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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Factors Influencing Grid-connected Heat Pump Water Heater Performance in the Southeast U.S.

Grid-connected heat pump water heaters (HPWH) can shift electrical load while minimizing impacts to hot water availability for occupants. This capability provides a flexible grid resource to utilities seeking to manage peak loads Such load control also can feasibly improve renewable utilization within the utility electric production mix, for instance using off-peak generation during periods with high renewable energy generation. It also offers lower electric bills to customers through increased energy efficiency of HPWH and cuts greenhouse gas emissions. In particular, the Southeast U.S. due to its high penetration of electric water heating presents a promising opportunity for grid-connected HPWHs. This paper builds upon the results of an extensive HPWH load shifting field study conducted in 51 occupied homes in Florida using EcoPort technology (Butzbaugh et al, 2022). In 2022, only an initial evaluation was available. Here, long term load results are available as well as examination of various control strategies and influences. Analysis is conducted for HPWH energy use and load shifting performance based on home occupancy (i.e., low and high) and water heater location (i.e., conditioned and unconditioned) across different temperature profiles. An unexpected outcome of this analysis was the poor performance of HPWHs located in conditioned spaces, possibly because of inadequate air volume from improper installation. We did find higher demand reductions from 2-hour load ups and slightly improved for critical peak signals in the afternoon control periods. As expected, higher occupancy households showed great load reductions.

Fenaughty, Karen↗
DOE OSTI2024

Denoising diffusion probabilistic models for generative alloy design

Inverse material design is an extremely challenging optimization task made difficult by, in part, the highly nonlinear relationship linking performance with composition. Quantitative approaches have improved significantly owing to advances in high throughput experimentation and computational thermodynamics. However, existing physics-based tools are mostly forward models; input a chemistry and obtain a prediction. More recently the materials community has leveraged advances in the machine learning community to establish novel inverse design frameworks. Very recently denoising diffusion probabilistic models have been shown to be extremely powerful generators producing synthetic data of various modalities e.g. images, text, audio, tables, etc.. In this work a novel framework for alloy design and optimization is proposed leveraging these class of models. Five key generative tasks are demonstrated (1) unconditional generation (2) composition conditioned generation (3) property conditioned generation (4) multi-feedstock conditioned generation and (5) generative optimization. These methods were tested on three case studies: high entropy alloy design, superalloy binder jet additive manufacturing, and in-situ dual-feedstock wire-arc additive manufacturing. Results indicate that the established models are extremely flexible, expressive, and robust. The architecture’s flexibility and training procedure empower the model to learn complex intra-compositional and composition-property relationships. Furthermore, the probabilistic nature of these models makes them well suited for addressing solution non-uniqueness and tackling uncertainty quantification tasks. While the fidelity and quantity of the underlying training data is paramount, we envision that future alloy design frameworks will make extensive use of these kinds of machine learning models as “search” tools bolstering the utility of experimental and computational approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Segmented Energy Routing for a Modular AC/DC Hybrid System

This article presents a modular ac/dc system with both distributed and centralized power ports for energy router (ER) applications. In each module of the described system, photovoltaic (PV) power generation units, battery-type energy storage (ES) units, and critical loads are connected to the cascaded H-bridge (CHB)-organized medium-voltage (MV) dc links, with fully distributed low-voltage (LV) dc power ports. Copies of modules share the centralized load bus and interact with an MV ac grid in parallel. Hybrid power port (HPO) assigns flexibility to the system but makes energy routings a necessity for stable operation. In this article, a segmented energy management strategy for the HPO-ER is proposed. In terms of the grid-side power transferring, the system ratings are intentionally designed to match significant power imbalance. Focally, a segmented energy management strategy is proposed to realize fully autonomous energy routing involving MV ac grid, distributed PV generations, distributed battery storages, and LV load. The system is proven to be stable using the derived impedance-based model considering the interaction between power blocks. The feasibility of the topology and control strategy is also verified through software simulation, laboratorial hardware prototype experiment, and hardware-in-the-loop (HIL) emulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Morphological Ordering of the Organic Layer for High-Performance Hybrid Thermoelectrics

