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At least 433 records · Page 24

Gaseous contaminant transfer in membrane-based air-to-air energy exchangers

Membrane-based air-to-air energy exchangers (M–AAEEs) transfer heat and moisture between building exhaust air and fresh ventilation air streams through a membrane, thereby reducing the energy required for conditioning the fresh ventilation air. Energy exchangers are typically used in buildings with relatively clean building exhaust air, such as office buildings and schools. Recently interest in using energy exchangers in a wider range of buildings has grown, to reduce the energy consumption associated with the heating, ventilating, and air-conditioning (HVAC) systems in these buildings. However, if the building exhaust air is not clean, as would be the case for laboratories or factories, new risks are encountered when using energy exchangers. It is possible that gaseous contaminants in the exhaust air may also transfer along with the moisture through the membranes, contaminating the incoming fresh ventilation air. Current test standards provide a test procedure to determine the contamination of the fresh ventilation air by measuring the transfer of an inert tracer gas in an energy exchanger. However, the tracer gas test may not represent the transfer of common indoor air contaminants due to differences in their transport properties. Therefore, in this study, an experimental facility is developed to determine the transfer of seven different contaminants through two membranes (porous and dense) at different flow rates. Contaminant transfer is quantified using a parameter called the exhaust contaminant transfer ratio (ECTR), which gives the fraction of the contaminants transferred from the exhaust air to the fresh ventilation air. A theoretical model based on the effectiveness-number of transfer units (ε-NTU) correlation and moisture transfer resistance of the membrane is presented to determine transfer through porous membranes and validated with experimental results. The major contribution of this paper is that it presents a simple method to predict the transfer of different contaminants through a porous membrane based on the moisture transfer resistance of the membrane at different operating conditions. It is found that as contaminant diffusivity decreases, ECTR generally also decreases, and as the flow rate increases, ECTR decreases, which is consistent with the predictions from the correlation.

42 ENGINEERING↗

Characterization of radiation damage effects in high-energy neutrino target graphite using low-energy ions

Exposure of graphite targets to high intensity proton beams at neutrino production facilities causes changes in the target material that can result in a shortened operation lifetime. The dominant factors in this process are currently thought to be mechanical in nature resulting primarily from microstructural effects that lead to thermal and structural changes in bulk material properties. As currently planned beam facilities with increased proton energy and intensity begin to come online it will be important to thoroughly understand these processes, and ideally to be able to predict the effects of new beam designs on target properties. Direct analysis of targets exposed to existing high-energy proton beams is complicated by several factors, such as very limited access to proton beam facilities, high associated costs, irradiation times on the order of months, and the resulting radioactivity of irradiated samples that requires special facilities for post-irradiation examination. Much of the existing literature concerning irradiation damage in graphite has been focused on the needs of the nuclear engineering community, however high-energy proton targets operate in a much different environment. In comparison to graphite irradiated in a nuclear reactor, graphite used in proton beam targets receives a higher dose rate, have greater gas production, and experience short irradiation pulses as opposed to continuous irradiation. Low-energy ion irradiation offers a method of inducing similar levels of radiation damage to high-energy protons while avoiding many of the difficulties and limitations associated with high-energy proton beams and the corresponding activated specimen testing. My research described in this thesis focused on investigating how low-energy ion irradiation could be used to induce the same or similar types of microstructural alteration and mechanical property degradation as that seen in high-energy neutrino production target graphites by varying damage le vels and irradiation temperatures prior to post-irradiation characterisation.

43 PARTICLE ACCELERATORS↗

Optimizing Ventilation Using Low-Cost Sensors to Improve Health, Safety, and Energy Efficiency

Air is the primary carrier of hazards within a space, whether it be hazardous bi-products of research activities or airborne pathogens. As a result, building ventilation is the primary defense against unseen airborne hazards. Critical laboratory facilities already demand the need for effective mitigation of exposure to research-related, airborne hazards, providing a proving ground for effective ventilation strategies that optimize safety of occupants and reduce energy use. The heart of smart laboratory building operation is dynamic, analytics-based ventilation, which requires an intimate knowledge of building environmental conditions achieved through contaminant-detection systems. Unfortunately, currently available contaminant-detection solutions are expensive, elaborate systems that raise barriers for building managers on a limited budget. Through the successful deployment of a novel low-cost, modular sensor technology, we have developed a demand-control ventilation protocol effective in improving safety and reducing energy in the critical laboratory environment. In this session, we will highlight best practices and lessons learned through this deployment that can be applied beyond laboratories without breaking the bank. This paper describes a low-cost solution for providing a safe, healthy building environment and reducing energy use through effective, efficient ventilation.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

