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The emission reduction value of storage has been locked behind a glass cage: everyone can see the potential for storage to reduce the grid’s carbon intensity, but, until now, the incentives and analytics required to value storage’s carbon abatement effects have been lacking. Or, as Rodney Dangerfield might have put it: storage gets no respect-it can’t even generate a REC. For renewable generators, procurement of traditional Renewable Energy Credits (RECs) has played a pivotal role in reducing emissions and has provided a critical incentive to bring new resources onto the grid. However, as renewable energy penetration grows, not all RECs are created equal. Adding a new solar project in the California desert provides little carbon reduction value when many other solar resources are already generating power (see Figure 1), whereas storing and shifting that power to overnight hours will offset natural gas fired generation and reduce overall grid emissions. Quantifying the time-varying carbon intensity of electric generation across locations in the grid is fundamentally necessary to achieve deep decarbonization because it will unlock the ability to account for and incentivize behaviors that reduce that intensity.
As seen in Figure 1, mid-day RT energy prices at CAISO’s SP15 hub in April 2024 were consistently negative, indicating that solar was on the margin and able to meet the region’s power needs during those hours. This implies that marginal emissions during solar hours were often zero for SP15 – see Technical Appendix for more details. Hidden in the magnitude of April’s negative prices is proof that California’s REC market is grossly inefficient. Solar resources setting the marginal price bid down to and below -$50/MWh. They did so because California’s strict RPS goals and upcoming compliance period has led to more demand than supply for RECs, causing their value to skyrocket, meeting and even exceeding Californias’s noncompliance penalty of $50/MWh. When load-serving entities (LSE’s) buy RECs produced at a time when marginal emissions are near zero, the carbon abatement value of these environmental attributes/credits is worthless, and their value exists only in RPS/CPUC compliance. They can then use those RECs to offset their consumption in non-solar hours, often produced with natural gas. Paying for abatement-free solar RECs and claiming “net-zero” reflects the broken nature and perverse incentives of the annual REC accounting system. And in April, doing so was not only ineffective, but expensive. The current $50+ price of RECs reflects strong corporate decarbonization goals, as well as the political will to impose costly obligations aimed at decarbonization. To get the most out of this money, a more effective accounting framework is needed -- one that reflects the emissions value of clean energy at different times and places.
To fill the void left by the traditional REC, clean energy buyers are turning to more sophisticated structures. Some groups1 are pioneering hourly REC matching, which will account for time-based attributes of clean energy production. This framework matches consumption and production on an hourly basis, largely eliminating the mismatch in emissions intensity that makes annual REC matching so ineffective. Other organizations2, however, focus on building and procuring whichever resources abate the most carbon, regardless of how they match electricity consumption. This framework matches a procurer’s incurred emissions to the emissions abatement of the resources they procure, incentivizing the lowest-cost and highest impact resources first. As higher-resolution incentives and new approaches to carbon accounting evolve, decision-makers need higher-resolution analytics to compare strategies and determine which resources most effectively meet their decarbonization goals. Enter AscendAnalytics’ Locational Marginal Emissions (LME) solution, which is being used to support both hourly matching and emissions-first approaches.
To reach the increasingly common goal of 24/7 carbon-free energy, or the tax credit requirements for hydrogen facilities to match hourly renewable energy procurement to hydrogen production, storage is needed to shift delivery of clean power from times of overproduction to times of underproduction. This underscores a major flaw in the current structure of market incentives intended to decarbonize the grid. Storage is conspicuously missing from the list of resource types that qualify. As seen in Figure 3, at CAISO’s SP15 Hub, storage can achieve roughly the same emissions reduction as an equivalently sized solar asset. Under current market structures, the solar resource would earn over 250,000 RECs, worth millions of dollars, while the storage resource would earn zero. Locational marginal emissions data and emerging structures for carbon accounting will not only value the emissions impact of storage, but incentivize increased investment, more effective project siting, and emissions-conscious operations.
