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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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The presentation, released quarterly, reviews major trends that occurred in the solar industry in 2019 and the first quarter of 2020. Major topics of focus will be global and U.S. supply & demand, module & system price, investment trends, and updates on U.S. government programs supporting the solar industry.
As the U.S. offshore wind market prepares for rapid growth, our understanding of specific workforce requirements and pathways to meet those requirements is not keeping pace. Without this deeper understanding, there is a risk that the workforce will not develop as efficiently or robustly as is needed to fully realize the benefits of offshore wind. The "U.S. Offshore Wind Workforce Assessment" provides a more detailed assessment of the workforce demand, supply, and pathways to support key stakeholders including industry, state and local governments, educational organizations, and unions in their efforts to attract, educate, train, and retain a domestic workforce to support this burgeoning industry.
Battery storage systems are increasingly being installed at photovoltaic (PV) sites to address supply-demand balancing needs. Although there is some understanding of costs associated with PV operations and maintenance (O&M), costs associated with emerging technologies such as PV plus storage lack details about the specific systems and/or activities that contribute to the cost values. This study aims to address this gap by exploring the specific factors and drivers contributing to utility-scale PV plus storage systems (UPVS) O&M activities costs, including how technology selection, data collection, and related and ongoing challenges. Specifically, we used semi-structured interviews and questionnaires to collect information and insights from utility-scale owners and operators. Data was collected from 14 semi-structured interviews and questionnaires representing 51.1 MW with 64.1 MWh of installed battery storage capacity within the United States (U.S.). Differences in degradation rate, expected life cycle, and capital costs are observed across different storage technologies. Most O&M activities at UPVS related to correcting under-performance. Fires and venting issues are leading safety concerns, and owner operators have installed additional systems to mitigate these issues. There are ongoing O&M challenges due the lack of storage-specific performance metrics as well as poor vendor reliability and parts availability. Insights from this work will improve our understanding of O&M consideration at PV plus storage sites.
Oak Ridge National Laboratory (ORNL), in collaboration with the Pacific Northwest National Laboratory (PNNL), the National Renewable Energy Laboratory (NREL), the Lawrence Berkeley National Laboratory (LBNL), and the Hummingbird Firm (a specialized consulting firm focused on promoting diversity, equity, and inclusion considerations), has initiated a national initiative known as the Heat Pump (HP) and Heat Pump Water Heater (HPWH) Field Validation Partnership. This effort involves active participation from numerous critical entities involved in research and market transformation within the field. The ORNL team is responsible for leading Late-Stage Research Development and Demonstration (LSRDD) among the four different topics. The overall outcomes of this project will be: (1) A structured Field Validation Partnership between DOE, the national labs, research, implementation, and market transformation organizations. This will result in unique way to coordinate field validation plans and collect relevant data from around the country into the HP and HPWH Field Validation Database. (2) The Field Validation Partnership will result in a continuous stream of information between DOE and the major industry players in the space of HPs and HPWHs. If desired, DOE could use this information to inform roadmaps related to HP and HPWH market adoption and research going forward. (3) The structure of this Partnership provides a mechanism for sharing lessons learned directly between Late-Stage RD&D, Building Integration Barriers, Regional Market and Policy and Workforce Development efforts. The result will be training content that is well-reviewed by the Partnership which will lead to a workforce that meets the industry’s quality and workforce supply demands. (4) The structure of this Partnership also provides an opportunity for regions to share lessons learned on policy and market transformation with each other through the Market and Policy core Committee. This report includes an update in Late-Stage Research Development and Demonstration.
The global shift towards renewable energy sources to mitigate fossil fuel dependency and meet carbon emission targets by 2050 has underscored the importance of innovative solutions to address energy supply-demand imbalances. Underground Hydrogen Storage (UHS) has emerged as a promising strategy to store excess renewable energy in subsurface formations for future retrieval and utilization. This report focuses on enhancing the site screening process for UHS facilities. By drawing on insights from prior research to identify key criteria influencing site suitability, our objective is to present a comprehensive set of sixteen specific criteria essential for refining the selection of UHS sites. These criteria cover various aspects such as reservoir performance, legal access, regulatory compliance, economic viability, public acceptance, and safety and security considerations. Our proposed methodology allows users to evaluate potential sites using binary responses, transitioning from isolated factors to broader considerations that facilitate a qualitative assessment of site suitability. This method enables comparative analysis and informed decision-making, supporting stakeholders in the site selection process. Our approach is designed as a guiding framework rather than a rigid template for site screening, emphasizing the importance of customizing approaches to individual circumstances. As UHS site development project evolves, adopting a comprehensive selection methodology that integrates holistic evaluations will be essential for ensuring efficient and effective site screening processes tailored to specific project needs.
The global shift towards renewable energy sources to mitigate fossil fuel dependency and meet carbon emission targets by 2050 has underscored the importance of innovative solutions to address energy supply-demand imbalances. Underground Hydrogen Storage (UHS) has emerged as a promising strategy to store excess renewable energy in subsurface formations for future retrieval and utilization. This report focuses on enhancing the site screening process for UHS facilities. By drawing on insights from prior research to identify key criteria influencing site suitability, our objective is to present a comprehensive set of sixteen specific criteria essential for refining the selection of UHS sites. These criteria cover various aspects such as reservoir performance, legal access, regulatory compliance, economic viability, public acceptance, and safety and security considerations. Our proposed methodology allows users to evaluate potential sites using binary responses, transitioning from isolated factors to broader considerations that facilitate a qualitative assessment of site suitability. This method enables comparative analysis and informed decision-making, supporting stakeholders in the site selection process. Our approach is designed as a guiding framework rather than a rigid template for site screening, emphasizing the importance of customizing approaches to individual circumstances. As UHS site development project evolves, adopting a comprehensive selection methodology that integrates holistic evaluations will be essential for ensuring efficient and effective site screening processes tailored to specific project needs.
