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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 343 records · Page 19

Research Priorities and Opportunities in United States Wholesale Electricity Markets

The power system is currently undergoing a number of changes, including a rapidly evolving resource mix, growth of distributed energy resources (DERs), more active consumer participation, increased deployment of energy storage and hybrid resources, and more advanced communication and control requirements. These changes in the power system present numerous technical, economic, implementation, and policy challenges and research opportunities for power system operators. To help address these challenges, a collaboration among five research institutions—Argonne National Laboratory, the National Renewable Energy Laboratory, Lawrence Berkeley National Laboratory, the Electric Power Research Institute, and Johns Hopkins University—has been established to provide technical assistance to the seven U.S. Independent System Operators (ISOs) and Regional Transmission Organizations (RTOs). The 3-year project aims to leverage the advanced methods, tools, datasets, and resources of the collaborators to provide robust analytical support to address the high-priority market challenges that will be faced in the 2- to 10-year time horizon.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Integrated Energy-Water Data for Cross-Sector Resilience

This white paper focuses on the “energy-for-water” domain, addressing the urgent need for integrated, empirical data to support regional management, benchmarking, and research on improving efficiency and developing technologies for water and wastewater management systems. The costs and energy required for the supply, treatment, and distribution of water and wastewater lack a standard data collection mechanism and centralized database or storage infrastructure, limiting data-driven decision-making across interdependent infrastructure systems.

42 ENGINEERING↗

Accurate and Rapid Forecasts for Geologic Carbon Storage via Learning-Based Inversion-Free Prediction

Carbon capture and storage (CCS) is one approach being studied by the U.S. Department of Energy to help mitigate global warming. The process involves capturing CO 2 emissions from industrial sources and permanently storing them in deep geologic formations (storage reservoirs). However, CCS projects generally target “green field sites,” where there is often little characterization data and therefore large uncertainty about the petrophysical properties and other geologic attributes of the storage reservoir. Consequently, ensemble-based approaches are often used to forecast multiple realizations prior to CO 2 injection to visualize a range of potential outcomes. In addition, monitoring data during injection operations are used to update the pre-injection forecasts and thereby improve agreement between forecasted and observed behavior. Thus, a system for generating accurate, timely forecasts of pressure buildup and CO 2 movement and distribution within the storage reservoir and for updating those forecasts via monitoring measurements becomes crucial. This study proposes a learning-based prediction method that can accurately and rapidly forecast spatial distribution of CO 2 concentration and pressure with uncertainty quantification without relying on traditional inverse modeling. The machine learning techniques include dimension reduction, multivariate data analysis, and Bayesian learning. The outcome is expected to provide CO 2 storage site operators with an effective tool for timely and informative decision making based on limited simulation and monitoring data.

58 GEOSCIENCES↗

Scale tests of the new DUNE data pipeline

In preparation for the second runs of the ProtoDUNE detectors at CERN (NP02 and NP04)[1], DUNE has established a new data pipeline for bringing the data from the EHN-1 experimental hall at CERN to primary tape storage at Fermilab and CERN, and then spreading it out to a distributed disk data store at many locations around the world. This system includes a new Ingest Daemon and a new Declaration Daemon. The Rucio[2] replica catalog, and FTS3 transport are used to transport all files. All file metadata is declared to the new MetaCat[3] metadata service. All of these new components have been successfully tested at a scale equal to the expected output of the detector data acquisition system (~2-4 GB/s), and the expected network bandwidth out of the experimental hall. We present the procedure that was used to test and the results of the test.

Timm, Steven↗

Reinforcement Learning for Distribution Grid Optimization (PyCIGAR) v0.1

PyCIGAR is a python software package that merges off-the-shelf reinforcement learning libraries (RLLib and Ray) with electric power distribution system simulation tools (OpenDSS and a custom power flow solver built by LBL). PyCIGAR enables the training of neural networks to optimize the behavior of different components in the electric distribution grid, such as control systems in photovoltaic rooftop solar inverters and electric battery storage systems. The software package has been used to train neural networks to update settings in photovoltaic rooftop solar inverter control systems to mitigate cyber attacks on other solar photovoltaic rooftop devices.