Inorganic-organic hybrids, such as Te-PEDOT:PSS core/shell nanowires, have emerged as a class of promising thermoelectric materials with combined attributes of mechanical flexibility and low cost. However, the poorly understood structure-property relationship calls for further investigation for performance enhancement. Here, through precise treatments of focused electron beam irradiation and thermal annealing on individual Te-PEDOT:PSS nanowires, new, nonchemical mechanisms are introduced to specifically engineer the organic phase, and the measured results provide an unprecedented piece of evidence, confirming the dominant role of organic shell in charge transport. Paired with the Kang-Snyder model and molecular dynamics simulations, this work provides mechanistic insights in terms of heating-enabled morphological ordering of the polymer chains. The measured results show that thermal annealing on the 42 nm nanowire results in a ZT value of 0.78 at 450 K. In conclusion, through leveraging the interfacial self-assembly of the organic phase to construct a high electrical conductivity domain, this work lays out a clear framework for the development of next-generation soft thermoelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The locational value of distributed energy resources: A parcel-level evaluation of solar and wind potential in New York state

We report distributed energy resources (DERs) are poised to play a significant role in evolving power systems because of their flexibility to be sited in areas of high value to the grid. Traditional DER compensation frameworks, specifically net energy metering (NEM), inadequately communicate differences in the locational and temporal value of DER generation to the grid. As a transition from NEM, New York State's (NYS's) Value of Distributed Energy Resources (VDER) framework provides a methodology for calculating different value components that DERs offer the grid. To study the impacts of VDER frameworks on DER deployment, we developed a model to assess the value of distributed solar and wind systems configured as either a behind-the-meter system or a front-of-the-meter system for each parcel of land in NYS. Using parcel-level granularity, we can closely evaluate DER locational value and siting availability, particularly in urban and suburban settings. Our analysis finds while most DER generators would be modestly compensated for deferred transmission and distribution infrastructure upgrades (~0.01 $\$$/kWh for solar PV), a subset of projects receive significant value from this component (0.035 to 0.089 $\$$/kWh for top 5% of parcels for solar PV). Finally, our analysis finds VDER provides less overall compensation than NEM to the average DER generator, however, it increases access to compensation for front-of-the-meter DERs - a large and emerging market.

14 SOLAR ENERGY↗
DOE OSTI2025

Automated Redox Titrations via Interdigitated Electrode Arrays: Application to the Mediated Electron Transfer Interrogation of Charge and Rate on Electrodeposited Polymers

Mediated electron transfer (MET) plays a crucial role in energy storage and conversion technologies such as redox targeting flow batteries (RTFBs), yet its experimental investigation often requires labor-intensive and low-throughput setups. To address this, we developed a microfabricated interdigitated electrode array (IDA) platform that enables automated, high-throughput electrochemical redox titration measurement to be performed to study the MET process. Our redox titration method enables simultaneous measurement of the charge capacity and rate of MET processes on a material or surface. Automated redox titration (ART) facilitates systematic investigation of the MET process across a broad parameter space, exemplified through the study of polypyrrole (PPy) and a pyrene-4,5,9,10-tetrone azo group-based polymer (PTAP), both redox-active polymers relevant to various energy storage applications. Using PPy as a model material, 500 redox titration measurements were conducted within 50 h, varying the electrode gap widths, polymer charging potentials, voltammetric scan rates, and electrolyte concentrations. Finite-element simulations confirmed the electrochemical responses and elucidated the kinetics of the MET reactions. Our automated methodology was further tested with PTAP, revealing a surprising charging potential dependence on the rate of MET. The automation, flexibility, and scalability of our redox titration platform pave the way not only for advanced studies of MET processes relevant to RTFBs, but also with implications in the understanding of next-generation energy storage materials, molecular electrocatalysis, and biosensing.

