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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Techno-Economic Analysis and Market Potential of Geological Thermal Energy Storage (GeoTES) Charged With Solar Thermal and Heat Pumps

In this project, we developed a techno-economic analysis (TEA) model that can be used to evaluate the viability of a proposed Geological Thermal Energy Storage (GeoTES) design. This MATLAB-based model integrates distinct subsystem models for the reservoir, wells, power cycle, and solar field to capture their distinct characteristics. It applies this approach in simulating GeoTES storage and dispatch operations for durations ranging from hourly to seasonal. Using cases studies based on GeoTES designs provided by industry partners - Premier Resource Management (PRM) and EarthBridge Energy - we validated the TEA model estimations of system performance and costs (such as thermal and electrical power/energy inflow and outflow, capital costs, and levelized costs of energy and storage) for both concentrating solar thermal (CST) and Carnot Battery (CB) pairings with GeoTES (CST-GeoTES and CB-GeoTES). For the CST-GeoTES case, the model was validated against the proposed system designed by PRM. It showed good agreement with PRM's estimations when well and pump costs derived from PRM's estimations were used. When GETEM-based costs were used, there was a slight overprediction due to GETEM's project/site agnostic assumption of these costs. From a sensitivity analysis perspective, the levelized cost of electricity (LCOE) of the CST-GeoTES case was most sensitive to well flow rate and the charging temperature. An optimal design scenario resulted in an LCOE of 0.11 $\$$/kWhe. CST-GeoTES can also provide a source of heat to meet seasonal demands. With 12-hour and 24-hour levelized cost of heat (LCOH) of 0.018 $\$$/kWhth and 0.022 $\$$/kWhth, respectively, CST-GeoTES could be competitive in the California market with an average industrial price of natural gas in California between 0.041-0.047 $\$$/kWhth. The levelized cost of storage (LCOS) for CST-GeoTES depends on the energy storage duration. Although the LCOS is relatively higher for shorter durations (e.g., ~0.50 $\$$/kWhe for 1 hour of storage), it is an order of magnitude lower (0.06 $\$$/kWhe) for longer storage durations and competitive with lithium-ion batteries (beyond 12 hours of storage) and molten-salt thermal energy storage (beyond 32 hours). Energy. Three options were explored and applied to the EarthBridge case study: (1) A Carnot Battery design using R125 working fluid with both hot and cold storage; (2) A Carnot Battery design using R125 working fluid with only hot storage; (3) A Carnot Battery using a commercially available heat pump with carbon dioxide (CO2) working fluid and hot storage only. The CB-GeoTES with cold storage only had a slight (round-trip) efficiency advantage over the system without (43.4% vs. 42.8%). This is because the cold storage is limited by the freezing point of water, so the cold storage is not much colder than the environment. The system using commercially available technologies was the least efficient - partly because different cycles were used in the heat pump (CO2) and heat engine (binary cycle) which leads to some inefficiencies. Using the commercially available design, the levelized cost of energy (LCOS) from the model (0.10 $\$$/kWhe) was higher than that estimated by EarthBridge (0.068 $\$$/kWhe). This is because of the low round-trip (38.7%) efficiency of the commercially available design. Sensitivity analysis reveals that the model is most sensitive to electricity price. Including electricity price in the TEA for CB-GeoTES leads to an increase in LCOS from the base value to 0.25 $\$$/kWhe. To determine storage sites suitable for GeoTES, we gathered and analyzed geological, petrophysical, and geophysical data of oil and gas reservoir and aquifers in California and Texas. We down-selected possible sites based on cut-off values for site characteristics (e.g., reservoir temperature, formation thickness, permeability, porosity, depth, and brine salinity) and preliminary costs. Using this approach, the Carrizo-Wilcox, Yegua-Jackson, and Dockum brackish aquifers in Texas were identified as having the highest suitability. Similarly, in the central California region, the White Wolf, Belridge South Tulare, and Belridge South Reef Ridge were the most suitable. Going further, we assessed the storage potential in the selected sites. To do this we developed distributions of reservoir characteristic data and applied a Monte Carlo-based analysis to account for intrinsic uncertainty in the acquired data. The analysis revealed that the Carrizo-Wilcox aquifer had the highest storage potential with a mean capacity of 554 TWhth (i.e., 63 TWhe). The estimated capacity serves as an upper limit of storage potential given that not all fields in the basin will be developed. We participated in multiple outreach activities including conference presentations, panel session discussions, and the facilitation of a GeoTES workshop at the NREL Golden campus.