Optimizing Ventilation Using Low-Cost Sensors to Improve Health, Safety, and Energy Efficiency

Air is the primary carrier of hazards within a space, whether it be hazardous byproducts of laboratory research activities or airborne pathogens. As a result, building ventilation is a primary defense against unseen airborne hazards. Critical laboratory facilities require effective mitigation of exposure to research-related, airborne hazards, providing a proving ground for effective ventilation strategies that optimize safety of occupants and reduce energy use. The heart of smart laboratory building operation is dynamic, analytics-based ventilation, which requires an in-depth intimate knowledge of building environmental conditions achieved through contaminant-detection systems. Unfortunately, currently many contaminant-detection solutions are expensive, elaborate systems that raise barriers for building managers. Through the successful deployment of a novel low-cost, modular sensor technology, we have developed a demand-control ventilation protocol effective in improving safety and reducing energy in critical laboratory environments. In this article, we will highlight best practices and lessons learned through this deployment that can be applied beyond laboratories. This article describes a low-cost sensor to support providing a safe, healthy building environment and reduce energy use through effective and efficient ventilation.

dynamic management of indoor air quality↗

Who Controls Energy in the Smart Home? A Multidisciplinary Taxonomy

Advances in technology have begun to open new opportunities for behavior-based and technical approaches to managing residential energy use and meet sustainability-related objectives. Visions of the future predict homes with smart technologies delivering enhanced comfort and cost savings to residents; utility-partners who can remotely optimize energy resources to meet grid needs; and occupants who play more active roles in the energy system supported by advanced information communication technologies. Each of these scenarios implies augmented control over home energy use, yet uncertainties remain regarding which ones will deliver the greatest grid benefits and services to customers in a given situation. These scenarios also raise broader questions regarding customer agency and the relationship between customers and third parties moving forward. While both the provision of information to spur behavior change and automated technologies theoretically enhance control over energy use in the built environment, these strategies are not often studied from an integrated perspective. Seeking to address this gap and develop a deeper understanding of the evolving paradigm of control over home energy use, this paper presents a taxonomy to evaluate perspectives from public policy (ex. demand-side management), technological innovation (automated controls), and user-agency (ex. the role of behavior change) on approaches to managing home energy use. We draw on theoretical and empirical evidence from across disciplines to detail the dimensions and implications of deploying programs that incorporate various levels of control and anticipate such a taxonomy will help holistically map out and evaluate tradeoffs between different approaches to demand-side management moving forward.

McIlvennie, Claire↗

Diesel Fuel Consumption in Prominent U.S. Open-Pit Mines: Site-Level Estimates

This report presents a comprehensive framework for estimating diesel fuel consumption and prices at open-pit mines in the United States. The framework includes transparent methods for calculating site-level diesel energy use when direct reporting is unavailable, and a structured confidence evaluation for each method. The framework is demonstrated to estimate current diesel consumption at 21 open-pit mines in the United States. Initial findings support ongoing efforts to strengthen the competitiveness and security of the U.S. industrial base by supporting data-driven supply chain analysis and decision-making, improved transparency in mining sector energy use, and targeted deployment of energy innovation and cost-reduction strategies. Future updates to the dataset—coupled with expanded data transparency and method validation—will help ensure that the findings remain relevant as the sector continues to evolve.