electrochemical analysis↗
DOE OSTI2025

Atomate2: modular workflows for materials science

High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screening, property database generation, and training of “universal” machine learning models. While several software frameworks have emerged to support these computational efforts, new developments such as machine learned force fields have increased demands for more flexible and programmable workflow solutions. This manuscript introduces atomate2, a comprehensive evolution of our original atomate framework, designed to address existing limitations in computational materials research infrastructure. Key features include the support for multiple electronic structure packages and interoperability between them, along with generalizable workflows that can be written in an abstract form irrespective of the DFT package or machine learning force field used within them. Our hope is that atomate2's improved usability and extensibility can reduce technical barriers for high-throughput research workflows and facilitate the rapid adoption of emerging methods in computational material science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Integrating novel stellarator single-stage optimization algorithms to design the Columbia stellarator experiment

Abstract The Columbia Stellarator eXperiment (CSX), currently being designed at Columbia University, aims to test theoretical predictions related to QA plasma behavior, and to pioneer the construction of an optimized stellarator using three-dimensional, non-insulated high-temperature superconducting (NI-HTS) coils. The magnetic configuration is generated by a combination of two circular planar poloidal field (PF) coils and two 3D-shaped interlinked (IL) coils, with the possibility to add windowpane coils to enhance shaping and experimental flexibility. The PF coils and vacuum vessel are repurposed from the former Columbia Non-Neutral Torus experiment, while the IL coils will be custom-wound in-house using NI-HTS tapes. To obtain a plasma shape that meets the physics objectives with a limited number of coils, novel single-stage optimization techniques are employed, optimizing both the plasma and coils concurrently, in particular targeting a tight aspect ratio QA plasma and minimized strain on the HTS tape. Despite the increased complexity due to the expanded degrees of freedom, these methods successfully identify optimized plasma geometries that can be realized by coils meeting engineering specifications. This paper discusses the derivation of the constraints and objectives specific to CSX, and describe how two recently developed single-stage optimization methodologies are applied to the design of CSX. A set of selected configurations for CSX is then described in detail.

Baillod, A. (ORCID:0000000303529180)↗
DOE OSTI2023

A Hydrokinetic Energy Conversion System using Underwater LLC-type Resonant Converter

The hydrokinetic energy of river and ocean currents is a valuable renewable energy resource. Conventional systems for harvesting hydrokinetic energy usually have bulky passive components, lengthy cables connecting the underwater turbine/generator with onshore power converters, and limited control over power generation. This paper presents a new hydrokinetic energy harvesting system using an LLC-type resonant converter that is placed underwater in close proximity to the generator. By using SiC devices and the soft switching characteristic of LLC resonant converter, the converter operates in 10s of kHz, significantly reducing the passive components. In addition, the LLC converter provides flexible power regulation of the system. Furthermore, the underwater placement of the power converter takes advantage of the cooling provided by the water and simplifies the system by reducing its connecting cable length.

Dai, Hang↗
DOE OSTI2024

Leptothrix ochracea genomes reveal potential for mixotrophic growth on Fe(II) and organic carbon

ABSTRACT Leptothrix ochracea creates distinctive iron-mineralized mats that carpet streams and wetlands. Easily recognized by its iron-mineralized sheaths, L. ochracea was one of the first microorganisms described in the 1800s. Yet it has never been isolated and does not have a complete genome sequence available, so key questions about its physiology remain unresolved. It is debated whether iron oxidation can be used for energy or growth and if L. ochracea is an autotroph, heterotroph, or mixotroph. To address these issues, we sampled L. ochracea -rich mats from three of its typical environments (a stream, wetlands, and a drainage channel) and reconstructed nine high-quality genomes of L. ochracea from metagenomes. These genomes contain iron oxidase genes cyc2 and mtoA, showing that L. ochracea has the potential to conserve energy from iron oxidation. Sox genes confer potential to oxidize sulfur for energy. There are genes for both carbon fixation (RuBisCO) and utilization of sugars and organic acids (acetate, lactate, and formate). In silico stoichiometric metabolic models further demonstrated the potential for growth using sugars and organic acids. Metatranscriptomes showed a high expression of genes for iron oxidation; aerobic respiration; and utilization of lactate, acetate, and sugars, as well as RuBisCO, supporting mixotrophic growth in the environment. In summary, our results suggest that L. ochracea has substantial metabolic flexibility. It is adapted to iron-rich, organic carbon-containing wetland niches, where it can thrive as a mixotrophic iron oxidizer by utilizing both iron oxidation and organics for energy generation and both inorganic and organic carbon for cell and sheath production. IMPORTANCE Winogradsky's observations of L. ochracea led him to propose autotrophic iron oxidation as a new microbial metabolism, following his work on autotrophic sulfur-oxidizers. While much culture-based research has ensued, isolation proved elusive, so most work on L. ochracea has been based in the environment and in microcosms. Meanwhile, the autotrophic Gallionella became the model for freshwater microbial iron oxidation, while heterotrophic and mixotrophic iron oxidation is not well-studied. Ecological studies have shown that Leptothrix overtakes Gallionella when dissolved organic carbon content increases, demonstrating distinct niches. This study presents the first near-complete genomes of L. ochracea , which share some features with autotrophic iron oxidizers, while also incorporating heterotrophic metabolisms. These genome, metabolic modeling, and transcriptome results give us a detailed metabolic picture of how the organism may combine lithoautotrophy with organoheterotrophy to promote Fe oxidation and C cycling and drive many biogeochemical processes resulting from microbial growth and iron oxyhydroxide formation in wetlands.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Valuing EV Managed Charging for Bulk Power Systems

