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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

SDN-Based Smart Cyber Switching (SCS) for Cyber Restoration of a Digital Substation

In recent years, critical infrastructure and power grids have increasingly been targets of cyber-attacks, causing widespread and extended blackouts. Digital substations are particularly vulnerable to such cyber incursions, jeopardizing grid stability. This paper addresses these risks by proposing a cybersecurity framework that leverages software-defined networking (SDN) to bolster the resilience of substations based on the IEC- 61850 standard. The research introduces a strategy involving smart cyber switching (SCS) for mitigation and concurrent intelligent electronic device (CIED) for restoration, ensuring ongoing operational integrity and cybersecurity within a substation. The SCS framework improves the physical network’s behavior (i.e., leveraging commercial SDN capabilities) by incorporating an adaptive port controller (APC) module for dynamic port management and an intrusion detection system (IDS) to detect and counteract malicious IEC-61850-based sampled value (SV) and generic object-oriented system event (GOOSE) messages within the substation’s communication network. The framework’s effectiveness is validated through comprehensive simulations and a hardware-in-the-loop (HIL) testbed, demonstrating its ability to sustain substation operations during cyber-attacks and significantly improve the overall resilience of the power grid.

Liu, Chen-Ching (ORCID:0000000289417958)↗
DOE OSTI2023

Ecosystem-Level Biomimicry for the Built Environment: Adopting Systems Ecology Principles for the Control of Heterogeneous Energy Systems

This paper presents, to our knowledge, the first system-level engineering study to bio-mimic the cybernetics and flow dynamics of energy resources in natural ecosystems for the control of heterogeneous energy infrastructures in the built environment. To this end, we introduce a novel Biomimetic Pulsing State (BPS) control that functionally mimics mature ecosystems. A preliminary Modelica-based case study features a single-family residential building with electrical and HVAC subsystems. The BPS control objective is to minimize the energy exchange between the building and the grid for the purposes of future self-supporting buildings and grid stability. The building contains PV, a wind turbine, a battery storage system, and a fan coil/heat pump HVAC system served by an ambient district energy network. Evaluating the control performance (BPS vs. constant setpoint) over several renewable energy scenarios (net importer, net zero, net exporter), simulation results show how the building's HVAC system can dynamically adjust its electrical load and temperatures to the electrical system's net energy status in real-time with BPS control. As a net importer, the heat pump consumed 29% less energy and its peak power reduced by 15% with BPS control compared to the constant setpoint case, with the zone air temperature 1 degree C lower on average. As a net exporter, the heat pump effectively consumed the same energy, but the peak power increased by 34% with BPS control, while the zone air temperature was 1 degree C higher when renewable energy was abundant, preheating the home. BPS and constant setpoint control produced comparable results under a net zero scenario. While further evaluation is essential, BPS control may help communities meet their sustainability and resiliency targets as they transition towards fully distributed and renewable energy grids.

biomimicry↗
DOE OSTI2013

High Performance, Low Cost Hydrogen Generation from Renewable Energy

Renewable hydrogen from proton exchange membrane (PEM) electrolysis is gaining strong interest in Europe, especially in Germany where wind penetration is already at critical levels for grid stability. For this application as well as biogas conversion and vehicle fueling, megawatt (MW) scale electrolysis is required. Proton has established a technology roadmap to achieve the necessary cost reductions and manufacturing scale up to maintain U.S. competitiveness in these markets. This project represents a highly successful example of the potential for cost reduction in PEM electrolysis, and provides the initial stack design and manufacturing development for Proton’s MW scale product launch. The majority of the program focused on the bipolar assembly, from electrochemical modeling to subscale stack development through prototyping and manufacturing qualification for a large active area cell platform. Feasibility for an advanced membrane electrode assembly (MEA) with 50% reduction in catalyst loading was also demonstrated. Based on the progress in this program and other parallel efforts, H2A analysis shows the status of PEM electrolysis technology dropping below $3.50/kg production costs, exceeding the 2015 target.

