Results for “Balancing Area” — Page 12

DOE OSTI2024

Optimal hybrid power plants for electric vehicle charging demand

Transmission constraints, increasing motivations to decarbonize, and concerns over peak electric vehicle (EV) load impacts on local grids have driven electric customers to consider behind-the-meter, hybrid power plant generation and storage at the distributed-grid level for EV charging. In this study, we develop capabilities to optimize hybrid power plant component capacities for EV charging. We then demonstrate these capabilities in a case study for Boulder, Colorado, using public EV charging data as well as wind and solar resource data. Our results show system designs that balance the cost of energy with load-meeting and peak shaving performance. Within the case study, systems designed for wind, solar photovoltaic (PV), and storage resulted in lower cost of energy than those optimized for PV and storage only. This indicates that in areas where wind resource exists, hybrid power plants that include wind, PV, and battery assets can better meet EV charging loads (including peak loads that are prone to overloading local grids) than PV and battery assets alone. Future work to address limitations in this paper include extending cost modeling to include performance losses (e.g., based on operations or weather) and charging station costs to estimate levelized cost of charging, and quantifying uncertainty and error in our aggregation methods for estimating EV charging loads at the hourly timescale.

14 SOLAR ENERGY↗

DOE OSTI2020

Materials and Approaches for Mitigation of SOFC Cathode Degradation in SOFC Power Systems

Perovskites such as doped lanthanum manganite and cobaltite have been used successfully as a cathode material in SOFC power systems operating between 700-1000°C. The electrodes, however, remain prone to degradation in presence of Cr containing gas atmosphere under systems operating conditions. Cathode in SOFCs is considered as one of the largest contributors of electrochemical performance degradations, leading to significant increase in ohmic and non-ohmic losses as well as interfacial compound formation. These degradations are mostly irreversible due to permanent changes to chemical and morphological alterations in the electrodes, resulting in the blockage of triple phase boundary (TPB) sites and decrease in oxygen reduction reactions (ORR). Fundamental mechanistic understanding has been developed to elucidate the reaction pathways of electrode poisoning in electronically conducting electrodes (LSM) as well as mixed ionic and electronically conducting electrodes (LSCF). The overall goal of this program has been identification and development of cost effective solutions to mitigate electrode degradations under “real world” systems operating conditions. The overall technological innovations and impact from this work are: The research provides an understanding of the degradation mechanism and cost-effective approaches for implementation in SOFC systems; Develop mitigation processes utilizing low cost getters using conventional synthesis and fabrication route; Develop tailored high surface area powders and coatings for high Cr capture capacity under systems operating conditions; >Developed computational models to understand mechanistic behavior; Experimentally measure rate of Cr evaporation from chromia and alumina forming alloys under SOFC operating conditions; Developed conditions to minimize Cr evaporation from balance-of-plant alloys; This innovation will support the development of getter platform to capture both intrinsic and extrinsic impurities present in air; and, Applications under wide operating temperature range (500-900°C) as well for wide high-temperature electrochemical systems (SOFC, SOEC, and OTM). The work has been successfully developed, validated experimentally and implemented. Successful technology transfer of this knowledge with industrial partners has been accomplished and the getters have been independently tested and validated under their systems operating conditions. The innovation will also find application in related high temperature electrochemical systems such as OTM and SOEC for the prevention of Cr assisted performance degradation. The proposed approach for Cr capture can also be applied to oxy-combustion and other advanced combustion techniques for the reduction of Cr vapor in the exhaust gas stream. This fundamental knowledge gained also has led to the path forward for developing advanced getters for capturing more than one contaminant in air.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Fractal Model for Drag Reduction on Multiscale Nonwetting Rough Surfaces