02 PETROLEUM↗

Building Energy Systems as Behind-the-Meter Resources for Grid Services: Intelligent load control and transactive control and coordination

To mitigate the impacts of climate change, significant reductions in emissions from all sectors of the economy are needed. The electricity generation sector has embarked on an ambitious plan to include renewable generation as part of its decarbonization efforts, and many cities and states are mandating all-electric buildings. While renewable resources will reduce emissions, they are not dispatchable, they vary temporally, and their generation is uncertain. Under these conditions, traditional approaches to managing grid reliability, where supply follows demand, will not be efficient and may not be cost-effective. Further, there is a more efficient alternative for balancing the supply–demand imbalance and for absorbing variability and uncertainty of renewable energy using distributed energy resources (DERs) as opposed to reserve generation. Because buildings consume more than 75% of total U.S. annual electricity consumption, behind-the-meter (BTM) DERs have a load flexibility of 77 GW of power and 90 GWh of virtual energy storage capacity nationwide (Kalsi, 2017). Therefore, some portion of the supply–demand imbalance can be met by these DERs at a lower cost compared to business-as-usual solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Deep Reinforcement Learning for Distribution System Restoration Using Distributed Energy Resources and Tie-Switches

Distributed energy resources (DERs), such as solar PVs and energy storage, can be used to restore distribution system critical loads after the extreme weather events to increase grid resilience. However, coordinating multiple DERs together with tie-switches for multi-step restoration process under renewable uncertainty is challenging. This paper proposes a deep reinforcement learning to control discrete actions of switching on/off tie switches and DERs for critical load restoration. The restoration problem is first cast into the Markov decision process suitable for DRL. Then, the original soft actor critic (SAC) method for continuous actions has been extended to handle discrete and continuous actions. Numerical comparison results with other stochastic optimization-based approaches on the modified IEEE 33-bus system show that the proposed method can achieve fast critical load restoration in the presence of substation power outage while maintaining system voltage limit throughout the restoration process.

active distribution systems↗

National Cost-effectiveness of ANSI/ASHRAE/IES Standard 90.1-2016

The purpose of this analysis is to examine the cost-effectiveness of the 2016 edition of ANSI/ASHRAE/IES Standard 90.1 (ASHRAE 2016). Standard 90.1 is developed by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Standard Standing Project Committee (SSPC) 90.1. It is the model energy standard for commercial and multi-family residential buildings over three floors (42 USC 6833). PNNL analyzed the cost-effectiveness of changes in Standard 90.1 from 90.1-2013 to 90.1-2016, as applied in commercial buildings across the United States. During the development of new editions of Standard 90.1, the cost-effectiveness of individual changes (addenda) is often calculated to support the deliberations of ASHRAE Standard Standing Project Committee (SSPC) 90.1. The ASHRAE process, however, does not include analysis of the cost-effectiveness of the entire package of addenda from one edition of the standard to the next, which is of particular interest to adopting State and local governments. Providing States with an analysis of cost-effectiveness may encourage more rapid adoption of newer editions of energy codes based on Standard 90.1. This information may also inform the development of future editions of Standard 90.1. To establish the cost-effectiveness of Standard 90.1-2016, three main tasks were addressed: (1) Identification of building elements impacted by the updated standard; (2) Allocation of associated installation, maintenance, and replacement costs; and (3) Cost-effectiveness analysis of required changes In addition to installation, maintenance, and replacement costs, energy cost differences were needed to determine cost-effectiveness. The energy costs for each edition of Standard 90.1 were determined previously under the development of Standard 90.1-2016, as described below. The current analysis builds on the previous PNNL analysis (as outlined in Section 5.2) of the energy use and energy cost saving impacts of Standard 90.1-2016 compared to previous editions. The overall energy savings analysis of Standard 90.1 utilized a suite of 16 prototype EnergyPlus building models in 15 climate locations representing all eight U.S. climate zones. Detailed methodology and overall energy saving results from Standard 90.1-2016 are documented in the DOE technical report titled Energy Savings Analysis: ANSI/ASHRAE/IES Standard 90.1-2016 (DOE. 2018b).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Solar Pathways in Federal Energy Assistance Programs: Expanding the Low-Income Home Energy Assistance Program (LIHEAP) and the Weatherization Assistance Program (WAP)

The U.S. Department of Health and Human Services Low-Income Home Energy Assistance Program (LIHEAP) and U.S. Department of Energy Weatherization Assistance Program (WAP) are federal programs to help low-income households reduce their energy costs. LIHEAP provides direct assistance to help households cover energy costs and stay connected to utility services, as well as weatherization and minor energy-related repairs, and WAP provides no-cost energy efficiency measures to reduce energy use and energy bills while also improving home comfort for income-qualified households. Across the U.S., states are implementing or considering solar energy as an eligible measure for LIHEAP and/or WAP funding, but the successful implementation pathways remain largely undocumented. This report fills that gap by analyzing states' LIHEAP and WAP annual plans, surveying administrators from LIHEAP grant recipients and WAP grantees about their challenges implementing solar or barriers to doing so, and conducting interviews and workshops with program administrators.