Arnold, Daniel↗

Decarbonizing the U.S. Economy by 2050: A National Blueprint for the Buildings Sector

Residential and commercial buildings are among the largest sources of carbon dioxide and other greenhouse gas (GHG) emissions in the United States, responsible for more than one-third of total U.S. GHG emissions. There are nearly 130 million existing buildings in the United States, with 40 million new homes and 60 billion square feet of commercial floorspace expected to be constructed between now and 2050. Today, most buildings consume large amounts of energy and cause significant climate pollution to meet our basic needs. Buildings account for 74% of U.S. electricity use and building heating and cooling drives peak electricity demand. Moreover, buildings are where electric vehicles (EVs), solar, storage, heat pumps, water heaters, and other distributed energy resources integrate with the electricity system. Consequently, the buildings sector will play a key role in achieving economywide net-zero emissions by 2050.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integrated protonic ceramic electrochemical cell for sustainable energy economy using water-energy nexus framework

Reliance on fossil fuels will continue for the next decades even though there are global pushes away from it to mitigate the overarching climate challenge, most especially by its highest consumers and availability. While there is a hastening global shift away from fossil fuel, integrating its assets into this technology helps limit the risk and future losses of stranded assets and reduce the cost of investment in the new technologies. Moreover, the generation of electricity from intermittent renewable sources like solar and wind has witnessed a significant surge in recent years, leading to a pressing demand for practical energy storage systems. Electrical energy storage is anticipated to play a pivotal role in the future global energy system, facilitating load-leveling operations to support the greater integration of renewable and distributed generation. Reversible electrochemical cells (RECs) offer a promising option for addressing the fossil fuel assets integration and energy storage challenges through the interconversion between electrical and chemical energy and concurrent utilizing carbon emission. In their electrolysis mode, the RECs convert electricity into durable, storable, and portable valuable chemical fuels such as syngas and methane. Conversely, the produced chemical fuels can be used as reactants in the fuel cell mode to generate electricity on demand with minimal (hydrocarbons) or zero when H2 or NH3 is used emissions. However, a challenging goal for this type of technology remains to achieve optimal operation and high roundtrip efficiencies, which has hindered the deployment of previous electrochemical cells. This dissertation demonstrates how reversible protonic ceramic electrochemical cells (RePCECs) can be integrated with fossil fuel power plants and renewable energy sources as a potential energy storage system. In this work, integrated RePCEC systems are designed and examined using computational modeling at scales to determine appropriate system configurations and operating conditions that achieve high roundtrip efficiencies. Cell level design of the PCEC is the first approach, several cells are assembled for the stack level model that is integrated into combined cycle powerplant and solar photovoltaic for the system level model. After critical literature review, this answered the operational and integration research questions proposed to address these challenges. The designed systems perform two functions, utilizing captured CO2 and storing renewable energy through co-electrolysis of steam and CO2. The co-electrolysis reaction involves endothermic water electrolysis and exothermic methanation reaction. To enhance high roundtrip efficiency, there is a need for thermal balance and management in the electrolysis mode. This involves operating the RePCEC stack under conditions that favor methane production to balance out heat needed by water electrolysis, it crucial for the RePCEC system operation. Methanation is enhanced by low temperatures. Leveraging on fabricated BCZYYb-electrolyte RePCEC, the cell model designed revealed that the optimum temperature for methane production is 450℃ at atmospheric pressure. Thus, to achieve optimum system performance, operating in the temperature range 450-525℃ is recommended at the given configuration, combining between the optimum temperature for methane production and temperature for the optimum stack roundtrip efficiency. Configuration with carbon capture system and purge stream is the optimum configuration from the seven conceptualized and evaluated. The modeling outcomes include a thermodynamic examination of integrated RePCEC systems, calibration of cell and stack level models, and steady-state simulation and integration into a 600MW combined cycle power plant retrofitted with two two-stage membrane-based carbon capture system and a wastewater treatment and recovery unit. At 100% powerplant loading, the stack and system roundtrip efficiencies are 72% and 51.37% respectively. Adding a purge stream for produced hydrogen at the system downstream improves the efficiencies to 74 and 55.48% respectively. At atmospheric pressure and 525℃, the system model suggests that a stack roundtrip of 82% is achievable, and overall system efficiency increases by reducing the energy consumption by the balance of plant components for steam generation and storage. Economic analysis of the process gives levelized cost of methane as $2.24/MMBtu lower than the conventional production route that range between $3.46/MMBtu and $9.85/MMBtu. The lifecycle analysis shows that the global warming potential for the production of methane and hydrogen from the RePCEC system is 3.83 kg CO2 eq which is lower than 9.35 kg CO2 eq emission during steam methane reforming for hydrogen production. This answered both the environmental and economic concerns in the raised research question. The proposed RePCEC configuration and analysis carried out in this dissertation to address the surge in renewable energy and challenges with PCEC technology hold significant potential in achieving large-scale energy storage while simultaneously reducing carbon emissions. These advancements, coupled with suitable governmental policies and incentive programs, have the potential to economically disrupt the natural gas industries by using RePCEC systems for methane production, thereby making them more favorable for eventual implementation and commercialization.