Rough surfaces in contact with a flow of fluid exhibit alternating no-slip and free shear boundary conditions at the solid–liquid and air–liquid interfaces, respectively, thereby potentially offering drag reduction benefits. The balance between the dynamic pressure in the flow and the restoring capillary pressure in the interasperity spaces determines the stability of the Cassie state of wettability and is a function of the relative extent of no-slip and free shear regions per unit surface area. In the present study, using a fractal representation of rough surface topography, an analytical model is developed to quantify the stability of the Cassie state of wettability as well as drag reduction and the friction factor for laminar flow in a rectangular channel between nonwetting multiscale rough surfaces. A systematic study is conducted to quantify the effects of fractal parameters of the surfaces and the flow Reynolds number on drag reduction and the friction factor. The studies are used to develop friction factor curves extending the classical Moody diagram to hydrophobic and superhydrophobic surfaces. On the basis of the studies, regime maps are derived for estimating the extent of drag reduction offered by hydrophobic and superhydrophobic surfaces, revealing that superhydrophobic surfaces do not always offer the best drag reduction performance. The application of the fractal model to practical topographies of nonwetting surfaces of copper, aluminum, and zinc oxide fabricated via electrodeposition and etching is also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Macroscopic Nonuniformities in Metal Grids Formed by Cracked Film Lithography Result in 19.3% Efficient Solar Cells

Cracked film lithography (CFL) is an emerging method for patterning transparent conductive metal grids. CFL can be vacuum- and Ag-free, and it forms more durable grids than nanowire approaches. In spite of CFL’s promising transmittance/grid sheet resistance/wire spacing tradeoffs, previous solar cell demonstrations have had relatively low performance. This work introduced macroscopic nonuniformities in the grids to improve the short-circuit current density/fill factor tradeoff in small area Cu(In,Ga)Se2 cells. Furthermore, the performance of optimized baseline grids was matched by CFL grids with microscopic openings and macroscopic patterns, culminating in a 19.3%-efficient cell. Simulations show that uniform CFL grids are enhanced by patterning because it leads to better balance among shadowing, grid resistance and transparent conductive oxide resistance losses. Thin-film module efficiency calculations were performed to highlight the performance gains that metal grids can enable by eliminating the transparent conductive oxide losses and widening monoliths. Adding the patterned CFL grids demonstrated in this work to CIGS modules is predicted to reach 0.7% higher efficiency (absolute) than screen-printed grids.

14 SOLAR ENERGY↗

DOE OSTI2022

MERIT-Plus Dataset: Delineation of endorheic basins in 5 and 15 min upscaled river networks

Endorheic drainage basins, those inland basins not connected directly to ocean, are essential for hydrological modeling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. Within many hydrological model frameworks, river basins are defined by digital river networks through their flow direction and connectivity datasets. Here we present an improvement to gridded flow direction data and its derivatives produced from upscaled global 5 and 15 arc minute MERIT networks. We explicitly label endorheic and exorheic drainage basins and alter the delineation of endorheic basins by merging small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion of those basins since most of the merged catchments were inside other larger endorheic areas. We developed and present here the endorheic basin delineation method. This method performs an analysis of the contributing river and basin geometry relative to the location of the flow end point (i.e. potential endorheic lake), proximity of the latter to the drainage basin boundary and the elevation difference between the basin's lowest point and potential spillover location at the basin boundary. The new digital river network was validated using the University of New Hampshire Water Balance Model by comparing the water balance of endorheic inland depressions with modeled accumulation of water in their inland lakes based on the observed historical climate drivers used by WBM.

Earth Systems↗

DOE OSTI2023

MERIT-Plus Dataset: Delineation of endorheic basins in 5 and 15 min upscaled river networks

Endorheic drainage basins, those inland basins not connected directly to ocean, are essential for hydrological modeling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. Within many hydrological model frameworks, river basins are defined by digital river networks through their flow direction and connectivity datasets. Here we present an improvement to gridded flow direction data and its derivatives produced from upscaled global 5 and 15 arc minute MERIT networks. We explicitly label endorheic and exorheic drainage basins and alter the delineation of endorheic basins by merging small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion of those basins since most of the merged catchments were inside other larger endorheic areas. We developed and present here the endorheic basin delineation method. This method performs an analysis of the contributing river and basin geometry relative to the location of the flow end point (i.e. potential endorheic lake), proximity of the latter to the drainage basin boundary and the elevation difference between the basin's lowest point and potential spillover location at the basin boundary. The new digital river network was validated using the University of New Hampshire Water Balance Model by comparing the water balance of endorheic inland depressions with modeled accumulation of water in their inland lakes based on the observed historical climate drivers used by WBM.

