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DOE OSTI2024

Comminty Geothermal: Planning and Design of a Heating and Cooling System in Framingham, Massachusetts

These reports, plans, and drawings review the achievements of Home Energy Efficiency Team (HEET) and its partners to plan and design a network of interconnected ground-source heat pump systems, or geothermal network, in an area encompassing multiple environmental justice (EJ) neighborhoods in the City of Framingham, MA. The materials provided in this dataset include, a) stakeholder and design best practices, b) study on optimal method to interconnect geothermal loops, c) guidelines for monitoring and metering, d) operations and maintenance plans, e) permitting guidelines and f) 10-day driller tutorial curriculum. These materials can guide the efficient and ethical design of future geothermal networks nationwide. The capacity of the system is estimated at 217 tons and is designed to provide 100% of heating and cooling needs for the buildings connected to the loop. In this project, 80 boreholes are used as the main thermal resources, the distribution system (or loop) consists of 0.61 miles of an 8-inch single-pipe at ambient temperature, with the capacity to connect 44 buildings, including 13 apartment buildings from the Framingham Housing Authority, one transitional home, one school building and 29 single family homes. While Framingham already has a geothermal network loop that is currently in the commissioning stage, our proposed project is unique because it is the first utility-led expansion loop (2nd loop) project that will connect to an adjacent existing geothermal loop (1st loop) in a pre-existing neighborhood. Both the 1st and 2nd loops are being installed, owned and operated by Eversource Energy, the utility Deployment Partner.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Modular Integrated System for Carbon-Neutral Methanol Synthesis Using Direct Air Capture and Carbon-Free Hydrogen Production

This study investigates the development and economic analysis of a modular integrated system for carbon-neutral methanol synthesis, leveraging direct air capture (DAC) and solid oxide electrolysis cells (SOEC) for carbon dioxide and hydrogen production, respectively. The proposed system integrates a novel building-based DAC process, functionalized solid sorbents, and low-energy SOEC technology, aiming to minimize operational and capital costs. A comparison between the base case system (1,000 t methanol/year) and a scaled-up model (14,758 t methanol/year) reveals significant improvements in efficiency and economic feasibility. The scaled-up system achieves a levelized cost of methanol (LCOM) of $740/t, a 7.5% reduction compared to that of conventional DAC-based systems, while utilizing existing building HVAC infrastructure for air handling. Detailed sensitivity analyses were conducted, evaluating the effects of plant capacity and air flow rate on the LCOM, demonstrating the scalability of the building-based DAC system. The cradle-to-gate life cycle analysis shows that the proposed process using renewable-sourced electricity achieves a 38% reduction in greenhouse gas (GHG) emission compared to reported values of green methanol production technologies that use a conventional DAC and a conventional methanol synthesis catalyst. When fossil-sourced electricity is used in the proposed process, it leads to about a 37.5% reduction in GHG emission in comparison to reported values for conventional methanol production technologies using steam methane reforming technology and fossil-sourced electricity.

alcohols↗

DOE OSTI2025

Winds of fortune? Understanding the geographic, sociodemographic, and temporal distribution of benefit mechanisms from land-based wind projects in the United States

Despite decades of research on factors shaping local responses to wind development, there is relatively little known about benefit mechanisms (e.g., agreements, funds, donations) used by developers in the U.S. land-based wind sector. To address this gap, we collected benefit mechanism data across all current utility-scale land-based wind projects installed between 1982 and 2024 (n = 1047), finding that just under one-third of projects had a benefit mechanism attached to them. We find the use of benefit mechanisms has become more common over time, is associated with larger projects, and varies by region. In terms of host community characteristics, the use of benefit mechanisms is associated with characteristics like higher education level, higher percent white, higher percent Republican, higher decision-making capacity, lower unemployment rate, and higher poverty rate. Building on a theoretical framework of purposes, we discuss what these findings could suggest about the motivations driving developers' use of these mechanisms, such as increasing local acceptance of a wind project or supporting distributive fairness. This first-of-its-kind study builds a comprehensive understanding of how benefit mechanisms have been used in the U.S. wind industry throughout its history, which can inform future approaches to benefit-sharing across sectors.