When and where electric vehicle (EV) charging occurs has significant implications for power systems supporting widespread EV adoption, especially with high shares of wind and solar generation. This study extends previous works by leveraging detailed simulation models for EV adoption, EV use, EV charging, and bulk power system operations, and by linking them with methods for describing charging flexibility at both the individual vehicle and aggregate levels. This technical potential study focuses on how the value of EV managed charging (EVMC) changes depending on charging flexibility type (within-charging session or within-week scheduling), dispatch mechanism (direct load control or one of several price-based mechanisms), and managed charging participation rate. We show that naively aggregating EV charging flexibility from individual vehicles into megawatt-scale resources grossly overestimates the flexibility of the fleet, because such aggregate models can unrealistically pair, e.g., one already-fully-charged vehicle's ability to increase load with another already-charging vehicle's ability to accept more charge, effectively requesting a charging rate that is infeasible for the latter vehicle. We find per-vehicle bulk system value is highest at low participation rates for all dispatch mechanisms. Factoring in production cost savings, avoided firm capacity savings, and combustion-related power sector emissions savings, we estimate the value of EVMC at low participation rates (5%) to be $33/vehicle-year to $69/vehicle-yr for within-session charging flexibility and $40/vehicle-yr to $120/vehicle-yr for within-week charging flexibility in an envisioned 2038 New England power system and monetary value reported in 2016 U.S. dollars. At 100% participation, per-vehicle value declines to $25/vehicle-yr to $31/vehicle-yr for within-session charging flexibility and to $29/vehicle-yr to $36/vehicle-yr for within-week charging flexibility; however, 100% participation yields the highest total system savings.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Portable diagnostic package for Thomson scattering and optical emission spectroscopy on Princeton field-reversed configuration 2 (PFRC 2)

An Advanced Research Projects Agency-Energy funded diagnostic system has been deployed to the Princeton field-reversed configuration 2 (PFRC-2) device, located at Princeton Plasma Physics Laboratory. The Portable Diagnostic Package (PDP), designed at Oak Ridge National Laboratory, allows for the measurement of Thomson Scattering (TS) for electron density and temperature and Optical Emission Spectroscopy (OES) for ion temperature, impurity density, and ion velocity. A tunable spectrometer on the PDP with three gratings provides the flexibility to measure low (1 eV) and high (1000 eV) electron temperature ranges from TS. Additionally, using a second spectrometer, the OES diagnostic can survey light emission from various ion excitation levels for wide wavelength ranges. The electron density (<2 × 10 19 m –3 ) of plasmas generated in PFRC-2 has been below the PDP TS discrimination threshold, which has made TS signal detection challenging against a high-background of laser stray light. The laser stray light was iteratively reduced by making modifications to the entrance and exit geometry on PFRC-2. Rayleigh scattering experiments on PFRC have yielded the TS discrimination sensitivity to be >1 × 10 20 m –3 for the PDP. A recently implemented narrow-band notch spectral filter that masks the second harmonic 532 nm Nd:YAG laser wavelength has increased the system’s TS light discrimination sensitivity 65 times compared to the instance when the notch filter was not implemented. The hardware implementation including design changes to the flight tubes and Brewster windows will be discussed, along with results from Rayleigh and rotational Raman scattering sensitivity analyses, which were used to establish a quantitative figure of merit on the system performance. Further, the Raman scattering calibration with the notch filter has improved the PDP electron density threshold to 1 ± 0.5 × 10 18 m –3 .