25 ENERGY STORAGE↗

Integrated Systems-to-Atoms (S2A) Framework for Designing Resilient and Efficient Hydrogen Infrastructure Solutions

The success of a future clean hydrogen infrastructure will depend on technology performance, operating conditions, and system configuration, which will be integrated to meet specific end-use requirements. We introduce a Systems-to-Atoms framework to cosimulate material, device, and system design for clean hydrogen storage and transport. Here we present a demonstration scenario in which hydrogen is distributed using a liquid organic hydrogen carrier to 700 bar refueling stations. Cross-scale analysis on hydrogen release at the refueling station reveals that while a high reaction pressure (up to 100 bar) may not enhance the catalyst performance, it can lead to system-level cost savings (up to 5% of total refueling station cost) due to savings in downstream gas compression. Further, a typically low-performing dehydrogenation catalyst material (e.g., copper) may be preferred over a high-performing catalyst (e.g., palladium) at different operating conditions when considering overall system affordability and supply chain resilience.

08 HYDROGEN↗

All Hazards Approach to Grid Modernization

Resilience hazards for electric power systems are on the rise, exacerbated by both a rise in extreme weather events and manmade physical and cyber attacks. At the same time, grid modernization challenges plague the United States, covering everything from increased electrification and ambitious renewable energy targets to aging infrastructure and regulation that lags behind today’s challenges. This talk will cover an all-hazards risk based approach that addresses both rising resilience and grid modernization challenges. Examples of this approach taken for national laboratory research projects will be discussed, including a deep dive into a project that addressed black start, resynchronization, distributed control, and cybersecurity challenges for an operational microgrid up to sub-transmission voltages. As takeaways from this project are translated from demonstration scale to real-world exercises, key lessons are noted on the translation from research into practice and how this can inform risk-based research moving forward

17 WIND ENERGY↗

Technical Assistance for Guam Power Authority

Through the Energy Technology Innovation Partnership Project (ETIPP), Guam Power Authority learned approaches to evaluate existing infrastructure to maximize distributed local energy generation without damaging existing system components.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SiC-Based 5-kV Universal Modular Soft-Switching Solid-State Transformer (M-S4T) for Medium-Voltage DC Microgrids and Distribution Grids

Medium-voltage DC (MVDC) grids are attractive for electric aircraft and ship power systems, battery energy storage system (BESS), fast charging electric vehicle (EV), etc. Such EV or BESS applications need isolated bidirectional MVDC to LVDC or LVAC converters. However, the existing Si-based solutions cannot fulfill the requirements of a high-efficiency and robust converter for MVDC grids. This paper presents a 5 kV SiC-based universal modular solid-state transformer (SST). This universal current-source SST can interface either a LVAC or LVDC grid with a MVDC grid in single-stage power conversion, while the conventional dual active bridge (DAB) converter needs an additional inverter. The proposed SST module using 3.3 kV SiC MOSFETs and diodes is bidirectional and can serve as a building block in series or parallel for higher-voltage higher-power systems. The topology of each module is based on the soft-switching solid-state transformer (S4T) with reduced conduction loss, which features reduced EMI through controlled dv/dt, and high efficiency with full-range ZVS for main devices and ZCS for auxiliary devices. Operation principle of the modular S4T (M-S4T), capacitor voltage balancing control between the cascaded modules, design of components including a medium-voltage (MV) medium-frequency transformer (MFT) to realize a 50 kVA 5 kV DC to 600 V DC or 480 V AC M-S4T are presented. Importantly, the MV MFT prototype achieves very low leakage inductance (0.13%) and 15 kV insulation with coaxial cables and nanocrystalline cores. Here, the proposed universal modular SST is compared against the DAB solution and verified with DC-DC and DC-AC simulation and 4 kV experimental results. Significantly, the MV experimental results of a modular DC transformer with each module at MVDC are rarely covered in the literature and reported for the first time.

14 SOLAR ENERGY↗

COVID 19 vaccine distribution solution to the last mile challenge: Experimental and simulation studies of ultra-low temperature refrigeration system

Most COVID-19 vaccines require ambient temperature control for transportation and storage. Both Pfizer and Moderna vaccines are based on mRNA and lipid nanoparticles requiring low temperature storage. The Pfizer vaccine requires ultra-low temperature storage (between -80 °C and -60 °C), while the Moderna vaccine requires -30 °C storage. Pfizer has designed a reusable package for transportation and storage that can keep the vaccine at the target temperature for 10 days. However, the last stage of distribution is quite challenging, especially for rural or suburban areas, where local towns, pharmacy chains and hospitals may not have the infrastructure required to store the vaccine. Also, the need for a large amount of ultra-low temperature refrigeration equipment in a short time period creates tremendous pressure on the equipment suppliers. In addition, there is limited data available to address ancillary challenges of the distribution framework for both transportation and storage stages. As such, there is a need for a quick, effective, secure, and safe solution to mitigate the challenges faced by vaccine distribution logistics. The study proposes an effective, secure, and safe ultra-low temperature refrigeration solution to resolve the vaccine distribution last mile challenge. Furthermore, the approach is to utilize commercially available products, such as refrigeration container units, and retrofit them to meet the vaccine storage temperature requirement. Both experimental and simulation studies are conducted to evaluate the technical merits of this solution with the ability to control temperature at -30 °C or -70 °C as part of the last mile supply chain for vaccine candidates.