08 HYDROGEN↗
DOE OSTI2019

H2@Scale: Economic Potential of Hydrogen as an Energy Intermediate

The H2@Scale concept envisions hydrogen as an energy intermediate across multiple energy sectors. The concept is motivated both by the opportunity to produce hydrogen from low-cost energy resources, and by the many potential applications of hydrogen, including as energy for transportation - used directly in fuel cell electric vehicles (FCEVs), as a feedstock for synthetic fuels, and to upgrade oil and biomass - feedstock for industry (e.g., for ammonia production, metals refining, and other end uses), heat for industry and buildings, and electricity storage. A key hydrogen production opportunity is using variable renewable electricity (i.e., electricity generated by wind turbines or solar photovoltaic panels) during hours when generation exceeds the load on the grid as a source of low-cost, dispatch constrained electricity (LDE). In addition to producing low-cost hydrogen, electrolysis can also serve as a form of responsive load on the electric grid, which can enhance grid stability, reduce curtailment, and create a supplementary revenue stream for generators. The future use and adoption of hydrogen across end-use applications depends both the cost of hydrogen production and on each application's threshold price (i.e., the maximum price each application will pay for hydrogen - above that price, the application has an alternative that is more economic). We estimate economic potential of the hydrogen market - the quantity of hydrogen at an equilibrium price at which suppliers are willing to produce and consumers are willing to buy the same quantity of hydrogen - by developing supply and demand curves for hydrogen production and use. The demand curves are based on the threshold price for various quantities of hydrogen in each market, which is affected by projected prices for alternatives that could provide the same service (e.g., fuel for vehicles, feedstock for metals refining). The supply curves include hydrogen produced via natural gas steam methane reforming, high-temperature electrolysis coupled with nuclear power plants, biomass gasification, and low-temperature electrolysis using LDE. We use a range of market and technology-advancement assumptions to estimate the economic potential for five scenarios in the mid 21st century timeframe, and the corresponding impacts on energy use and emissions. We estimate hydrogen's economic potential to be 14-48 MMT/yr in the contiguous United States - corresponding to 1.5-5 times current annual consumption - depending on key assumptions about the future market conditions and the success of hydrogen production research and development (R&D) in our five scenarios. As a result of the estimated economic potential markets, we also approximate that grid-integrated electrolysis can increase the penetration of wind generation in the electricity market by providing a value stream for LDE, and that total U.S. fossil fuel use could decline below a scenario with high renewable penetration on the grid. We find that hydrogen has potential to provide technical and economic synergies when integrated across multiple sectors of the U.S. energy system, but continued R&D, infrastructure, and market development for LDE are required.

08 HYDROGEN↗
DOE OSTI2019

Flexible Geothermal Power Generation utilizing Geologic Thermal Energy Storage (Final Seedling Project Report)

This report concludes that there is a cost-effective strategy for seasonal storage of heat that will provide firm, but dispatchable, electrical generating capacity in times when other renewable energy is not available to meet demand. Deployment of the technology appears to require no new technology, but instead combines solar, geothermal, and conventional oil and gas drilling technologies in a novel way. The study basis is the use of sedimentary geologic formations as a medium for thermal energy storage (TES), specifically for heat collected in concentrating solar collectors. The study identifies methodologies that could be used to transport this heat into and out of the subsurface in order to produce dispatchable electrical power, and reports on initial optimization results. The GeoTES system (heat input, storage, heat recovery, and heat to electric conversion) described in this analysis has the potential to provide a unique pathway for increasing the grid penetration of renewable energy in large blocks of power and across many states and regions. Further, the system can be used both to meet the nation’s flexible energy needs while also improving grid stability and reliability. The present study evaluated the use of a large number of dedicated wells to store and recover the heat, essentially creating a synthetic geothermal reservoir. The use of sedimentary geology allows the wells to be drilled at low cost. Dedicated hot and cold wells are used, arranged in a five-spot well pattern with each hot or cold well surrounded at an appropriate distance by the opposite type of well. In large numbers this becomes alternating rows of hot and cold wells. Each hot and cold well is operated using a push-pull strategy. This configuration provides the ability to immediately recover stored hot fluid from a GeoTES reservoir, or to store the heat over many months for recovery at low loss when needed. This is a practical approach for managing the system’s fluid inventory and reducing parasitic load. The production and injection power requirements are reduced because the rows of wells operating in “push” mode provide help to the wells operating in “pull” mode, and vice-versa. Initial charging of a GeoTES system increases the heat recovery temperature. Increasing the duration of the charging period decreases the magnitude of the temperature fluctuations that occur following prolonged system operation. Because of direct contact of the heated water with the reservoir formation, the production of both hot water and steam from the TES, and the temperature ranges of the recovered fluid (190 – 230°C or 375 – 445°F), conventional geothermal power cycles were used to convert the stored heat to electricity. A power cycle configuration for the GeoTES system was selected following a screening study of a number of flash, and flash/binary hybrid options. This analysis concluded that, of the configurations evaluated, a dual-stage flash steam cycle provides the lowest capital costs per unit net power generation with an acceptable hot brine inlet fluid flow rate. The evaluation included the power plant cost estimate, the cost and number of wells and the associated parasitic loads. Annual power generation performance was simulated to evaluate capacity factor and LCOE. The LCOE calculated for the inherently high capacity GeoTES system was $\$$0.13/kWhe. This value was calculated for the case where the solar thermal collector was sized in such a way that the solar collectors permitted an annual power plant capacity factor of up to 97%. The power cycle was able to provide power to the grid every night of the year, and flexible base-load power during the winter, if needed. This LCOE value compares favorably with reported values for solar photovoltaic plus battery energy storage (PV+BES) systems in the open literature, i.e. $\$$0.148/kWhe for a PV+BES system with 4 hours of electrochemical battery energy storage capacity. Addition of battery energy storage with more hours of storage would further increase PV+BES system LCOE and increase the separation between GeoTES and PV+BES. A GeoTES system would therefore provide superior economics for high capacity and long duration solar energy storage.

