allow companies to select and invest in renewable energy projects with the greatest carbon-reducing impact.


If companies are serious about reducing their Scope 2 emissions from energy use, they need better data — data that reflects the actual carbon-intensive units their clean energy megawatt-hours are displacing. 



Reposted as in PowerMagazine.

WHITE PAPER: Locational Marginal Emissions

Purchasing renewable energy is a means to an end: decarbonization. Yet, renewable energy projects are not all equal when it comes to cutting carbon. We’re developing a new carbon impact measurement tool called Locational Marginal Emissions (LMEs) that measures carbon emission reductions at the granular level: the electrical node where energy is injected into the grid.

Fill out the form below to access our white paper on Locational Marginal Emissions.


POWER, FINANCE & RISK: Locational Marginal Emissions

Increasingly popular “24/7 clean energy” strategies can miss project details if they’re based on regional and annual averages, Power Finance & Risk reported May 10 in a story by Taryana Odayar.


“That strategy ignores the sub-regional transmission congestion that can have a significant impact on carbon intensity,” the magazine quoted  REsurety CEO Lee Taylor saying on Norton Rose Fulbright’s May 4 Currents podcast . Instead, REsurety has a new way to measure carbon called “Locational Marginal Emissions” that looks at exactly where and when energy is added to the grid.


“We have a common enemy which is that not all megawatt-hours are equal, so a megawatt-hour generated from one location can be meaningfully different from another location based off of the electrical grid that that’s operating,” Taylor said on Currents. “As companies are trying to go carbon-neutral, carbon-free, carbon-negative, they need more than annual megawatt-hour accounting to do that effectively.”


Power Finance & Risk linked to REsurety’s white paper with The Brattle Group on LMEs, which compares two solar projects in West Texas. One displaces twice as much carbon because it has access to transmission to displace coal-fired generation, while the other curtails another nearby solar plant. The result helps companies such as Google that are committed to 24/7 strategies find out exactly how much carbon they’re reducing.



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