Earth Systems↗

DOE OSTI2023

MERIT-Plus Dataset: Delineation of endorheic basins in 5 and 15 min upscaled river networks

Endorheic drainage basins, those inland basins not connected directly to ocean, are essential for hydrological modeling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. Within many hydrological model frameworks, river basins are defined by digital river networks through their flow direction and connectivity datasets. Here we present an improvement to gridded flow direction data and its derivatives produced from upscaled global 5 and 15 arc minute MERIT networks. We explicitly label endorheic and exorheic drainage basins and alter the delineation of endorheic basins by merging small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion of those basins since most of the merged catchments were inside other larger endorheic areas. We developed and present here the endorheic basin delineation method. This method performs an analysis of the contributing river and basin geometry relative to the location of the flow end point (i.e. potential endorheic lake), proximity of the latter to the drainage basin boundary and the elevation difference between the basin's lowest point and potential spillover location at the basin boundary. The new digital river network was validated using the University of New Hampshire Water Balance Model by comparing the water balance of endorheic inland depressions with modeled accumulation of water in their inland lakes based on the observed historical climate drivers used by WBM.

Earth Systems↗

DOE OSTI2023

MERIT-Plus Dataset: Delineation of endorheic basins in 5 and 15 min upscaled river networks

Endorheic drainage basins, those inland basins not connected directly to ocean, are essential for hydrological modeling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. Within many hydrological model frameworks, river basins are defined by digital river networks through their flow direction and connectivity datasets. Here we present an improvement to gridded flow direction data and its derivatives produced from upscaled global 5 and 15 arc minute MERIT networks. We explicitly label endorheic and exorheic drainage basins and alter the delineation of endorheic basins by merging small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion of those basins since most of the merged catchments were inside other larger endorheic areas. We developed and present here the endorheic basin delineation method. This method performs an analysis of the contributing river and basin geometry relative to the location of the flow end point (i.e. potential endorheic lake), proximity of the latter to the drainage basin boundary and the elevation difference between the basin's lowest point and potential spillover location at the basin boundary. The new digital river network was validated using the University of New Hampshire Water Balance Model by comparing the water balance of endorheic inland depressions with modeled accumulation of water in their inland lakes based on the observed historical climate drivers used by WBM.

Earth Systems↗

DOE OSTI2021

Land cover change-induced decline in terrestrial gross primary production over the conterminous United States from 2001 to 2016

As one of the most dynamic aspects of global environmental change, land cover change (LCC) has a profound impact on terrestrial carbon sequestration. However, LCC-induced carbon fluxes are still the most uncertain terms in global and regional carbon budgets. Ecosystem gross primary production (GPP) is the total carbon uptake by vegetation through photosynthesis, serving as a major control on ecosystem function and land carbon balance during and after the modification of the land surface. However, accurately capturing LCC-induced GPP changes requires both high-quality land cover data and controlling for variation driven by other environmental factors such as climate. In this study, we comprehensively examined the effects of LCC on annual GPP trends over the conterminous United States (CONUS) from 2001 to 2016 using the USGS National Land Cover Database, a remote sensing-driven ecosystem model, and the Google Earth Engine cloud computing platform. We designed a series of model experiments to identify LCC effects on GPP by controlling climate effects. During the study period, LCC exerted a strong negative effect on total GPP across the CONUS ([-2.2, -1.8] Tg C yr -2 ), while climate had smaller positive effects ([0.17, 0. 92] Tg C yr -2 ). The LCC-induced reduction of GPP was mainly caused by net forest loss ([-1.98, -1.39] Tg C yr -2 ) and urban expansion ([-2.03, -1.92] Tg C yr -2 ), but was partially offset by increases in crop area ([+0.66, +0.79] Tg C yr -2 ). Ensemble simulations from TRENDY did not capture the strong negative LCC influences on GPP, likely due to limitations of the adopted land use/cover data. Overall, our study provides a novel perspective on LCC-induced GPP changes, which could help to improve our understanding of ecosystem function changes and constrain the estimation of land carbon balance in the context of anthropogenic activity and climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Uranium and Nickel Partitioning in a Contaminated Riparian Wetland