14 SOLAR ENERGY↗
DOE OSTI2020

A Comprehensive Review on the Development of Solid–State Metal–Air Batteries Operated on Oxide–Ion Chemistry

The recently developed solid oxide metal–air redox battery (SOMARB) operating on oxide-ion chemistry represents an emerging and promising energy storage technology, which is well suited for managing grid stability and efficiently harvesting renewable energy. Compared to widely reported metal–air batteries operating on liquid-phase alkali-ion or alkaline chemistries, the SOMARB uniquely features a direct reduction of the high concentration of O 2 molecules in the gas phase without invoking the detrimental formation of a diffusion-blocking oxide phase on the surface of the oxygen electrode. A typical SOMARB is composed of a reversible solid oxide cell (RSOC) and an energy storage unit (ESU), which is capable of storing a high capacity of energy at high power without safety concerns. In this article, the SOMARB concept birth and development are reviewed and discussed with the fundamental differences separating it from other types of metal–air batteries, along with the challenges and opportunities around commercialization. Particular focus is placed on the functional materials tailored for ESU and RSOC applications, including recent experimental and computational efforts to boost the redox activity of Fe-based ESU materials and the performance of intermediate temperature RSOCs. Lastly, candid opinions are offered on the challenges and opportunities facing the future development of SOMARBs toward large-scale energy storage applications.

08 HYDROGEN↗
DOE OSTI2022

Grid‐responsive smart manufacturing: A perspective for an interconnected energy future in the industrial sector

Abstract With the growing amount of renewable energy sources, the grid has become responsible for accounting for intermittency and the flexibility needed to utilize dynamic sources. Expensive peaking plants and energy storage systems have been proposed as ways to mitigate those problems. There is a large group of energy consumers that can respond to grid conditions. Historically, these consumers have been residential and commercial users, but with modern innovations and practices, industrial consumers have the potential to become a major player in this space. Grid‐responsive smart manufacturing can be used to utilize modern tools in manufacturing innovation as enablers for grid response. These modern tools already exist but are not widely used for industrial grid‐side energy management. This article defines grid‐responsive smart manufacturing, identifies five major barriers to its widespread implementation, and portrays the path to getting industrial users to be key players in grid stability and flexibility.