17 WIND ENERGY↗

DOE OSTI2024

Climate change and its influence on water systems increases the cost of electricity system decarbonization

The electric sector simultaneously faces two challenges: decarbonization to mitigate, and adaptation to manage, the impacts of climate change. In many regions, these challenges are compounded by an interdependence of electricity and water systems, with water needed for hydropower generation and electricity for water provision. Here, we couple detailed water and electricity system models to evaluate how the Western Interconnection grid can both adapt to climate change and develop carbon-free generation by 2050, while accounting for interactions and climate vulnerabilities of the water sector. We find that by 2050, due to climate change, annual regional electricity use could grow by up to 2% from cooling and water-related electricity demand, while total annual hydropower generation could decrease by up to 23%. To adapt, we show that the region may need to build up to 139 GW of additional generating capacity between 2030 and 2050, equivalent to nearly thrice California's peak demand, and could incur up to $\$$150 billion (+7%) in extra costs.

13 HYDRO ENERGY↗

DOE OSTI2026

Launch Alaska Transportation and Energy Accelerator (LATEA)

The Launch Alaska Transportation and Energy Accelerator (LATEA), funded through the U.S. Department of Energy Office of Technology Commercialization’s Energy Program for Innovation Clusters (EPIC),advanced deployment of innovative and efficient transportation and energy technology in Alaska from October 2021 through June 2025. The project was designed to leverage Launch Alaska’s accelerator model to identify, recruit, and support transportation technology companies with novel solutions to market needs while building the stakeholder networks, demonstration opportunities, and institutional capacity necessary to accelerate commercialization in one of the most challenging operating environments in the United States.

08 HYDROGEN↗

DOE OSTI2025

Techno-economic feasibility of borehole thermal energy storage system connected to geothermal heat pumps for seasonal heating load of two buildings in Fairbanks, Alaska

Borehole thermal energy storage (BTES) is an effective solution for managing imbalanced heating and cooling loads in cold regions. This study evaluated the long-term feasibility of a BTES system in the Fairbanks area, Alaska, through building energy modeling, resource characterization, and numerical modeling. The system was designed to store waste heat from a nearby coal power plant during summer and provide thermal energy during winter to geothermal heat pumps supplying heating loads in two buildings. Heating load profiles were modeled for the buildings using EnergyPlus, and the results indicated the annual heating load was 5.6 times greater than the cooling load. 40 borehole heat exchangers were pre-designed approximately 100 m away from the two buildings in terms of land availability and regulatorily optimized depth. The 20-year performance of the designed BTES system under two operational scenarios—one with a 5-year preheating period and one without—was numerically modeled using subsurface temperature and properties characterized through the literature review and thermal response tests. Both scenarios demonstrated that the BTES has the capacity to fully cover the heating loads in the two buildings throughout the 20-year lifetime. Production temperatures at central wells were 33 % higher on average than at outer wells in both scenarios. The 5-year preheating period increased subsurface and extraction temperatures, and correspondingly annual average and total thermal energy production was higher for 8 years than in the scenario without the preheating period. These results highlight the long-term reliability and sustainability of the BTES system in meeting heating demands over its lifetime, with the preheating period offering potential performance improvements. Implementing the BTES system in cold regions with high heating demand, such as Fairbanks, Alaska, could provide a long-term, sustainable energy solution for managing imbalanced heating and cooling loads.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Carbon Capture, Transport, And Storage (CTS) Cost Modeling Of The Onshore Gulf Coast

The onshore Gulf of Mexico region presents significant opportunities for CO2 capture, transport, and storage due to its numerous CO2 sources, such as power plants, refineries, and its substantial CO2 storage potential. However, operators face critical decisions in designing an efficient and cost-effective CO2 pipeline network. This study examines the economic implications of two primary strategies: constructing a trunkline with excess initial capacity versus developing dedicated pipelines incrementally as new CO2 sources come online. Building a trunkline first offers the advantage of future-proofing the network, allowing for the accommodation of increased CO2 volumes from various sources over time. However, this approach incurs higher upfront costs and risks underutilizing the transport capacity in the initial stages, potentially resulting in economic inefficiencies. Conversely, constructing dedicated pipelines for each new CO2 source as it becomes operational may avoid the initial overcapacity issue but fails to capitalize on the economies of scale. This could lead to higher overall costs due to the duplication of infrastructure and increased complexity in network management. This research employs a comprehensive cost-benefit analysis, integrating factors such as capital expenditure, operational costs, projected CO2 volumes, and potential economies of scale. Through this analysis, we aim to provide operators with insights into the most economically viable strategy for CO2 pipeline network design in the region. The findings underscore the importance of strategic planning and highlight the trade-offs between immediate capacity utilization and long-term cost savings, ultimately guiding stakeholders towards informed decision-making in the development of CO2 transport infrastructure. Presented at the 41st USAEE/IAEE North American Conference, 3-6 November 2024, Baton Rouge, LA, United States.