15 GEOTHERMAL ENERGY↗
NASA NTRS1989

The visual appearance of comets under varying solar wind conditions

Three-dimensional MHD simulations have been performed for four different sets of solar wind conditions and cometary outgassing rates appropriate to the Halley encounters. Even though the simulations are single fluid calculations, it is possible to separate the solar wind and cometary ions using the divergenceless nature of the solar wind ions. The cometary ion density is then integrated along the line-of-sight from the observer through the comet to determine how the comet would look to a distant observer under these different conditions. In general, comet tails appear longer when the interplanetary magnetic field lies in the plane of the sky rather than along the line-of-sight. Also, the tail shrinks as the speed of the solar wind increases and/or the mass loading rate decreases.

Russell, C. T.↗
NASA NTRS1984

The Fourier Tachometer 2: an Instrument for Measuring Global Solar Velocity Fields

The High Altitude Observatory and Sacramento Peak Observatory have jointly constructed a second version of the Fourier Tachometer, which is now undergoing final integration and testing. This is an interferometric instrument for measuring the Doppler shift of solar spectrum lines. The principal features and performance goals of this instrument are: simultaneous velocity observations over a 2-dimensional, 100 x 100 pixel field of view; measurement of absolute Doppler shifts with 1 m/s accuracy; noise level for moderate-1 oscillation modes of 1 cm/s for a 1-day observing run; flexibility and ease of use. Early (though incomplete) testing suggests that these goals should be attainable with the current instrument.

Brown, T. M.↗
NASA NTRS1988

Solar-flare shielding with Regolith at a lunar-base site

The Langley high energy nucleon transport computer code BRYNTRN is used to predict time-integrated radiation dose levels at the lunar surface due to high proton flux from solar flares. The study addresses the shielding requirements for candidate lunar habitat configurations necessary to protect crew members from these large and unpredictable radiation fluxes. Three solar proton events have been analyzed, and variations in radiation intensity in a shield medium due to the various primary particle energy distributions are predicted. Radiation dose predictions are made for various slab thicknesses of a lunar soil model. Results are also presented in the form of dose patterns within specific habitat configurations shielded with lunar material.

Nealy, John E.↗
DOE OSTI2023

Computationally Accelerated Discovery and Experimental Demonstration of High-Performance Materials for Advanced Solar Thermochemical Hydrogen Production