60 APPLIED LIFE SCIENCES↗

Lessons Learned From Techno-Economic Analysis of Solar Photovoltaics and Battery Energy Storage at a Vietnam Industrial Park

Through the Clean Energy Investment Accelerator (CEIA), engineers from the United States (U.S.) National Renewable Energy Laboratory (NREL) conducted a case study analysis evaluating the techno-economic feasibility of battery energy storage systems (BESS) at an industrial park in Vietnam. The analysis uses NREL's REopt platform, a distributed energy modeling and optimization tool, to identify the cost-optimal system sizing for BESS, in conjunction with onsite renewables such as solar photovoltaics (PV), to reduce electricity costs, increase onsite renewable energy generation utilization, and improve resilience to grid outages.

batteries↗

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement: Preprint

Distribution system resilience enhancement is an important topic to ensure customers have access to the power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecasts. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement

Distribution system resilience enhancement is an important topic to ensure customers have access to power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecast. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗

FLISR in the Presence of DERs ADMS Test Bed Use Case

Fault location, isolation, and restoration (FLISR) is one of the distribution automation applications that utilities are most interested in. It operates groups of switches on distribution feeders to improve the reliability of power delivery after localizing outages. FLISR is an essential function for enabling a self-healing grid, and it directly affects grid reliability and resilience. The presence of DERs brings both new opportunities and challenges for FLISR applications. For instance, some DERs can work as backup generation sources and help energize local networks so more switching options can be achieved with the coordination of FLISR operations; however, the existence of DERs also brings new challenges. The bidirectional power flow resulting from DERs might require dynamic changes to protective devices' fault current settings, and thus the FLISR application will need to dynamically adjust its operations in coordination with the dynamic protection settings. Also, some FLISR applications make their service restoration decisions and close tie-switches based on predefined rules; however, the presence of DERs and their impact on altering net loads on the local feeder network are not considered. For this use case, the project team is using the FLISR application of the Survalent ADMS operating on a real-time simulation of a feeder from Central Georgia EMC, a cooperative electric utility. The performance of the FLISR application is being evaluated for different locations and combinations of DERs, including grid-forming battery energy storage systems.

ADMS↗

Voltage Restoration in Microgrids using Temporal Logic Specifications

This paper proposes an energy storage controller synthesis method for voltage restoration in microgrids with respect to temporal logic specifications (TLSs). TLSs is introduced in this paper as a formalism to control the voltage variation of a critical bus against an operational bounds over time. The power system with synchronous generator (SG) connected to a critical load bus is modeled as a set of differential-algebraic equations and a simplified analytical model is derived to describe the voltage variation of this critical bus. The control objective is to schedule an optimal control input signal from a supportive energy storage system (ESS) connected to the critical bus, such that the voltage variation of the latter satisfies the TLSs, such as a finite-time restoration. The proposed control is verified on a lumped distribution system model. With this control diagram, supportive controllers can be designed to make voltage behaviors comply with grid codes and avoid unnecessary relay actions.

Taousser, Fatima Zohra↗

Fiber optic system for direct detection of CO 2 leakage in carbon storage wells (Abbreviated Final Report)

The feasibility study focused on the development of new fiber for distributed chemical sensing that will allow direct detection of CO2 leakages in the environment. This is particularly important for monitoring well integrity for carbon capture and storage (CSS), which can provide early warning for an incoming well failure and potential CO2 leaking through it. We proposed Raman or IR interrogation within gas-filled Holey Fibers (HoFs) interleaved with Fiber Bragg Grating (FBG) sections, so that the location and concentration of the gases would be provided simultaneously. The methodology would overcome current roadblocks to using fiber optics for CO2 (and other gases) detection in wells with direct in-situ measurements of concentration along with other important parameters such as temperature and pressure. We were able to assess commercially available IR/Raman hollow core fiber and demonstrated detection of CO2 through them in our controlled environment setups at various pressure conditions. We have also established the ability of drilling precisely with fs-lases side holes to enable penetration of CO2 into the hollow core fiber and reduce diffusion rates. Open joint collars were also explored with double functionality: to obtain splice to solid core fiber critical for field deployment and create gas ingress locations. Both diffusion-only and pressurized fiber system have been constructed following COMSOL based semi-hybrid optical /fluidodynamics models. FBGs have been identified and procured and characterized. Along the work we leveraged internal modeling/design, photonics/laser characterization, optical fiber fabrication, and AM lab capabilities to design, develop and test in-house components or assemblies. Our results indicate the potential of HoF for CO2 downhole direct detection.

25 ENERGY STORAGE↗