Shih, Chung Yan↗

DOE OSTI2025

Learning from Arctic Microgrids: Cost and Resiliency Projections for Renewable Energy Expansion with Hydrogen and Battery Storage

Electricity in rural Alaska is provided by more than 200 standalone microgrid systems powered predominantly by diesel generators. Incorporating renewable energy generation and storage to these systems can reduce their reliance on costly imported fuel and improve sustainability; however, uncertainty remains about optimal grid architectures to minimize cost, including how and when to incorporate long-duration energy storage. This study implements a novel, multi-pronged approach to assess the techno-economic feasibility of future energy pathways in the community of Kotzebue, which has already successfully deployed solar photovoltaics, wind turbines, and battery storage systems. Using real community load, resource, and generation data, we develop a series of comparison models using the HOMER Pro software tool to evaluate microgrid architectures to meet over 90% of the annual community electricity demand with renewable generation, considering both battery and hydrogen energy storage. We find that near-term planned capacity expansions in the community could enable over 50% renewable generation and reduce the total cost of energy. Additional build-outs to reach 75% renewable generation are shown to be competitive with current costs, but further capacity expansion is not currently economical. We additionally include a cost sensitivity analysis and a storage capacity sizing assessment that suggest hydrogen storage may be economically viable if battery costs increase, but large-scale seasonal storage via hydrogen is currently unlikely to be cost-effective nor practical for the region considered. While these findings are based on data and community priorities in Kotzebue, we expect this approach to be relevant to many communities in the Arctic and Sub-Arctic regions working to improve energy reliability, sustainability, and security.

25 ENERGY STORAGE↗

DOE OSTI2026

Multiscale characterization of phase change materials for building thermal energy storage applications

Phase change materials (PCMs) store and release large amounts of thermal energy because of their high latent energy storage capacity. However, long-term cyclic stability, supercooling and performance-scalability are some of the major challenges for their use in building thermal energy storage (TES) applications. Here, in this study, we present a comprehensive multiscale characterization of two commercially available organic PCMs, Puretemp 18 and Puretemp 23. At the microscale, differential scanning calorimetry (DSC) was used to characterize phase change temperature, specific heat, and latent heat. At the mesoscale, a heat flow meter apparatus (HFMA), following the ASTM C1784 standard, was employed to measure the phase change temperature, specific heat, and latent heat properties. A comparative analysis of latent heat as a function of temperature was conducted by integrating the DSC and HFMA results. At the macroscale, the thermal performance and cyclic stability of the TES system was evaluated using Puretemp 23. The TES system consisted of a finned tube heat exchanger with a storage volume of 0.0189 m 3 (5 gal), which represents a compact, real-world TES solution suitable for building energy storage. The results showed consistent thermal stability of the PCM over 200 cycles, and the supercooling temperature remained within 0.2 °C, which was not detected in smaller-scale characterization methods. Additionally, the macroscale testing methodology of the PCM revealed that the TES is able to charge and discharge stored latent energy within 2 h under a temperature differential of 16.67 °C measured between the inlet water temperature and the phase transition temperature of the PCM. The proposed multiscale PCM characterization method provides a systematic basis for comparing important thermal storage properties while also investigating the scalability, reliability and integration challenges in large scale TES applications.

Latent heat↗

DOE OSTI2025

Energy innovation in the US buildings sector: Setting the stage and mapping the future

Jared Langevin is a staff scientist at Lawrence Berkeley National Laboratory, where he leads modeling of US buildings sector innovation and its implications for energy demand, consumer costs, and the power grid. Eric Wilson is a senior research engineer in the Building Technologies and Sciences Center at the National Renewable Energy Laboratory (NREL). Much of his 15-year career at NREL has revolved around modeling and analysis of the US building stock. Jared and Eric co-led the development of a National Blueprint for buildings sector innovation while serving as advisors to the US Department of Energy’s Deputy Assistant Secretary for Buildings and Industry.