This project achieved its overarching goal of accelerating the discovery and validation of solar thermochemical hydrogen (STCH) materials through a tightly integrated approach that combined high-throughput computational screening, advanced machine learning (ML), and experimental testing. Guided by the objectives outlined in the Statement of Project Objectives (SOPO), our work fulfilled all major milestones across four technical tasks and delivered scientific breakthroughs and practical tools that significantly exceeded the original scope of the project. We began by addressing the challenge of predicting material phase stability through machine learning. A novel Python module was developed to generate thousands of meaningful features from composition, structure, and electronic properties, enabling rapid and reproducible ML model development. Using these tools, we trained a model to predict temperature-dependent Gibbs energies (G(T)) for inorganic crystalline materials with near-chemical accuracy—roughly 40 meV/atom—marking the first such descriptor of its kind. We also introduced a new machine-learned tolerance factor, τ, that accurately predicted perovskite formability with over 90% success, outperforming traditional heuristic models, such as the Goldschmidt tolerance factor. These capabilities allowed for rapid and accurate predictions of phase stability across a vast oxide composition space, setting the stage for high-throughput thermodynamic screening. Building on this foundation, we conducted an extensive computational screening of candidate STCH oxide materials. Over 1.1 million perovskite compositions were evaluated using the τ descriptor, leading to the identification of more than 27,000 predicted stable structures. Using density functional theory (DFT), we refined over 68,000 multinary perovskite structures and computed oxygen vacancy formation energies for over 1,300 ternary and double perovskites. These calculations enabled us to isolate compounds with redox behavior consistent with STCH requirements and resulted in a public dataset now hosted on the Materials Project. Recognizing that thermodynamic screening alone is insufficient, we addressed kinetic limitations by developing a suite of tools to estimate transition state (TS) energies for key redox reactions. We implemented a novel bounding approach that provides lower and upper estimates of TS energies with dramatically reduced computational cost, requiring less than 10% of the CPU time of a full nudged elastic band (NEB) calculation while maintaining high accuracy. This enabled rapid evaluation of over 200 reaction pathways across 90 materials. To further accelerate screening, we developed a SISSO-based ML model to predict diffusion barriers with a 96.7% success rate in classifying fast vs. slow materials, supporting a robust, data-driven framework for assessing redox kinetics. Experimental validation was critical to confirming the predictive power of our models. We synthesized and tested a wide array of candidate materials, including Mn-doped hercynite and several Gd- and La-based perovskites. Notably, Sr 0.4 Gd 0.6 Mn 0.6 Al 0.4 O 3 (SGMA) and Gd 0.5 La 0.5 Co 0.5 Fe 0.5 O 3 (GLCF) emerged as leading STCH materials, exhibiting robust redox cycling and high hydrogen yields exceeding 150 µmol H 2 /g per cycle. These materials also retained over 50% of their hydrogen productivity under high-conversion conditions (H 2 O:H 2 = 1333:1), demonstrating strong thermodynamic favorability and promising performance under industrially relevant scenarios. Additional candidates, such as La 2 MnNiO 6 (L2MN), were found to produce even higher yields than ceria under standard STCH conditions. Our collaborators at Sandia National Laboratories confirmed these findings using high-temperature X-ray diffraction and thermogravimetric analysis, observing stable phase evolution and reversible redox activity. In several respects, the project went beyond the goals initially outlined in the SOPO. We published 17 peer-reviewed articles, including a large dataset of over 66,000 theoretical perovskites and a new structure prediction method (SPuDS-DFT) that accurately identifies ground-state structures at a fraction of the cost of traditional DFT. We demonstrated that our machine-learned G(T) model offers accuracy rivaling quasiharmonic calculations while being orders of magnitude faster. In partnership with the Materials Project, we made our datasets openly available, providing a powerful new resource for the broader materials science community. The combined computational and experimental advances of this project represent a significant advance in STCH materials discovery. By creating a robust, generalizable, and open workflow for thermodynamic and kinetic screening, and validating key findings through synthesis and reactor testing, we have provided a practical and scalable pathway for the rapid identification of new redox-active materials. The tools, data, and materials developed under this project are already supporting ongoing research and have laid the groundwork for the next generation of solar fuel technologies.

08 HYDROGEN↗
DOE OSTI2023

Observations and Lessons Learned in Residential Roofing Integrated Photovoltaics

The data file includes field observations of residential roofing integrated photovoltaics installation that happened between July 2021 and June 2022 in California. There are 21 observations - 2 in the re-roofing category and 19 in the new construction category. The file includes two time and motion forms (Re-Roofing & New Construction) we used to capture the time it takes for each activity in the rooftop solar and electrical installation process. You will see the duration for detailed steps along with activities that are included for total installation time for the paper. There are three parts to the time and motion form - Part 1 has project and crew characteristics, product information, and inspection and permitting data and can be filled before the installation. Part 2 has the actual installation time stamps and related notes. Part 3 has the crew information and can be filled on-site or off-site, but this section is optional. The re-roofing form has pre-solar activities and gutters and vents section in Part 2 of the form, whereas new construction form includes a section for capturing the time it took for rough wiring. The re-roofing form does not include rough wiring but instead includes the final electrical wiring process. These are the key differences in both the forms. Each day/step/installation activity needs to include the crew break time as they happen and there is space available to capture the crew breaks duration. In Table 1 below, the different terms used in the time and motion form are defined and their corresponding unit of measurement stated. We also highlight the optional sections. The data is captured in total mins, total hours, person mins, person hours. You can use this form or make edits to the form to recreate the study or make your own observations. The data herein was reviewed but may not be comprehensive. NREL invites questions and inputs to improve the data, including to: Correct erroneous information Fill in missing/updated information Clarifications on data and variables Updated information may be submitted to Sushmita Jena at sushmita.jena@nlr.gov.