14 SOLAR ENERGY↗

Makah Tribe Strategic Energy Plan

The U.S. Department of Energy’s (DOE) Energy Transitions Initiative Partnership Project (ETIPP) connects remote and island communities, regional partners, and the DOE national laboratories to support communities as they seek to build resilience in their energy systems. The Makah Tribe faces several energy challenges, including frequent power outages and the potential for an extended outage due to an earthquake or tsunami. The Tribe joined ETIPP in 2022 to address those challenges, seeking to build energy resilience and sovereignty in the community. The Makah Tribe, Spark Northwest, the Pacific Northwest National Laboratory (PNNL), and the National Renewable Energy Laboratory (NREL) collaborated to develop a strategic energy plan as part of the second cohort of ETIPP communities. The long-term energy vision of the Makah Tribe includes increasing energy efficiency in the community, improving energy management capacity, and developing the renewable energy generation and storage sufficient to independently power the Reservation for one year. Additionally, the ETIPP team worked with Makah leadership, staff, and community members to identify a set of community priorities, values, and goals to guide energy development as the Tribe takes the incremental steps toward their vision for energy sovereignty. Those energy values include ecosystem-based management, energy sovereignty and project ownership, workforce development and capacity, economic opportunity, community wellbeing and priorities, and emergency disaster resilience. To understand what would be needed for a year for energy independence, the PNNL team conducted an assessment to determine the current energy usage of the Tribe and also modeled several scenarios for future energy use. Using the energy usage values, the team estimated how two types of renewable energy technology, specifically locally deployed solar and small-scale wind, could contribute towards the energy independence goal. The energy baseline and resource assessment produced the following key findings:

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

ResStock Technical Reference Documentation (V.3.3.0)

ResStock™ is the best-in-class building stock energy model for simulating and publishing energy use, utility bills, and greenhouse gas emissions from the residential sector of the U.S. ResStock answers two primary questions: (1) How is energy used in the U.S. residential building stock? and (2) What is the timeseries aggregate impact of energy technologies? Specifically, ResStock quantifies energy use across geographical locations, demographic groups, building types, fuels, end uses, and time of day. Additionally, it details the impact of efficiency or electrification measures: total changes in the amount of energy used by measure; where or in what use cases efficiency or electrification upgrade measures save energy; when or at what times of day savings occur; and which building stock or demographic segments have the biggest savings potential. This model, and the datasets it produces, are foundational to identifying pathways to affordable and equitable decarbonization of the U.S. residential buildings sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Achieving 50% Energy Savings in Chicago Homes: A Case Study for Advancing Equity and Climate Goals

Since 2019, the National Renewable Energy Laboratory (NREL) and Elevate have collaborated to identify pathways to deep energy retrofits in Chicago's housing stock, document equity implications and co-benefits of this transition, and validate the findings by implementing retrofits in real Chicago homes. This document summarizes our analysis process to model advanced retrofit packages that lead to greater than 50% energy savings in Chicago homes. Based on these findings, we have also developed a roadmap with the City to guide implementation, and are deploying the recommended retrofit packages in real Chicago homes to realize these energy savings. This work was developed in collaboration with two key stakeholders - the City of Chicago and Commonwealth Edison (ComEd) - and funded by the U.S. Department of Energy (DOE). NREL's Residential Buildings team maintains the best-in-class ResStock™ energy model of the U.S. residential building stock. For this work, we calibrated ResStock to Chicago's unique local housing stock to accurately simulate energy use in Chicago homes both for current conditions and with various retrofit scenarios. We simulated a wide range of potential building retrofits covering all aspects of residential energy use and then grouped these into packages based on energy and utility bill savings. ResStock can model diverse building types and housing characteristics, so we're able to observe the range of outcomes that might occur when these upgrades are deployed across the entire housing stock. We can then estimate potential energy savings from an advanced retrofit program on Chicago's housing stock by comparing the modeled energy use before versus after a retrofit. This novel version of ResStock, calibrated to Chicago with data from Elevate, can help City officials, ComEd, and other partners plan for community-scale decarbonization via residential retrofits. Specifically, this work contributes the following project goals: Develop a building retrofit prioritization strategy for Chicago single-family and 2- to 4-unit buildings; Identify neighborhoods and home types that have the highest potential for savings from electrification; and Assess the impact of advanced building retrofits on energy use, utility bills, and CO2 emissions at the city and building level. Although this study is specific to Chicago, its methods and learnings are applicable across the United States. These findings are especially notable for heat pumps and electrification retrofits in cold climates.

