Q2 2026 OpenEAC Alliance Meeting
Join us for a deep dive on GridScore, CarbonScore, and a new thermostat workstream
Next week (Thursday, 8am PT) is the next quarterly meeting of the OpenEAC Alliance. Following up on last quarter’s rollout of demand response and load shifting methodologies, we have introduced two new metrics for calculating the impacts of demand-side energy resources.
GridScore is the percentage of energy savings that happen during the 10% of hours when the grid is most stressed.
CarbonScore is the carbon savings per kilowatt-hour of energy savings.
Like most metrics, there are a number of edge cases that we’ve encountered as we’ve rolled this out across different DER classes. There are small denominator effects, negative number effects, etc. We’ll use the time to take a deep dive on how to think about measuring the grid and carbon impacts of DERs and how to report them in a way that captures the full value.
Smart Thermostat Load Shifting
In addition to formalizing GridScore and CarbonScore as default EAC impact metrics, we will begin the work of creating a unified smart thermostat load shifting methodology. We’ve already developed a general load shifting methodology using smart meter data, but in many cases, smart thermostats are deployed in areas where smart meters are lacking or where data access is prohibitively difficult and/or expensive. Still, in aggregate, these devices are capable of delivering megawatts of load flexibility, essential for managing summer and winter peak loads.
We will propose a novel solution to the classic challenge of thermostat calculations, using NREL-based load profiles for buildings as the basis for determining the size of the HVAC load. Combined with thermostat run-time data, we expect that the subjectivity and potential for error will be greatly reduced by this approach. Empirical studies using available meter data will provide uncertainty metrics for evaluating portfolio level impacts.
Summary of Q1 OpenEAC Alliance Meeting
We did not share out the notes from the last quarterly meeting. If you weren’t able to attend, below are the highlights of what we covered:
Demand Efficiency Focus: Shift from traditional energy efficiency to managing when energy is consumed for better grid use.
DER Contribution Metrics: Coincident peak contribution and effective load carrying capacity (ELCC) to assess DER impacts during peak stress.
Incentive Model Challenges: Upfront incentives conflict with long-term measurement and verification, complicating DER investment.
Regulatory Drivers: FERC 2222 opens pathways for aggregated demand response to compete in energy markets.
Localization Impact: DER value varies significantly based on proximity to grid constraints and regional characteristics.
Collaboration and Feedback: Open invitation for stakeholder input to refine methodologies and ensure effective grid integration.
Notes
Demand Efficiency Concept and Grid Impact
The meeting clarified that the core shift is focusing on demand efficiency rather than traditional energy efficiency, aiming to optimize grid use by managing when energy is saved or consumed (05:26).
Paradigm shift from energy to demand efficiency (05:26)
The value of energy savings depends heavily on the time of day, with peak evening savings more valuable than midday.
Infrastructure costs, like substations and transmission lines, drive rising bills, not just total energy use.
Efficiently using the grid’s capacity at all hours lowers per-unit infrastructure costs.
Distributed Energy Resources (DERs) can help flatten load profiles, maximizing grid utilization and reducing expansion needs.
Grid as a water pipe analogy illustrating capacity use (11:19)
The grid has fixed capacity like a water pipe’s diameter; maximizing flow means better cost recovery.
Peak demands require costly grid upgrades, increasing overall costs if consumption spikes unevenly.
Inefficient demand patterns, even with steady total use, can force expensive grid expansions and higher rates.
DERs delivering demand efficiency during peak hours can prevent costly upgrades and reduce consumer bills.
Challenges related to utility incentives and DER adoption (14:18)
Utilities often profit from building infrastructure, disincentivizing demand efficiency that reduces expansion.
Regulatory and market developments like FERC 2222 enable non-utility buyers and aggregated demand response participation.
Corporate buyers, such as data centers, could fund DERs themselves to manage flexible interconnections and reduce grid stress.
This “bring your own capacity” (BYOC) model could unlock peak capacity savings and reduce utility infrastructure costs.