14 SOLAR ENERGY↗
NASA NTRS2011

Sensitivity of Depth-Integrated Satellite Lidar to Subaqueous Scattering

A method is presented for estimating subaqueous integrated backscatter from the CALIOP lidar. The algorithm takes into account specular reflection of laser light, laser scattering by wind-generated foam as well as sun glint and solar scattering from the foam Analyses show that the estimated subaqueous integrated backscatter is most sensitive to the estimate of transmittance used in the atmospheric correction, and is very insensitive to the estimate of wind speed used. As a case study, CALIOP data over Tampa Bay were compared to MODIS 645 nm remote sensing reflectance, which previously has been shown to be nearly linearly related to turbidity. The results indicate good correlation on nearly all CALIOP clear-free dates during the period 2006 through 2007, particularly those with relatively high atmospheric transmittance. When data are composited over the entire period the correlation is reduced but still statistically significant, an indication of variability in the biogeochemical composition in the water. Overall, the favorable results show promise for the application of satellite lidar integrated backscatter in providing information about subsurface backscatter properties, which can be extracted using appropriate models

Barton, Jonathan S.↗
DOE OSTI2021

Robust and Spectrally Selective Aerogels for Solar Receivers

The development of next generation concentrated solar thermal (CST) plants requires solar receivers to reach high temperatures (> 600°C) while minimizing costs. Efficiently generating such high temperatures using a line-focusing collector and an air-stable receiver has the potential to change the current CSP paradigm because it would: (1) result in large improvements in system-level efficiency of line-focusing systems by enabling the use of high-efficiency supercritical CO 2 power cycles; (2) decrease the LCOE of line-focusing systems to meet SETO 2030 goals; (3) maintain performance over the lifetime of the CSP plant by avoiding issues related to breakdown of vacuum. The use of aerogels as transparent insulating materials (TIMs) in solar thermal receivers has the potential to enable such improvements. Specifically, aerogels can be placed in front of a black (or partially selective) high-temperature absorber to allow sunlight to transmit to the absorber but block heat from escaping. These materials can improve the efficiency and simplify the complexity of thermal transport systems by enabling operation at moderate or no vacuum levels. These potential benefits have been explicitly identified by SETO as ‘high impact’. The use of mesoporous silica as a TIM has already led to large improvements in solar collection efficiency. Nevertheless, these materials inherently lose structural integrity and the ability to suppress radiation losses at high temperatures. Here, we address these challenges by leveraging 1-cycle atomic layer deposition of aluminum oxide onto a silica aerogel to form a thermally stable interfacial layer that is transparent to sunlight but broadly absorbs in the mid-infrared. This interfacial absorption results in a two-fold reduction in measured heat losses from an absorber at 700°C and solar thermal efficiency of 81% at 700°C under 60 Suns, based on measurements of heat loss and solar transmittance. Extended-duration heat treatment reveals that the multicomponent aerogel is stable at high temperatures relative to a silica aerogel. Furthermore, we experimentally demonstrate the concept of using infrared plasmon resonances to selectively enhance the thermal absorption coefficient of TIMs in order to strongly suppress thermal radiative losses at high temperatures. We term this mechanism plasmon-enhanced greenhouse selectivity (PEGS). Unlike silica aerogels, where much of the IR absorption is lost at high temperatures, local surface plasmon resonances (LSPRs) in doped oxide nanoparticles overlap a significant portion of the blackbody spectrum and are maintained at high temperatures. Overall, this work paves the way for next-generation solar thermal energy using thermally robust transparent insulating materials.

14 SOLAR ENERGY↗
DOE OSTI2020

Robust and Spectrally Selective Aerogels for Solar Receivers (Final Technical Report)