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

DRDMannTurb: A Python package for scalable, data-driven synthetic turbulence

Synthetic turbulence models (STMs) are used in wind engineering to generate realistic flow fields and are employed as inputs to industrial wind simulations. Examples include prescribing inlet conditions in large eddy simulations that model loads on wind turbines and tall buildings. We are interested in STMs capable of generating fluctuations based on prescribed second-moment statistics since such models can simulate environmental conditions that closely resemble on-site observations. To this end, the widely used Mann model (see Mann, 1994, 1998) is the inspiration for DRDMannTurb. The Mann model is described by three physical parameters: a magnitude parameter influencing the global variance of the wind field and corresponding to the Kolmogorov constant multiplied by the rate of viscous dissipation of the turbulent kinetic energy to the two-thirds, αϵ 2/3 , a turbulence length scale parameter L, and a nondimensional parameter Γ related to the lifetime of the eddies. A number of studies, as well as international standards (e.g., those by the International Electrotechnical Commission (IEC)), include recommended values for these three parameters with the goal of standardizing wind simulations according to observed energy spectra. Yet, having only three parameters, the Mann model faces limitations in accurately representing the diversity of observable spectra. This Python package enables users to extend the Mann model and more accurately fit field measurements through flexible neural network models of the eddy lifetime function. Following Keith et al. (2021), we refer to this class of models as Deep Rapid Distortion (DRD) models. DRDMannTurb also includes a general module implementing an efficient method for synthetic turbulence generation based on a domain decomposition technique. This technique is also described in Keith et al. (2021).

17 WIND ENERGY↗
DOE OSTI2026

Modeling Framework for Data Center

This chapter highlights the critical need for advanced modeling of data centers due to their rapidly increasing energy consumption and impact on grid reliability. Driven by the demand for AI applications, data centers are projected to consume a significant portion of US energy by 2028, putting stress on an already challenged power grid. The chapter emphasizes the importance of "fast" time-scale models to understand the dynamic interactions between data centers and the grid, especially given the rapid power fluctuations of AI workloads. It outlines a modeling framework that includes both offline and real-time EMT domain simulations, detailing the necessary representations for various components like utility interfaces, transformers, IT loads, UPS, cooling loads, Battery Energy Storage Systems (BESS), generators, protection systems, and higher-level control systems. While standard simulation tools like PSCAD offer basic models, custom development is often required to accurately capture the unique and fast-changing behaviors of modern data centers. The chapter also discusses key metrics and test cases for validating these models, focusing on transient load responses, protection relay coordination, and demand flexibility. Finally, it addresses the challenges of modeling large-scale data centers, such as computational complexity and the trade-off between model fidelity and practicality, suggesting hybrid modeling approaches as a solution. The overarching goal is to create a robust framework that helps assess data center impacts on grid stability, identify vulnerabilities, and inform the development of standards for reliable integration of these large loads into the bulk power system.

25 ENERGY STORAGE↗
DOE OSTI2024

Titanium Dioxide Nanomaterial Ink Production Through Laser Ablation Synthesis in Solution for Printed Electronics Applications

Flexible and printed electronics have become increasingly popular as they make possible the production of flexible, low-cost, multifunction devices that are unachievable through traditional manufacturing methods. The printed films are significantly impacted and thus limited by the existing ink production process. Herein, an alternate technique of generating high-quality titanium dioxide (TiO 2 ) nanoparticle ink compatible with aerosol jet printing using laser ablation synthesis in solution (LASiS) is showcased. Dynamic light scattering data and transmission electron microscopy confirm the particle size distribution. UV–vis measurements are performed, and the Beer–Lambert relationship is used to determine the concentration of the generated ink. The inks generated at two different repetition rates are compared: 200 kHz and 1 MHz. X-Ray diffraction analysis of the aerosol jet printed thin film post-thermal sintering confirms the grain size and phase purity of the printed thin films. This work demonstrates the effectiveness of the LASiS technique in producing printable nanoparticle inks with little-to-no postprocessing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Change Agent: Energy Storage as a Driver of Regulatory Evolution