Massive scale and automation needs for DER deployment (19:12)
Current DER installations represent about 1% of what will be needed for future high-load centers like data centers.
Scalable and automated measurement and verification (M&V) systems are essential to manage this growth efficiently.
Standardized, hourly granularity measurement is needed to ensure accurate capacity valuation and avoid double counting in markets.
The complexity and scale demand robust data systems and regulatory clarity to support multi-buyer competitive markets.
Measurement and Verification Methodology
The team introduced a draft methodology focusing on precise, hourly measurement of DER contributions aligned with grid stress signals to enable clear capacity valuation (34:28).
Two key metrics: coincident peak contribution and effective load carrying capacity (ELCC) (34:28)
Coincident peak contribution measures how much a DER reduces load during stressed hours based on hourly M&V data.
ELCC estimates the reliability and capacity value of DERs across various stress scenarios, similar to how utilities value power plants.
ELCC accounts for portfolio effects, seasonal variation, and the likelihood of DER availability during peak periods.
Different Independent System Operators (ISOs) have varying approaches to ELCC, reflecting inconsistent valuation standards across markets.
Use of system stress signals to identify critical hours (37:43)
Stress signals can be utility-wide peak loads, market price signals, or locational grid constraints, varying by region and buyer.
Example visuals showed battery discharge aligning with winter morning peaks, highlighting the importance of matching DER dispatch to stress periods.
The methodology allows for adapting stress definitions depending on the market or buyer’s operational context.
Challenges remain in accessing granular utility data and defining precise stress signals for localized DER valuations.
Standardized hourly M&V crucial for market settlement and trust (31:11)
Moving from annual kWh savings to hourly kW capacity values enables consistent measurement across short-term dispatch and long-term efficiency projects.
Utilities require this granularity to avoid double counting and to recognize DERs as reliable grid resources.
Smart meter data or cost-effective alternatives are essential for accurate, hour-by-hour verification.
Standardization simplifies market transactions, enabling DER developers to sell capacity transparently without bespoke agreements.
Open invitation for methodology feedback and refinement (39:49)
The draft methodology is shared publicly for comments to refine capacity definitions, portfolio valuation, and seasonal adjustments.
Discussions on whether to integrate carbon savings with capacity and energy attributes are ongoing to create comprehensive certificates.
The team is exploring how to apply ELCC values to combinations of DER assets for portfolio optimization.
Feedback from industry participants is encouraged to improve applicability across diverse grid conditions and market structures.
Market and Incentive Structure Considerations
The conversation revealed tensions between existing incentive models and the need for reliable, upfront valuation of DER contributions to accelerate adoption (45:40).
Conflict between upfront incentives and post-installation M&V (45:40)
Customers want immediate incentives to fund DER investments, but M&V often requires long-term data collection.
Traditional deemed savings models persist because they provide quick estimates despite being less accurate.
Real-time or predictive M&V methods need development to balance customer needs and market integrity.
Shifting investment risk away from consumers (47:16)
Example given of data centers funding heat pumps for homes to reduce winter peak load, unlocking grid capacity and revenue.
This approach reduces financial risk on consumers while enabling large-scale capacity savings for new grid loads.
Utilities and ratepayers benefit from deferred infrastructure costs and more efficient grid use.
It creates a virtuous investment cycle with lower bills for consumers and expanded capacity for corporate buyers.
Need for market efficiency and trust (50:30)
Standardized M&V enables efficient capacity markets with transparent settlement and fair payments.
Clear capacity rights and reliable measurement incentivize private sector investments in DERs.
Without trust in M&V data, utilities and grid operators may resist adopting DER solutions fully.
The team emphasized that better M&V is foundational to unlocking the economic potential of demand efficiency.
Environmental and supply-side considerations (51:50)
McGee Young acknowledged most new generation is renewable but stressed ongoing challenges with natural gas and coal.
Demand efficiency also involves using renewables effectively by shifting consumption and storage to match supply.
The approach must blend demand-side efficiency with supply-side clean energy growth to meet broader policy goals.