The development of next generation concentrated solar thermal (CST) plants requires solar receivers to reach high temperatures (> 600°C) while minimizing costs. Efficiently generating such high temperatures using a line-focusing collector and an air-stable receiver has the potential to change the current CSP paradigm because it would: (1) result in large improvements in system-level efficiency of line-focusing systems by enabling the use of high-efficiency supercritical CO2 power cycles; (2) decrease the LCOE of line-focusing systems to meet SETO 2030 goals; (3) maintain performance over the lifetime of the CSP plant by avoiding issues related to breakdown of vacuum. The use of aerogels as transparent insulating materials (TIMs) in solar thermal receivers has the potential to enable such improvements. Specifically, aerogels can be placed in front of a black (or partially selective) high-temperature absorber to allow sunlight to transmit to the absorber but block heat from escaping. These materials can improve the efficiency and simplify the complexity of thermal transport systems by enabling operation at moderate or no vacuum levels. These potential benefits have been explicitly identified by SETO as ‘high impact’. The use of mesoporous silica as a TIM has already led to large improvements in solar collection efficiency. Nevertheless, these materials inherently lose structural integrity and the ability to suppress radiation losses at high temperatures. Here, we address these challenges by leveraging 1-cycle atomic layer deposition of aluminum oxide onto a silica aerogel to form a thermally stable interfacial layer that is transparent to sunlight but broadly absorbs in the mid-infrared. This interfacial absorption results in a two-fold reduction in measured heat losses from an absorber at 700°C and solar thermal efficiency of 81% at 700°C under 60 Suns, based on measurements of heat loss and solar transmittance. Extended-duration heat treatment reveals that the multicomponent aerogel is stable at high temperatures relative to a silica aerogel. Furthermore, we experimentally demonstrate the concept of using infrared plasmon resonances to selectively enhance the thermal absorption coefficient of TIMs in order to strongly suppress thermal radiative losses at high temperatures. We term this mechanism plasmon-enhanced greenhouse selectivity (PEGS). Unlike silica aerogels, where much of the IR absorption is lost at high temperatures, local surface plasmon resonances (LSPRs) in doped oxide nanoparticles overlap a significant portion of the blackbody spectrum and are maintained at high temperatures. Overall, this work paves the way for next-generation solar thermal energy using thermally robust transparent insulating materials.

14 SOLAR ENERGY↗
DOE OSTI2021

A Comparative Analysis of Lithium-Ion Battery Chemistries for Cold-Climate Maritime Applications

Energy storage, primarily in the form of electrochemical batteries, is critical for enabling integration of marine energy (e.g., power from waves and currents) with end-use applications at sea due to the periodicity of the resources and requirement of consistent, smooth power delivery. Powering high-latitude coastal or ocean-based observing systems has been identified as a high value-proposition use case, exemplifying the concept of Powering the Blue Economy. An existing power system implementation for such a platform uses solar panels coupled to rechargeable lithium-ion batteries, augmented by a non-rechargeable backup bank used to power heaters in winter months. As wave energy is a potential resource for powering this and similar use cases and is strongest when solar power is most limited, it was hypothesized that integration of wave power would alleviate some of the challenges in cold climates related to energy storage. In this work, we investigate the use case scenario in simulation and perform a comparative test of commercially-available lithium-ion battery chemistry formulations to determine the most appropriate choice for the application. The experiment compared the most commonly-used lithium-based battery types (NCM, NCA, and LFP) in laboratory conditions emulating a battery enclosure thermally coupled to freezing seawater using an industrial battery performance tester in PNNL's arctic simulation lab. Battery strings were repeatedly cycled (i.e., charged, discharged, rested) and their usable capacity was measured. Both NCM and NCA strings exhibited degradation upon cycling, while the LFP string maintained stable operation through over 700 complete cycles. Though lower in baseline capacity, LFP are recommended for this and similar low-temperature applications with access to high levels of bulk charging current (e.g., from high-energy wave events) and their use may reduce the cost and complexity of battery conditioning and protection apparatus.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Ultrafast Triplet Generation at the Lead Halide Perovskite/Rubrene Interface

Triplet sensitization of rubrene by bulk lead halide perovskites has recently resulted in efficient infrared-to-visible photon upconversion via triplet-triplet annihilation. Notably, this process can occur under solar relevant fluxes, potentially paving the way toward integration with photovoltaic devices. In order to further improve the upconversion efficiency, the fundamental photophysical pathways at the perovskite/rubrene interface must be clearly understood to maximize charge extraction. Here, we utilize ultrafast transient absorption spectroscopy to elucidate the processes underlying triplet generation at the perovskite/rubrene interface. In this work, our results point to a triplet generation mechanism based on hot carriers; thermally excited charge carriers in the perovskite cool more rapidly in the presence of rubrene, suggesting rapid extraction of these thermally excited carriers on the picosecond time scale. Subsequent triplet formation in rubrene is observed on a subnanosecond time scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Consensus-Based Control and Optimization of Power System Inertia

The integration of distributed energy resources (DERs), such as solar, wind, and energy storage systems, into power grids through inverter-based resources reduces power system inertia, leading to faster frequency dynamics and potential grid instability. To address this challenge, this paper proposes a distributed, consensus-based approach for the real-time control and optimization of inertia sources (synchronous generators and/or DERs) during system disturbances, enhancing both system stability and economic performance. The distributed control and optimization approach assumes each inertia source exchanges information solely with its neighbor ones, making it easily scalable to large power grid networks. The impacts of the communication connectivity among the inertia sources as well as their generation capacity limits on the distributed approach are investigated. We also demonstrate the approach’s robustness in scenarios involving communication time delays and packet losses, validating its effectiveness through numerical simulations on a 4-bus test system and a two-area 8-bus test system.