Billings, Blake W.↗
DOE OSTI2022

Optimizing the physical design and layout of a resilient wind, solar, and storage hybrid power plant

We report as wind and solar technologies improve and their costs decrease, the share of power produced by these sources will increase. As the market penetration increases, these power sources will need to provide grid services, such as dispatchability, in addition to providing energy. One way to reduce variability, provide higher quality power to the grid, and address local grid stability issues is through colocating wind and solar power plants. In addition to operating reliably during normal operating conditions, in scenarios with high penetrations of renewable generation, it is important that these hybrid plants can withstand production disruptions and continue to supply power despite prolonged resource reduction, extreme weather events, or other disruptions. In this paper, we present a methodology to optimize a wind-solar-battery hybrid power plant down to the component level that is resilient against production disruptions and that can continually produce some minimum required power. We introduce the models and assumptions we used to simulate a hybrid power plant as well as the design variable parameterization and specific methods we used to optimize the plant. We demonstrate the performance of our method by comparing a plant optimized for different objectives, generation outage durations, minimum power requirements, and power purchase agreements. Although the plant design is sensitive to model parameters and various other assumptions, our results demonstrate some of the optimal designs that occur in different scenarios and what one should expect when designing a hybrid wind-solar-storage power plant.

14 SOLAR ENERGY↗
DOE OSTI2025

Hydropower and environmental flow management: System-level trade-offs at Glen Canyon Dam

The research focuses on the Colorado River Basin, specifically examining the Glen Canyon Dam (GCD) and its influence on surrounding aquatic ecosystems. This area is crucial due to its role in hydropower production and its impact on downstream environments, including the Grand Canyon National Park. This study explores the integration of environmental factors into hydro dispatch modeling at GCD to tackle ecological challenges posed by the invasive smallmouth bass (SMB). Utilizing the GTMax SL and SERM models, the research assesses the effects of SMB control experiments on hydropower generation, economic value, and grid stability. The study examines the financial and economic impacts of bypass flows designed to release colder water to prevent SMB spawning, which can significantly reduce hydropower output and increase costs. The research identifies that declining reservoir levels and rising water temperatures in Lake Powell have facilitated SMB spawning, posing a threat to native fish populations like the endangered humpback chub. The findings highlight the importance of adaptive management strategies to balance ecological preservation with hydropower generation amid long-term weather-related challenges. The study underscores the need for comprehensive assessments of flow options to prevent SMB establishment below GCD, considering the broader implications for sediment dynamics and ecological interactions.

Ecological impact assessment↗
DOE OSTI2025

A cross-dimensional analysis of data-driven short-term load forecasting methods with large-scale smart meter data

Electricity load forecasting is essential to utility operation and power grid stability. A wide spectrum of data-driven methods, ranging from linear regression models to more recent deep learning models have been adopted to forecast electric load over the years. However, there still lacks a holistic evaluation of the applicability of conventional statistical and machine learning based algorithms with respect to different temporal and spatial scopes, computational requirements, and sensitivity of model-tuning. Enabled by a large-scale electricity load profile dataset of over 40,000 residential customers in a utility region, we conducted a cross-dimensional analysis of data-driven load forecasting methods. Three regression-based and seven deep learning algorithms with different model configurations were evaluated in terms of their overall and peak load prediction accuracy, and training burdens, across spatial aggregation levels ranging from the transformer, feeder, substation, to neighborhood. We found, first, the load forecasting accuracy is constrained by a predictability boundary, influenced by the forecasting horizon and spatial aggregation level. Specifically, RandomForest, XGBoost, TFT, TSMixer, and TiDE models achieved less than 10 % prediction error for up to 96-h ahead forecasting for district, substation, and feeder levels, while other models struggle at long-horizon predictions; Second, for winter and summer peak load dates, most models were able to predict the peak demand timing within ± 1 h, but the prediction percentage error varied by models, with TFT and TiDE models being the top performers; Third, models with similar prediction accuracy can differ in training burden by an order of magnitude. Therefore, choosing model configurations that balance prediction performance and computational resource is an important practical consideration for large-scale deployment of the machine learning based load forecasting. The outcome of this study can guide researchers and practitioners to choose the proper load forecasting algorithms based on their problem scope, required accuracy, and available resources. The predictability boundary can serve as a benchmark for electricity load forecasting problems with new algorithms and datasets.