Uranium (U) and nickel (Ni) released 50 years ago have been immobilized in the Tims Branch wetlands located on the Savannah River Site in the United States. Sediments were collected from seven locations to identify the factors responsible for this attenuation. Ni and U contents in the solids were significantly correlated, suggesting that depositional as opposed to chemical processes contributed to their spatial distribution. Based on sequential extractions, 63 ± 16% of the U was partitioned into the organic fraction, whereas Ni was distributed between several sediment fractions. An inverse pH-organic matter (OM) correlation and positive correlations of OM with total U and organic-bound U/Ni suggest that increased OM preservation and binding to the mineral surfaces were likely responsible for Ni- and especially U-sediment retention (Tims Branch pH = 4.84 ± 0.68). EXAFS analysis indicated the predominance of U(VI) coordinated with clay minerals (~65%), together with ~35% coordinated to either OM (in areas with elevated OM levels) or iron oxides. The desorption-Kd coefficients of U (3972 ± 1370 L/kg) and Ni (30 ± 8 L/kg) indicate that dissolved Ni poses a greater long-term risk than dissolved U for migrating downstream. This study suggests that a delicate balance of geochemical properties controls whether wetlands behave as sinks or sources of contaminants.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2023

Study of Storage Requirements and Costs for Shaping Renewables and Nuclear Energy (FY23 Summary Report)

To decarbonize electricity generation primarily by using wind and solar resources, it is likely that additional low (or zero) carbon dioxide (CO 2 ) alternatives will be required for ensuring a reliable electricity supply. This study extends the work and modeling framework that we consolidated in FY 2022, by assessing the zero-CO 2 pathways of a Texas power system in which the availability of variable renewable energy (VRE), nuclear energy, and energy storage types (i.e., battery and thermal energy storage [TES]) are considered the sole resources available for expansion. Using the Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON) frameworks, this study investigates the market of two nuclear energy technologies (i.e., large light-water reactors [LWRs] and LWR-type small modular reactors [SMRs]) under two plausible storage coupling scenarios (i.e., electric coupling and direct thermal coupling). We also explore optimal environments for nuclear energy deployment, and identify key performance characteristics that make nuclear energy economically viable in areas with significant intermittent energy sources. Our analysis encompasses 24 cases. We model the least-cost grid systems, highlight the potential for a coupled LWR-TES approach, and utilize SMRs to achieve deep decarbonization in an affordable, technically feasible manner. We also examine seasonal variations in balancing electricity supply and demand, and account for varying performance, costs, and grid constraints. Overall, the findings of our modeling afford valuable insights for supporting future technology investment decisions in the energy sector.