Ascend’s locational marginal emissions data allow developers and procurers to assess the expected hourly emissions reduction potential at a nodal level. Given a price on reducing carbon emissions, these data can then be used to estimate the dollar value of storage’s effect on emissions. At $35/ton, the 100MW storage project shown in Figure 3 could have earned $1.8 million in emissions abatement value, in addition to energy market and resource adequacy revenues. As the monetization of storage’s emissions reduction matures, this will become a critical revenue stream in the storage revenue stack and drive continued buildout, not unlike how RECs have allowed the solar and wind industries to finance projects to date. However, just as not all RECs are created equal, not all locations are created equal with regard to their emissions reduction potential, as seen by large differences between SP15 Hub and NP15 Hub in Figure 4.
Besides displacing carbon-emitting capacity resources, storage reduces emissions by charging when LMEs are low and discharging when LMEs are high. Therefore, locations with the largest spreads in hourly emissions intensity have the highest emissions reduction potential for storage resources. This adds a new dimension to the siting of storage resources, where the existing paradigm is largely influenced by choosing sites with the largest spreads in Locational Marginal Prices (LMPs). A storage project may have very different emissions impacts depending on its location, as seen in Figure 5. In the face of evolving revenue streams, careful analysis of both price volatility and emissions volatility is needed to determine optimal project siting and unlock the emissions reductions value of storage.
CAISO’s recent emissions and market dynamics have shown that annual REC matching is an inadequate carbon accounting method for grids in the midst of the energy transition. Quantifying the location and time dependent emissions intensity of electricity production is critical to incentivizing resources that most effectively meet emissions goals. Doing so will accelerate investment in historically undervalued resources such as storage and improve the industry’s understanding of the optimal resource mix to accelerate decarbonization.
To learn more about Ascend’s temporal and geospatial emissions data and stay updated on the rollout of forward-looking LME data for CAISO and for other markets, learn more about our Market Intelligence Solution. For technical details supporting this publication, please contact us to request a copy of the Technical Appendix: Ascend Analytics’ Locational Marginal Emissions Methodology, dated July 2024.
Endnotes
The emission reduction value of storage has been locked behind a glass cage: everyone can see the potential for storage to reduce the grid’s carbon intensity, but, until now, the incentives and analytics required to value storage’s carbon abatement effects have been lacking. Or, as Rodney Dangerfield might have put it: storage gets no respect-it can’t even generate a REC. For renewable generators, procurement of traditional Renewable Energy Credits (RECs) has played a pivotal role in reducing emissions and has provided a critical incentive to bring new resources onto the grid. However, as renewable energy penetration grows, not all RECs are created equal. Adding a new solar project in the California desert provides little carbon reduction value when many other solar resources are already generating power (see Figure 1), whereas storing and shifting that power to overnight hours will offset natural gas fired generation and reduce overall grid emissions. Quantifying the time-varying carbon intensity of electric generation across locations in the grid is fundamentally necessary to achieve deep decarbonization because it will unlock the ability to account for and incentivize behaviors that reduce that intensity.
As seen in Figure 1, mid-day RT energy prices at CAISO’s SP15 hub in April 2024 were consistently negative, indicating that solar was on the margin and able to meet the region’s power needs during those hours. This implies that marginal emissions during solar hours were often zero for SP15 – see Technical Appendix for more details. Hidden in the magnitude of April’s negative prices is proof that California’s REC market is grossly inefficient. Solar resources setting the marginal price bid down to and below -$50/MWh. They did so because California’s strict RPS goals and upcoming compliance period has led to more demand than supply for RECs, causing their value to skyrocket, meeting and even exceeding Californias’s noncompliance penalty of $50/MWh. When load-serving entities (LSE’s) buy RECs produced at a time when marginal emissions are near zero, the carbon abatement value of these environmental attributes/credits is worthless, and their value exists only in RPS/CPUC compliance. They can then use those RECs to offset their consumption in non-solar hours, often produced with natural gas. Paying for abatement-free solar RECs and claiming “net-zero” reflects the broken nature and perverse incentives of the annual REC accounting system. And in April, doing so was not only ineffective, but expensive. The current $50+ price of RECs reflects strong corporate decarbonization goals, as well as the political will to impose costly obligations aimed at decarbonization. To get the most out of this money, a more effective accounting framework is needed -- one that reflects the emissions value of clean energy at different times and places.