Purpose of Review Dividing the electric grid into the functions of generation, transmission, anddistribution enabled the drawing of jurisdictional lines and the application of the U.S.Constitution’s federalist system to energy regulation. Energy storage technologies,which can be placed throughout the grid to increase flexibility, can provide serviceacross all three of those functions. But the jurisdictional boundaries that have beendrawn around those functions have created barriers that restrict energy storagetechnologies from achieving their full potential. This review analyzes regulatory changes made to reduce barriers to storage deployment and their broader impacts on energy regulation in the U.S. Recent Findings Major energy regulations promulgated at the state and federal levels have generally focused on liberalizing the U.S. electric system through deregulation and increased competition. Paradoxically, however, these efforts have erected strict regulatory barriers that prevent energy storage technologies from providing service across multiple functions. A new wave of regulations in recent years has endeavored to reduce and remove those barriers. Summary Energy regulations adopted in recent years to reduce barriers to energy storage functionality in recent years have had deep and far-reaching impacts on U.S. electric regulation. These impacts go beyond storage and affect all energy technologies. This paper traces the development of energy regulation in U.S., the functional barriers that they created that impede energy storage functionality, recent efforts to remove those barriers, and the broader effects of those efforts. It concludes with a brief discussion of remaining barriers that prevent energy storage from reaching their full potential on the U.S. electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Cross-Linking and Charging Molecular Magnetoelectronics

Magnetoelectrics are witnessing an ever-growing success toward the voltage-controlled magnetism derived from inorganic materials. However, these inorganic materials have predominantly focused on the ferroelectromagnetism at solid-to-solid interfaces and suffered several drawbacks, including the interface-sensitive coupling mediators, high-power electric field, and limited chemical tunability. Here, we report a promising design strategy to shift the paradigm of next-generation molecular magnetoelectrics, which relies on the integration between molecular magnetism and electric conductivity though an in situ cross-linking strategy. Following this approach, we demonstrate a versatile and efficient synthesis of flexible molecular-based magnetoelectronics by cross-linking of magnetic coordination networks that incorporate conducting chain building blocks. Furthermore, the as-grown compounds feature an improved critical temperature up to 337 K and a room-temperature magnetism control of low-power electric field. It is envisaged that the cross-linking of molecular interfaces is a feasible method to couple and modulate magnetism and electron conducting systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Modelling and analysis of nuclear reactor system coupled with a liquid metal battery

Traditionally, nuclear power plants in the U.S. provide baseload power to the power grid because they have less flexibility for ramping their output power than natural gas peaking plants. However, achieving climate goals to reduce the consumption of fossil‐based natural gas places pressure on nuclear power plants and other power generators to ramp up their power output to balance grid generation with demand. This paper presents the modelling and performance analysis of a nuclear reactor system (NRS) coupled to a liquid‐metal battery (LMB) to improve its dynamic response and enable its black start capability. The NRS and LMB thermal behaviour are modelled in Dymola, while the electrical dynamics of the LMB and power grid are modelled in RTDS‐RSCAD. Both simulation platforms are coupled and share their thermal and electrical data using a Transmission Control Protocol/Internet Protocol (TCP/IP) communication protocol. The dynamic performance of the NRS‐LMB integration is tested on the IEEE 9 bus, which demonstrates its ability to respond and provide frequency and voltage regulation. The black start capability of the NRS‐LMB is also evaluated by simulating a grid outage and using the LMB to supply the auxiliary loads required to bring the NRS back online as soon as possible. The results show that coupling an NRS to an LMB improves the system dynamic performance and enables it to black start after being disconnected from the grid for several days.

25 ENERGY STORAGE↗