Li, Han↗
DOE OSTI2024

Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources

Here, this paper demonstrates a novel modular distributed framework that uses optimal energy-dispatching strategies to enable greater flexibility and profitability in nuclear-renewable integrated energy systems (NR-IES). Hydrogen is used as a commodity in this framework since its production can improve grid stability and system operational flexibility, decarbonize heavy industry, and create an additional revenue stream for electricity generators, particularly nuclear power plants with high operational expenses. The proposed solution addresses the challenges associated with merging multiple software and services from various domains by using functional mock-up units (FMU) to co-simulate diverse subsystems designed in various platforms. The tightly coupled integrated energy system (IES) is optimized to maximize revenue by utilizing the deep reinforcement learning (DRL) technique to make smart dispatching decisions based on variable electricity prices and the availability of renewable energy. Proximal policy optimization (PPO) algorithm is used in training and testing the DRL agent. Over a period of 120 days, the proposed hydrogen-based IES framework showed about 10% revenue boost compared to a non-hydrogen generating baseline IES while also providing an easily-adoptable framework which can help to improve the flexibility of future generation nuclear power plants.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

A systematic literature review on residential demand response with a focus on opportunities for low-income communities

Demand Response improves efficiency and grid stability, reducing peak load and total system costs. It can potentially contribute to other societal aspects, including mitigating climate change and improving air quality, health, stress levels, and comfort. This paper reviewed the literature on residential demand response programs in the United States, through the lens of the five energy justice principles, identifying and categorizing a set of 165 papers from 1960 to 2024. As a result, we observe significant progress in distributive justice, however, mostly focused on increasing participation rather than attending specific needs of historically marginalized communities. Concordantly, recognition and procedural justice dimensions are lagging, while cosmopolitan justice studies are scarce, underscoring a need to improve the measurement of impacts resulting from the implementation of demand response programs. Future research opportunities include the consolidation of standardized definitions and metrics, to better understand burdens and needs of diverse residential users. In terms of policy, collection and transparent access to standardized data is required as a condition to the design of flexible, customizable, transparent, and easy to navigate demand response programs. As a result, a better understanding of and engagement with customers has the potential to increase adoption rates, persistence in the program, and overall impacts for the system, households, and society.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Real-time optimization of multi-cell industrial evaporative cooling towers using machine learning and particle swarm optimization

Existing electrical generating stations must operate with greater flexibility due to increasing renewable energy penetration on the electrical grid, and many coal-fired power stations have transitioned away from baseload operation to load-following operation to aid in grid stability. In cases where multiple independently controlled cooling tower cells are used in parallel for the cooling purposes of such stations, there is an opportunity to increase plant efficiency through data-driven optimization across their full load ranges. This work presents a novel application of real-time optimization using machine learning and particle swarm optimization on a multi-cell induced-draft cooling tower servicing a coal-fired power station under variable load. This is the first work to demonstrate simultaneous optimization of a multi-cell cooling tower, in addition to using machine learning for closed-loop control on a cooling tower. A novel control configuration is presented that ensures original control logic is not adversely affected and that the overall plant process is not disrupted using only existing hardware and operational data. To verify this methodology, the 12 independent cooling tower cells are simulated in parallel using historic operating data to demonstrate the effectiveness of real-time optimization compared to current practice. An artificial neural network is trained to predict overall cooling tower power consumption using only operational data and ambient conditions with an R2 value of greater than 0.96. The real-time optimization using particle swarm yields 6.7% annual energy usage savings compared to current practices, although the extent of the real-time savings varies greatly with both plant load and environmental conditions. This is particularly significant for a variable load situation because frequent ramping typically results in reduced overall efficiency. Furthermore, this proposed AI-based solution presents an opportunity to improve the overall heat rate of a load-following coal-fired power plant without the need to perform extensive first-principles modeling or add additional hardware to the cooling tower, resulting in more resources conserved and less overall emissions per unit of electricity generated.

42 ENGINEERING↗
DOE OSTI2025

Surface modification of cathode material enhances electrochemical performance in dry-processed Li-ion battery electrodes

The transition to electric vehicles (EVs) is pivotal for achieving energy security and integrating grid stability, with lithium-ion batteries (LIBs) playing a central role in this transformation. However, the conventional wet electrode manufacturing relying on N-methyl-2-pyrrolidone (NMP) solvent is energy intensive and costly. Dry processing (DP) has emerged as a promising alternative, eliminating solvents and using polytetrafluoroethylene (PTFE) binder for electrode fabrications. Despite its advantages, DP faces a critical challenge: poor interfacial adhesion between the hydrophobic PTFE binder and the hydrophilic cathode active material (CAM), particularly LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811), which undermines electrode performance. Here, to address this, we introduced a novel vapor-phase trimethoxymethylsilane (TMMS) coating to hydrophobize the CAM surface, enhancing compatibility with PTFE. This surface modification significantly enhances binder – CAM interactions, enabling uniform mixing and robust electrode integrity without damaging the CAM particles. Our findings advance the feasibility of environmentally sustainable and cost-effective dry processing, representing a significant step toward sustainable battery manufacturing.