Locational and Grid Specific Valuation Challenges
Granular, location-based valuation of DER impacts is essential but complex due to diverse grid characteristics and infrastructure constraints (28:37).
Importance of locational granularity in DER valuation (28:37)
DER value depends heavily on proximity to constrained grid elements, like substations or feeder lines.
Value closer to load centers or constrained feeders is higher due to direct impact on infrastructure deferral.
System-wide values like resource adequacy are more diffuse and less financially impactful locally.
Utilities’ distributed grid configurations require tailored valuation models to capture real avoided costs.
Variability of grid characteristics across regions (24:45)
Different ISOs show varying ELCC values for DERs due to unique grid mixes, load shapes, and renewable penetrations.
DER impacts vary seasonally and by time of day depending on local demand patterns and resource availability.
For example, batteries behave differently in summer vs. winter; heat pumps have distinct seasonal load impacts.
Valuation approaches must reflect this diversity to fairly compensate DER contributions.
Utility concerns about capacity rights and operational risk (56:52)
Utilities view fixed connection capacities as physical limits, and time-varying capacities pose enforcement challenges.
Without hardware or controls to enforce dynamic capacity limits, utilities fear reliability risks and lack of grid control.
This uncertainty creates resistance to market models based on flexible capacity rights.
Pierre Vogler-Finck noted that utilities’ long-term planning horizons and risk aversion complicate market adoption.
Trust and persistence risks with DER programs (57:27)
Utilities doubt the persistence and reliability of non-wire alternatives and demand response programs.
Lack of visibility into customer behavior and installed measures leads to preference for “steel in the ground.”
M&V improvements are key to building trust and overcoming utility skepticism.
McGee shared a story illustrating utilities’ mistrust of demand response without strong verification.
Strategic Industry and Regulatory Context
The discussion reflected ongoing industry shifts, regulatory drivers, and the evolving role of DERs in energy markets (00:00 & throughout).
Open EAC Alliance’s role in paradigm shift (00:00)
The quarterly meeting focused on preparing the measurement and verification industry for new demand efficiency realities.
The alliance aims to create consistent, standardized methodologies to support DER integration and market participation.
This work addresses a major transformation in how demand-side resources are valued and compensated.
The team emphasized that this shift is among the most consequential since the alliance’s inception.
Regulatory developments enabling DER markets (14:18)
FERC 2222 requires ISOs to accept aggregated demand response as equivalent to supply-side resources.
This regulatory change opens pathways for DERs to compete in wholesale markets and for corporate buyers to participate.
The alliance’s methodology supports compliance and market readiness under these evolving rules.
Utilities remain mixed in their responses, reflecting regulatory complexity and incentive misalignments.
Vision for competitive, multi-buyer DER markets (16:01)
Moving beyond sole utility buyers to allow data centers and other corporate entities to fund and own DER capacity.
This could unlock significant private investment in grid flexibility and reduce ratepayer costs.
The alliance envisions open, scalable demand-side energy markets with transparent and standardized settlements.
This vision requires robust M&V, regulatory clarity, and collaborative industry efforts.
Future steps and ongoing collaboration (59:19)
The alliance encourages ongoing input on the methodology and continued dialogue with stakeholders.
Further meetings will address unresolved questions around capacity valuation granularity, portfolio effects, and certification.
The team recognizes the complexity and invites broad participation to co-create workable solutions.
Emphasis on building trust with utilities and regulators remains a priority for successful DER integration.
Action items
McGee Young
Continue refining and sharing the draft demand efficiency methodology for open comment and collaborative improvement (34:28)
Engage in further work on granularity of capacity values regionally and seasonally, incorporating locational data like PG&E GRIP database info (28:37)
Take offline further discussions from audience questions to address technical and policy challenges on demand efficiency M&V and market design (57:52)
Stephen Suffian
Help support and detail demand efficiency measurement and verification methods, particularly coincident peak contribution and ELCC metrics (34:28)
Provide clarifications and engage with feedback on methodology draft shared with the group (59:22)
All Participants
Review and provide comments on the shared draft methodology document to improve and validate the demand efficiency measurements (34:28)