building energy modeling↗

Characteristics of U.S. Energy Production using Nuclear Fission

When considering potential energy production technologies for the future, a critical consideration centers on the question of “how green” the technology is. Here, the word “green” implies that the technology has a zero or minimal impact on the public and environment while still providing benefits by way of electricity, heat, and other products such as hydrogen and water. And, these potential impacts must be considered over the lifecycle of the technology deployment, from design, construction, operation, and disposition. Ideally, a green energy technology would be net-zero (i.e., having no to almost negligible contribution) on five key elements: 1. Greenhouse gas emissions, including carbon dioxide (CO 2 ), methane, nitrous oxide, and fluorinated gases such as ozone-depleting gases 2. Water consumption 3. Material resource consumption 4. Disposition of wastes 5. Public, flora, and fauna safety including deaths, health, and environmental impacts. Society would benefit from net-zero impacts of the five elements above while having low-cost energy. As society starts to replace fossil fuels in the energy mix, we need to consider the possible impacts of adopted technologies. We need a production approach that provides large quantities of energy while being safe, reliable, economical, and sustainable. In this report, we describe a variety of characteristics related to the five elements above to provide a fact-supported, science-based depiction of nuclear fission as an energy providing technology. By better understanding how fission power is nearly net-zero in the five elements above, we can position our thinking to align with the overarching goal to provide society with a low-impact energy source.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Energy Intensity Baselining and Tracking Guidance

Each company joining the U.S. Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) commits to establishing an energy consumption and energy intensity (EI) baseline and to tracking its energy performance over a 10-year period against that baseline. The baseline must reflect a company’s energy consumption over a 12-month period, covering all its U.S.-based operations. Energy consumption is calculated by fuel type in terms of primary energy (also known as source energy). EI is broadly defined as the amount of energy consumed per unit of output produced. For this guidance document and for the program, the term energy performance represents an evaluation of a facility’s capacity to use energy efficiently. Metrics used to assess a facility’s energy performance can include EI, energy consumption, improvements in EI, etc. Establishing an energy baseline and tracking system is a critical first step in effectively managing energy use. Developing a baseline can help a company understand energy use within the corporation and give it a point of comparison to evaluate future efforts to improve energy performance. It can also support efforts to validate a company’s energy management activities, improve comparative analyses when using benchmarks, and help in predicting future energy needs. In addition, a company that normalizes its performance data can determine highly defensible measures of energy savings generated through implemented energy efficiency projects. Establishing a baseline and tracking energy performance is also a requirement for ISO 50001 certification. Although basic energy data can be collected through utility bills, most manufacturers will have to perform additional analyses to develop accurate and robust energy baselines and tracking systems. Energy is consumed in many ways within the manufacturing sector and can come from multiple sources. Energy is sometimes generated and sold to other parties or captured and reused on-site. External events can exert a significant impact on a facility or company’s energy use independent of any purposeful efforts to improve energy efficiency. Operational changes, such as production shifts—which may be inevitable for some companies over the 10-year period covered by the program—can also make a big difference in energy use. Since Better Plants asks companies to account for all their U.S.-based operations, mergers, acquisitions, and divestitures can also have significant implications for a company’s energy metrics. This document aims to demystify the sometimes complex baselining process. It devotes special attention to the task of normalizing and adjusting energy consumption to account for external factors, such as weather and production changes. A key recommendation is that companies use regression analysis to normalize their energy consumption data whenever possible. Regression analysis is a statistical technique that estimates the dependence of a variable (i.e., energy use in the context of Better Plants) on one or more independent variables such as ambient temperature, while controlling for the influence of other variables at the same time. A properly developed regression analysis can provide a reliable estimate of energy savings resulting from energy improvement strategies and projects by accounting for the effects of variables such as annual production levels and weather. DOE has developed a companion Energy Performance Indicator software tool (EnPI) to simplify the baselining process. This tool can run regression models, calculate changes in EI at the facility level, and automatically compile facility-level data into a corporate-wide metric. Note that although the relevant equations used to calculate EI are provided in this document, the EnPI tool will automatically perform most calculations for the user. Additionally, Better Plants Partners (Partners) can call on their Technical Account Manager (TAM) to help them establish a baseline and assist with the necessary calculations to track progress.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Chapter 2 Biomass Currently Used for Energy and Coproducts