Choi, Junbin [Oak Ridge National Laboratory (ORNL)↗
DOE OSTI2016

A symmetric organic-based nonaqueous redox flow battery and its state of charge diagnostics by FTIR

Redox flow batteries have shown outstanding promise for grid-scale energy storage to promote utilization of renewable energy and improve grid stability. Nonaqueous battery systems can potentially achieve high energy density because of their broad voltage window. In this paper, we report a new organic redox-active material for use in a nonaqueous redox flow battery, 2-phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (PTIO) that has high solubility (>2.6 M) in organic solvents. PTIO exhibits electrochemically reversible disproportionation reactions and thus can serve as both anolyte and catholyte redox materials in a symmetric flow cell. The PTIO flow battery has a moderate cell voltage of ~1.7 V and shows good cyclability under both cyclic voltammetry and flow cell conditions. Moreover, we demonstrate that FTIR can offer accurate estimation of the PTIO concentration in electrolytes and determine the state of charge of the PTIO flow cell, which suggests FTIR potentially as a powerful online battery status sensor. In conclusion, this study is expected to inspire more insights in this under-addressed area of state of charge analysis aiming at operational safety and reliability of flow batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Damping inter-area oscillation using reinforcement learning controlled TCSC

Appropriate damping control of the inter-area oscillation would ensure the grid stability and maintain the tie-line power transfer capability. In this paper, we proposed a novel reinforcement learning (RL) based power oscillation damping (POD) controller that uses Thyristor Controlled Series Compensators (TCSC) to damp inter-area oscillations. By leveraging the unbiased gradient direction estimation of the natural evolution strategy (NES), we successfully regulated the power flows on the tie-lines and damped inter-area oscillations through dynamically modulating the inserted reactance of the TCSC. The proposed RL-based POD controller has been tested on both two-area four-machine system and North American Minni-WECC system. Extensive studies have demonstrated the excellent performance of the proposed RL-based TCSC POD controller in damping inter-area oscillations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Packaging - Materials review

Nowadays, a large number of different electrochemical energy storage systems are known. In the last two decades the development was strongly driven by a continuously growing market of portable electronic devices (e.g. cellular phones, lap top computers, camcorders, cameras, tools). Current intensive efforts are under way to develop systems for automotive industry within the framework of electrically propelled mobility (e.g. hybrid electric vehicles, plug-in hybrid electric vehicles, full electric vehicles) and also for the energy storage market (e.g. electrical grid stability, renewable energies). Besides the different systems (cell chemistries), electrochemical cells and batteries were developed and are offered in many shapes, sizes and designs, in order to meet performance and design requirements of the widespread applications. Proper packaging is thereby one important technological step for designing optimum, reliable and safe batteries for operation. In this contribution, current packaging approaches of cells and batteries together with the corresponding materials are discussed. The focus is laid on rechargeable systems for industrial applications (i.e. alkaline systems, lithium-ion, lead-acid). In principle, four different cell types (shapes) can be identified - button, cylindrical, prismatic and pouch. Cell size can be either in accordance with international (e.g. International Electrotechnical Commission, IEC) or other standards or can meet application-specific dimensions. Since cell housing or container, terminals and, if necessary, safety installations as inactive (non-reactive) materials reduce energy density of the battery, the development of low-weight packages is a challenging task. In addition to that, other requirements have to be fulfilled: mechanical stability and durability, sealing (e.g. high permeation barrier against humidity for lithium-ion technology), high packing efficiency, possible installation of safety devices (current interrupt device, valve, etc.), chemical inertness, cost issues, and others. Finally, proper cell design has to be considered for effective thermal management (i.e. cooling and heating) of battery packs.

25 ENERGY STORAGE↗