To fill the void left by the traditional REC, clean energy buyers are turning to more sophisticated structures. Some groups1 are pioneering hourly REC matching, which will account for time-based attributes of clean energy production. This framework matches consumption and production on an hourly basis, largely eliminating the mismatch in emissions intensity that makes annual REC matching so ineffective. Other organizations2, however, focus on building and procuring whichever resources abate the most carbon, regardless of how they match electricity consumption. This framework matches a procurer’s incurred emissions to the emissions abatement of the resources they procure, incentivizing the lowest-cost and highest impact resources first. As higher-resolution incentives and new approaches to carbon accounting evolve, decision-makers need higher-resolution analytics to compare strategies and determine which resources most effectively meet their decarbonization goals. Enter AscendAnalytics’ Locational Marginal Emissions (LME) solution, which is being used to support both hourly matching and emissions-first approaches.
To reach the increasingly common goal of 24/7 carbon-free energy, or the tax credit requirements for hydrogen facilities to match hourly renewable energy procurement to hydrogen production, storage is needed to shift delivery of clean power from times of overproduction to times of underproduction. This underscores a major flaw in the current structure of market incentives intended to decarbonize the grid. Storage is conspicuously missing from the list of resource types that qualify. As seen in Figure 3, at CAISO’s SP15 Hub, storage can achieve roughly the same emissions reduction as an equivalently sized solar asset. Under current market structures, the solar resource would earn over 250,000 RECs, worth millions of dollars, while the storage resource would earn zero. Locational marginal emissions data and emerging structures for carbon accounting will not only value the emissions impact of storage, but incentivize increased investment, more effective project siting, and emissions-conscious operations.
Ascend’s locational marginal emissions data allow developers and procurers to assess the expected hourly emissions reduction potential at a nodal level. Given a price on reducing carbon emissions, these data can then be used to estimate the dollar value of storage’s effect on emissions. At $35/ton, the 100MW storage project shown in Figure 3 could have earned $1.8 million in emissions abatement value, in addition to energy market and resource adequacy revenues. As the monetization of storage’s emissions reduction matures, this will become a critical revenue stream in the storage revenue stack and drive continued buildout, not unlike how RECs have allowed the solar and wind industries to finance projects to date. However, just as not all RECs are created equal, not all locations are created equal with regard to their emissions reduction potential, as seen by large differences between SP15 Hub and NP15 Hub in Figure 4.
Besides displacing carbon-emitting capacity resources, storage reduces emissions by charging when LMEs are low and discharging when LMEs are high. Therefore, locations with the largest spreads in hourly emissions intensity have the highest emissions reduction potential for storage resources. This adds a new dimension to the siting of storage resources, where the existing paradigm is largely influenced by choosing sites with the largest spreads in Locational Marginal Prices (LMPs). A storage project may have very different emissions impacts depending on its location, as seen in Figure 5. In the face of evolving revenue streams, careful analysis of both price volatility and emissions volatility is needed to determine optimal project siting and unlock the emissions reductions value of storage.
CAISO’s recent emissions and market dynamics have shown that annual REC matching is an inadequate carbon accounting method for grids in the midst of the energy transition. Quantifying the location and time dependent emissions intensity of electricity production is critical to incentivizing resources that most effectively meet emissions goals. Doing so will accelerate investment in historically undervalued resources such as storage and improve the industry’s understanding of the optimal resource mix to accelerate decarbonization.
To learn more about Ascend’s temporal and geospatial emissions data and stay updated on the rollout of forward-looking LME data for CAISO and for other markets, learn more about our Market Intelligence Solution. For technical details supporting this publication, please contact us to request a copy of the Technical Appendix: Ascend Analytics’ Locational Marginal Emissions Methodology, dated July 2024.
Endnotes
Ascend Analytics is the leading provider of market intelligence and analytics solutions for the energy transition. The company's offerings enable decision makers in power development and supply procurement to maximize the value of planning, operating, and managing risk for renewable, storage, and other assets. From real-time to 30-year horizons, their forecasts and insights are at the foundation of over $50 billion in project financing assessments. Ascend provides energy market stakeholders with the clarity and confidence to successfully navigate the rapidly shifting energy landscape.
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