Langevin, Jared↗

DOE OSTI2025

Demonstration of a Novel Technology to Manage Electricity Demand in Grid-Independent Military Microgrids

This research was conducted by the National Renewable Energy Laboratory (NREL) in collaboration with the S&C Electric Inc. through funding provided by the ESTCP. The project demonstrates use of cybersecure Automated Demand Response (ADR) technology to effectively manage microgrid loads during grid-independent, also known as "islanded," operation. When military microgrids become isolated from the main electrical grid, they are required to balance electricity supply and demand locally. Given that local generation may be constrained, the prevailing strategy involves shedding all but the most critical loads by tripping smart circuit breakers, which then necessitate manual resetting. This approach is generally implemented at the building level, which means that the buildings with mission-critical activities are exempt from load management and remain fully powered, whereas those deemed non-critical can experience a complete loss of service. In this research we developed a method that allows building automation systems to selectively control their assets in response to load shedding request from a microgrid controller, avoiding total loss of service in contrast to the conventional control approach. A commercial OpenADR client server by GridFabric is used for communication between the microgrid controller and the building management system (BMS). The microgrid controller monitors both generation capacity and various assets within the microgrid and issues a demand reduction request when necessary. This request is communicated to the OpenADR server via Modbus. Upon receiving the request, the OpenADR server forwards it to the BMS utilizing the OpenADR protocol. The BMS is pre-configured with various levels of load reduction strategies based on the controllable assets available, allowing for a nuanced approach to demand reduction. Both lab and field tests were performed that considered load shedding needed to achieve closed transition into island mode and to accommodate changing loads and power source availability while islanded. A commercial microgrid controller was used for these tests with normal programming within the expected constraints of the system capabilities. That is, the solution did not require any specialized modification to the code base of the controller. Given the latency of the round-trip communication path between the microgrid controller and the various devices involved with the load shed processes, there are certain scenarios for which the demonstrated solution are appropriate and some which are not. The methods described in this report can be used for load shedding/restoration during transitions between islanded and grid-tied modes of operation, as well as accommodating normal variations in load and the need to remove a power source from operation for maintenance. These methods should not be used for scenarios that require load shedding within a second or two such as sudden and unanticipated significant load increases or loss of power sources through equipment faults.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop: Preprint

Geothermal cost and performance evaluation implemented via technoeconomic assessment (TEA) modeling is critical for the Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for the Annual Technology Baseline (ATB). The ATB data are inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL’s reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the US generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on technoeconomic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next generation technologies such as closed loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

Annual Technology Baseline↗

DOE OSTI2025

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop

Geothermal cost and performance evaluation implemented via techno-economic assessment (TEA) modeling is critical for the U.S. Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for NREL's Annual Technology Baseline (ATB), which provides inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL's reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the U.S. generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on techno-economic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next-generation technologies such as closed-loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

annual technology baseline↗

DOE OSTI2025

Improved internal short circuit models for thermal runaway simulations in lithium-ion batteries

Thermal runaway (TR) modeling is one of the primary tools that can be used to overcome challenges associated with lithium-ion battery (LIB) safety. Among all LIB accidents that have occurred over the past decade, Internal Short Circuit (ISC) remains the most common trigger mechanism. Many available models in the literature either use a simplified approach to simulate ISC or completely ignore its contribution. The aim of this study is to understand the nature of the heat released for different types of ISC scenarios, including aluminum-anode, anode–cathode, and copper-cathode ISC. We study ISC behavior using a coupled electrochemical–thermal model with an integrated TR chemical kinetics solver built in the COMSOL Multiphysics framework. The time duration of heat release and the magnitude of the peak ISC current are studied as functions of parameters such as the size of the penetrating filament and the capacity of the cell. The numerical results are used to build an empirical model validated against the published experimental TR propagation data. Our model can be successfully used as a viable low-cost substitute in lower order (lumped) TR simulations to enable TR prevention and mitigation.