Power system inertia↗
DOE OSTI2021

Optimized AC/DC Dual Active Bridge Converter using Monolithic SiC Bidirectional FET (BiDFET) for Solar PV Applications

Grid interface power conversion systems for commercial, industrial and residential solar power generation are becoming ubiquitous due to the competitive cost of solar energy. The AC/DC dual active bridge (DAB) converter is an upcoming topology in industrial PV energy and energy storage applications, providing bidirectional power transfer and galvanic isolation. In this paper, the properties of a DAB-type converter are leveraged to propose a design optimization process. It can optimize the high-frequency RMS current, size of magnetic elements and zero-voltage-switching (ZVS) region of the converter. The resulting design is compared against that derived from a conventional approach. In addition, an algorithm to compute the harmonic currents at the DC and line frequency AC ports of the system is proposed, and the respective filter designs are presented. The optimized design of the AC/DC DAB converter is implemented using the newly developed, 1200 V, 46 mΩ, four quadrant, SiC-based monolithic bidirectional FETs (BiDFET). Experimental results from the 2.3 kW, 400V/277VRMS hardware prototype are finally presented to verify the design process.

Bidirectional isolated AC-DC conversion, solar ene↗
DOE OSTI2021

Real-time Simulation Framework for Hardware-in-the-Loop Testing of Multi-port Autonomous Reconfigurable Solar Power Plant (MARS)

Multiport autonomous reconfigurable solar power plant (MARS) has been proposed for integrated development of photovoltaic (PV) and energy storage system (ESS) that can connect to high-voltage direct current (HVdc) and alternating current (ac) transmission grid. To de-risk the development of this complex integrated system that consists of hundreds to thousands of power electronics modules, a controller hardware-in-the-loop (cHIL) test setup will be extremely beneficial. The cHIL testing can be used for evaluation of modules as well as the hierarchical control system in MARS. With the unique configuration of power electronics modules in MARS, it becomes necessary to develop custom-designed real-time simulation models in the cHIL setup in absence of off-the-shelf models. In this paper, high-fidelity dynamic model of MARS, control algorithms at the lower level, and required communication algorithms are developed and optimized for real-time performance in the cHIL setup. Real-time experimental results from the cHIL are provided.

Dong, Zerui↗
DOE OSTI2023

Multi-Fidelity Gaussian Process for Distribution System Voltage Probabilistic Estimation with PVs

The increasing penetration of behind-the-meter PVs causes challenges to maintain voltage security due to the lack of distribution system visibility. This paper proposes a nonlinear autoregressive Gaussian process (NARGP) approach to fuse limited number of SCADA/AMI data together with historical pseudo measurements for distribution node voltage probabilistic estimation. The high-fidelity SCADA data are fused with the low-fidelity AMI and pseudo measurements by the autoregressive algorithm embedded in the Gaussian process. This allows us to use multi-fidelity data to achieve entire distribution system voltage visibility. Numerical results carried out on the IEEE 123node system demonstrate that the NARGP method is able to obtain high accuracy in estimating bus voltage and quantifying estimation uncertainties as compared to other approaches.

distribution system estimation↗
DOE OSTI2022

Welcome to the Special Issue on Grid-Edge Computing With Behind-the-Meter Resources [Guest Editorial]

The integration of distributed energy resources (DERs), such as solar photovoltaic systems, as well as other synergistic assets, including electric vehicles, energy storage, and smart appliances, in electric power systems has been dramatically increasing in the past few years. These assets have the capability to provide much-needed flexibility to electric power systems for improved grid reliability, resilience, and economic efficiency; however, most of these resources are located behind the meter (BTM) on customer premises, and their flexibility is not fully used in current grid operations. Grid-edge computing plays an important role in unlocking the great benefits and potential that BTM resources could provide to electric power systems by enhancing visibility and controllability at the grid edge.

behind-the-meter resources↗