25 ENERGY STORAGE↗

DOE OSTI2024

Material Control and Accounting for Liquid-Fueled Molten Salt Reactors: Material Control and Holdup Considerations

The US Nuclear Regulatory Commission (NRC) will likely require license applicants for liquid-fueled molten salt reactors (MSRs) with circulating fuel to submit a nuclear material control and accounting (MC&A) plan or detailed MC&A program description for the facility. In liquid-fueled MSRs with special nuclear material (SNM) in bulk (i.e., not in discrete items) form and rapidly changing quantities due to fuel transmutation and depletion, using traditional nuclear material accounting methods with material balance evaluations is challenging. In reactors with changing inventories, these expected quantities of SNM must be calculated based on operational parameters. Reducing uncertainties on these expected quantities is challenging in the case of MSRs without decades of operational experience to verify and validate predictive computational codes. Moreover, many areas in MSRs are inaccessible because of high-temperature and high-radiation environments, making measurements challenging.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

SNICAR-ADv4: a physically based radiative transfer model to represent the spectral albedo of glacier ice

Abstract. Accurate modeling of cryospheric surface albedo is essential for our understanding of climate change as snow and ice surfaces regulate the global radiative budget and sea-level through their albedo and mass balance. Although significant progress has been made using physical principles to represent the dynamic albedo of snow, models of glacier ice albedo tend to be heavily parameterized and not explicitly connected with physical properties that govern albedo, such as the number and size of air bubbles, specific surface area (SSA), presence of abiotic and biotic light absorbing constituents (LACs), and characteristics of any overlying snow. Here, we introduce SNICAR-ADv4, an extension of the multi-layer two-stream delta-Eddington radiative transfer model with the adding–doubling solver that has been previously applied to represent snow and sea-ice spectral albedo. SNICAR-ADv4 treats spectrally resolved Fresnel reflectance and transmittance between overlying snow and higher-density glacier ice, scattering by air bubbles of varying sizes, and numerous types of LACs. SNICAR-ADv4 simulates a wide range of clean snow and ice broadband albedo (BBA), ranging from 0.88 for (30 µm) fine-grain snow to 0.03 for bare and bubble-free ice under direct light. Our results indicate that representing ice with a density of 650 kg m−3 as snow with no refractive Fresnel layer, as done previously, generally overestimates the BBA by an average of 0.058. However, because most naturally occurring ice surfaces are roughened “white ice”, we recommend modeling a thin snow layer over bare ice simulations. We find optimal agreement with measurements by representing cryospheric media with densities less than 650 kg m−3 as snow and larger-density media as bubbly ice with a Fresnel layer. SNICAR-ADv4 also simulates the non-linear albedo impacts from LACs with changing ice SSA, with peak impact per unit mass of LACs near SSAs of 0.1–0.01 m2 kg−1. For bare, bubble-free ice, LACs actually increase the albedo. SNICAR-ADv4 represents smooth transitions between snow, firn, and ice surfaces and accurately reproduces measured spectral albedos of a variety of glacier surfaces. This work paves the way for adapting SNICAR-ADv4 to be used in land ice model components of Earth system models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Power Flow Solution Methods for Combined Transmission and Distribution Systems

High distributed PV penetration makes the distribution systems more active and increases their impact on the upstream transmission grid. To facilitate the studies on this area, this paper proposes a power flow (PF) model and formulation of combined transmission and distribution (T&D) power systems. The formulation is based on the physical coupling of transmission and distribution grids. The unbalanced nature of distribution feeders and voltage regulators are modeled so that the resulting PF balance equations in distribution systems are similar to those in the interconnected transmission system. The formulated nonlinear PF equations are solved using the proposed unified and sequential methods. Both methods are verified and compared with each other using several combined T&D power systems. A multi-period PF simulation is also included to demonstrate the capability of the proposed formulation and solution methods in capturing the influences of high distributed PV penetration on transmission level.

Nguyen, Quan H.↗

DOE OSTI2025

Fiber-Optic Sensing for Earthquake Hazards Research, Monitoring, and Early Warning

The use of fiber‐optic sensing systems in seismology has exploded in the past decade. Despite an ever‐growing library of ground‐breaking studies, questions remain about the potential of fiber‐optic sensing technologies as tools for advancing if not revolutionizing earthquake‐hazards‐related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber‐optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber‐optic sensing to impact monitoring efforts by documenting the data completeness in a number of long‐term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber‐optic sensing and unlock its potential application to a broad range of earthquake hazard problems.