Singh, Bakhshish Preet (ORCID:0000000264751992)↗

DOE OSTI2025

MSD CoP Webinar: Energy and AI

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Projections of the need for new data centers to support Artificial Intelligence (AI) are large but highly uncertain. Recent projections indicate up to a 15% annual growth rate in data center electricity demand within the next 5-10 years. Given that most electric utilities are required to have a reserve margin of roughly the same magnitude as the projected growth in demand, these new data center loads could soon threaten resource adequacy and reliability unless data centers build their own generation, interruptible loads are negotiated, commensurate new capacity and/or transmission is built, or some combination of these options. Similarly, depending on the cooling technology and geographic location of new data centers, they could threaten water adequacy in water scarce regions. This webinar will provide an overview of the interactions between energy and AI and highlight two MSD projects exploring the grid and water implications of new data centers to support AI. Presenters : Dr. Casey Burleyson (Pacific Northwest National Laboratory); Dr. Stephanie Morris (Pacific Northwest National Laboratory); Kendall Mongird (Pacific Northwest National Laboratory) Moderator: Patrick M. Reed (MSD CoP Facilitation Team) This webinar was held on: June 16th, 2025 from 1-2 PM EST.

Artificial Intelligence↗

DOE OSTI2025

Energy and AI: Evaluating Future Grid and Water Stress Due to Data Centers

Projections of the need for new data centers to support Artificial Intelligence (AI) are large but highly uncertain. Recent projections indicate up to a 15% annual growth rate in data center electricity demand within the next 5-10 years. Given that most electric utilities are required to have a reserve margin of roughly the same magnitude as the projected growth in demand, these new data center loads could soon threaten resource adequacy and reliability unless data centers build their own generation, interruptible loads are negotiated, commensurate new capacity and/or transmission is built, or some combination of these options. Similarly, depending on the cooling technology and geographic location of new data centers, they could threaten water adequacy in water scarce regions. This presentation highlights the grid and water implications of new data centers to support AI.

Mongird, Kendall (ORCID:0000000328077088)↗

DOE OSTI2026

An approach for fast and accurate simulation of phase change material based thermal energy storage in buildings

Latent heat thermal energy storage (LHTES) has significant potential for mitigating peak electricity demand and enabling load shifting in buildings. Phase Change Material embedded heat exchangers (PCM-HX) can significantly improve energy demand management due to high storage capacity. However, PCM-HX evaluation typically depends on computationally expensive fully transient simulations, posing significant challenges for scalable system- and building-level energy assessments across different climates and system architectures. This paper presents a generalized, accurate, and computationally efficient methodology for simulating building energy systems integrated with LHTES. The PCM-HX transient performance is represented by performance maps generated using a Generalized Resistance-Capacitance Model (GRCM) that enables accurate predictions of arbitrary PCM-HXs at low computational cost. The feasibility of the proposed approach was verified using a case study considering a dual-mode heat pump-thermal energy storage (HP-TES) system simulated in Modelica with Spawn of EnergyPlus™ for a DOE prototype small office building in two locations: Tampa, FL, and International Falls, MN. The PCM-HX performance maps provided accurate predictions of PCM-HX transient behavior, with mean absolute percentage deviations within 2–4% compared to GRCM while also achieving at least 1800× reduction in computational time. Moreover, the HP-TES system achieved energy savings of up to 17.4% in Tampa, FL, and 62.2% in International Falls, MN, demonstrating the broader applicability of the proposed methodology across different climate zones. This work highlights the importance of robust PCM-HX models in enabling accurate and computationally efficient building-level simulations and enabling future research opportunities for investigating optimized HP-TES designs and advanced control strategies for grid-interactive buildings.

Modelica↗

DOE OSTI2026

Oversizing and Part-Load Problems

Oversizing, the common engineering practice of specifying devices with capacity exceeding the actual load requirement, is a widespread practice across virtually all building technologies end-use categories, including HVAC, electrical systems, lighting, appliances, and plug loads. This practice, driven by factors like design uncertainty, institutional pressures, and risk aversion, results in wasted capital investment, control difficulties, and excessive energy consumption due to inefficient part-load operation. Part-load operation, where devices run below maximum capacity, is the dominant operating mode in most energy systems and presents a complex design challenge. Solutions to match output to load fall into three broad categories: constraining the output, adjusting the device’s internal behavior, and linking output to energy storage or other waste-heat reuse applications. The energy implications of part-load are critical, as efficiency often drops sharply as load decreases across a wide diversity of devices. To quantify the extent of this problem, we derive a dimensionless Part-Load Metric (PLM) based on device efficiency and its frequency distribution of operating hours at various output levels. The PLM quantifies the deviation of a device's actual efficiency from its maximum design efficiency. This metric also serves as a measure of "capital inefficiency," enabling engineers to compare the impact of different part-load solutions and providing a unified framework for evaluating performance across various devices and systems.

Meier, Alan↗