Jacobson, R., and S. Curran. 2024. “Chapter 2: Biomass Currently Used for Energy and Coproducts.” In 2023 Billion‐Ton Report. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. doi: 10.23720/BT2023/2316167.

BT23↗

Remote Alaska Communities Energy Efficiency Competition: Energy Efficiency for the Gem of the Yukon (Final Report)

Over the past decade, the City of Ruby has been proactive in working to reduce cost and energy use in the community. Ruby (Tl’aa’ologhe) is a remote city in Alaska located on the south bank of the Yukon River near the Kilbuck-Kuskokwim Mountains, about 50 air miles east of Galena and 230 air miles west of Fairbanks. As of 2019, the community has a population of over 150 people and most of Ruby’s residents are Koyukon Athabascan. Ruby has a long history of promoting local efficiency and clean energy in an effort to become more sustainable. Between 2007-2010, the community hosted Alaska’s first demonstration of an in-river hydrokinetic test project, sponsored by the Yukon River Inter-Tribal Watershed Council. In 2011, a 5kW solar photo-voltaic (PV) array was installed by the Interior Regional Housing Authority. In 2012, the community had a new power plant constructed by the Alaska Energy Authority that supplies waste heat to the washeteria, clinic and public safety garage, saving the community more than 4,000 gallons of heating fuel per year. The clinic, constructed by the Tanana Chiefs Conference, is one of the most energy efficient buildings in the interior and utilizes new building efficiency standards that were passed by the tribes. It has a 5kW solar PV array that provides energy into the local electric grid and offsets approximately 20% of the annual energy use. Building on this legacy, the City of Ruby entered into Department of Energy’s (DOE’s) Remote Alaska Communities Energy Efficiency Competition (RACEE) in 2016, pledging to reduce per-capita energy use 15% by 2020. During the second phase of the competition, 13 communities including Ruby were provided funding for tailored technical assistance to measure energy use and create energy efficiency plans.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Geological Thermal Energy Storage Using Solar Thermal and Carnot Batteries: Techno-Economic Analysis

Energy storage is increasingly necessary as variable renewable energy technologies are deployed. Seasonal energy storage can shift energy generation from the summer to the winter, but these technologies must have extremely large energy capacities and low costs. Geological thermal energy storage (GeoTES) is proposed as a solution for long-term energy storage. Excess thermal energy can be stored in permeable reservoirs such as aquifers and depleted hydrocarbon reservoirs for several months. In this article, we describe a techno-economic model that has been developed to evaluate GeoTES systems. The models are developed by combining the output of specialist models, which enables the performance and cost of both the subsurface and surface systems to be captured. Off-design models are developed so that the performance can be evaluated at each hour of the year. GeoTES can be charged with two different energy sources: (1) concentrating solar thermal and (2) renewable electricity using heat pumps (henceforth known as a "Carnot Battery"). The stored thermal energy can be used to generate electricity and, uniquely, also directly produce heat that can be used by industrial processes. Furthermore, Carnot Battery GeoTES can also be used to form a cold storage reservoir. Preliminary results that quantify the technical and economic performance of these two GeoTES systems are presented.

carnot battery↗