58 GEOSCIENCES↗

DOE OSTI2021

Net-Zero Carbon Microgrids

The microgrid concept has been effective in creating aggregations of distributed energy resources—generation, storage and loads—for resiliency, in the form of energy security. The success of microgrids in bringing energy security to a wide range of customers—from individual residences to commercial and industrial installations to military bases—has been exemplified during power disruptions and extended outages due to extreme weather events, cybersecurity attacks, and equipment failures. Now microgrids have an opportunity to meet the challenges of climate change and contribute to a carbon-free power delivery system. The transition to net-zero starts within microgrids themselves. In fact, today’s microgrids are largely dominated by generators using fossil fuels, natural gas and diesel, with high greenhouse gas emissions. In short, the transition to net-zero means replacing fossil fueled generators with renewable generation in microgrids. This transition is extended by including new dispatchable generation technologies that are 100% carbon-free and that offer additional advantage of a more-dependable and sustainable source of energy and power. Basically, the decarbonization of microgrids requires three elements: 1) maximizing generation from renewable energy resources, 2) management of storage and flexible loads to balance the variability and intermittency of renewable energy resources, and 3) introducing new clean power sources, including hydrogen-based generation and small modular reactors. This report affirms a need for specific focus by governmental agencies at national, regional, and local levels to establish technology, policy, and investment in this area. The intention of the Net-Zero Microgrid (NZM) Program is to inform these constituencies with cross-cutting research and tools for the reduction of GHG in microgrids – to net-zero in the near term eventually to zero in the longer term. The NZM Program is committed to achieving decarbonization for resiliency and for providing clean energy at the local or distribution level, from remote communities to underserved communities, and large industrial and military facilities. The NZM Planning and Design Platform is a core tool to be developed as an early deliverable of the NZM Program because only a fully integrated microgrid-design approach will ensure maximum carbon reduction in energy production.

13 HYDRO ENERGY↗

DOE OSTI2020

Evapotranspiration depletes groundwater under warming over the contiguous United States

A warmer climate increases evaporative demand. However, response to warming depends on water availability. Existing earth system models represent soil moisture but simplify groundwater connections, a primary control on soil moisture. Here we apply an integrated surface-groundwater hydrologic model to evaluate the sensitivity of shallow groundwater to warming across the majority of the US. We show that as warming shifts the balance between water supply and demand, shallow groundwater storage can buffer plant water stress; but only where shallow groundwater connections are present, and not indefinitely. As warming persists, storage can be depleted and connections lost. Similarly, in the arid western US warming does not result in significant groundwater changes because this area is already largely water limited. The direct response of shallow groundwater storage to warming demonstrates the strong and early effect that low to moderate warming may have on groundwater storage and evapotranspiration.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Artificial intelligence inferred microstructural properties from voltage–capacity curves

Abstract The quantification of microstructural properties to optimize battery design and performance, to maintain product quality, or to track the degradation of LIBs remains expensive and slow when performed through currently used characterization approaches. In this paper, a convolution neural network-based deep learning approach (CNN) is reported to infer electrode microstructural properties from the inexpensive, easy to measure cell voltage versus capacity data. The developed framework combines two CNN models to balance the bias and variance of the overall predictions. As an example application, the method was demonstrated against porous electrode theory-generated voltage versus capacity plots. For the graphite|LiMn $$_2$$ 2 O $$_4$$ 4 chemistry, each voltage curve was parameterized as a function of the cathode microstructure tortuosity and area density, delivering CNN predictions of Bruggeman’s exponent and shape factor with 0.97 $$R^2$$ R 2 score within 2 s each, enabling to distinguish between different types of particle morphologies, anisotropies, and particle alignments. The developed neural network model can readily accelerate the processing-properties-performance and degradation characteristics of the existing and emerging LIB chemistries.

25 ENERGY STORAGE↗