The increased penetration of renewable generation induces unbalanced demand-supply on a power grid, while integrated energy systems (IES) can provide high part-load efficiency and high flexibility to support grid resilience. To study the transients and improve dynamic operability, it’s important to investigate the interplay between IES and power grid concurrently using real-time co-simulation approaches. In this presentation, we showed the previous co-simulation test between NETL and INL and discussed how this co-simulation can be beneficial for both IES and power grid research. In addition, we gave an overview about the SuperLab2.0 project, which was a federated national platform to address future power grid challenges. (Virtual presentation to the MILLENNIUM CLEAN and SUSTAINABLE POWER workshop 2025).
With the increasing awareness for sustainable future and green energy, the demand for electric vehicles (EVs) is growing rapidly, thus placing immense pressure on the energy grid. To alleviate this, local trading between EVs should be encouraged. In this paper, we propose a blockchain and public key infrastructure (PKI)-based secure vehicle-to-vehicle (V2V) energy-trading protocol. A permissioned blockchain utilizing the proof of authority (PoA) consensus and smart contracts is used to securely store data. Encrypted communication is ensured through transport layer security (TLS), with PKI managing the necessary digital certificates and keys. A multi-leader, multi-follower Stackelberg game-based trade algorithm is formulated to determine the optimal energy demands, supplies, and prices. Finally, we propose a detailed communication protocol that ties all the components together, enabling smooth interaction between them. Key findings, such as system behavior and performance, scalability of the trade algorithm and the blockchain, smart contract execution costs, etc., are presented through numerical results by implementing and simulating the protocol in various scenarios. This work not only enhances local energy trading among EVs, encouraging efficient energy usage and reducing burden on the power grid, but also paves a way for future research in sustainable energy management.
The share of wind power in power systems is increasing dramatically, and this is happening in parallel with increased penetration of solar photovoltaics, storage, other inverter-based technologies, and electrification of other sectors. Recognising the fundamental objective of power systems, maintaining supply–demand balance reliably at the lowest cost, and integrating all these technologies are significant research challenges that are driving radical changes to planning and operations of power systems globally. In this changing environment, wind power can maximise its long-term value to the power system by balancing the needs it imposes on the power system with its contribution to addressing these needs with services. A needs and services paradigm is adopted here to highlight these research challenges, which should also be guided by a balanced approach, concentrating on its advantages over competitors. The research challenges within the wind technology itself are many and varied, with control and coordination internally being a focal point in parallel with a strong recommendation for a holistic approach targeted at where wind has an advantage over its competitors and in coordination with research into other technologies such as storage, power electronics, and power systems.
University of California investigations to determine the usefulness of modern remote sensing techniques have concentrated on the water resources of the state. The studies consider in detail the supply, demand, and impact relationships.
Since May 1970, personnel on several campuses of the University of California have been conducting investigations which seek to determine the usefulness of modern remote sensing techniques for studying various components of California's earth resources complex. Emphasis has been given to California's water resources as exemplified by the Feather River project and other aspects of the California Water Plan. This study is designed to consider in detail the supply, demand, and impact relationships. The specific geographic areas studied are the Feather River drainage in northern California, the Chino-Riverside Basin and Imperial Valley areas in southern California, and selected portions of the west side of San Joaquin Valley in central California. An analysis is also given on how an effective benefit-cost study of remote sensing in relation to California's water resources might best be made.
The author has identified the following significant results. The supply, demand, and impact relationships of California's water resources as exemplified by the Feather River project and other aspects of the California Water Plan are discussed.
An econometric model was developed that can be used to predict demand and supply figures for crystals over a time horizon roughly concurrent with that of NASA's Space Shuttle Program - that is, 1975 through 1990. The model includes an equation to predict the impact on investment in the crystal-growing industry. Actually, two models are presented. The first is a theoretical model which follows rather strictly the standard theoretical economic concepts involved in supply and demand analysis, and a modified version of the model was developed which, though not quite as theoretically sound, was testable utilizing existing data sources.
The basic ideas and constructs for a general physical/physiological process level winter wheat simulation model are documented. It is a materials balance model which calculates daily increments of photosynthate production and respiratory losses in the crop canopy. The partitioning of the resulting dry matter to the active growing tissues in the plant each day, transpiration and the uptake of nitrogen from the soil profile are simulated. It incorporates the RHIZOS model which simulates, in two dimensions, the movement of water, roots, and soluble nutrients through the soil profile. It records the time of initiation of each of the plant organs. These phenological events are calculated from temperature functions with delays resulting from physiological stress. Stress is defined mathematically as an imbalance in the metabolite supply; demand ratio. Physiological stress is also the basis for the calculation of rates of tiller and floret abortion. Thus, tillering and head differentiation are modeled as the resulants of the two processes, morphogenesis and abortion, which may be occurring simulaneously.
The possibility that the greenhouse warming predicted by the GISS general-circulation model and other GCMs could lead to severe droughts is investigated by means of numerical simulations, with a focus on the role of potential evapotranspiration E(P). The relationships between precipitation (P), E(P), soil moisture, and vegetation changes in GCMs are discussed; the empirically derived Palmer drought-intensity index and a new supply-demand index (SDDI) based on changes in P - E(P) are described; and simulation results for the period 1960-2060 are presented in extensive tables, graphs, and computer-generated color maps. Simulations with both drought indices predict increasing drought frequency for the U.S., with effects already apparent in the 1990s and a 50-percent frequency of severe droughts by the 2050s. Analyses of arid periods during the Mesozoic and Cenozoic are shown to support the use of the SDDI in GCM drought prediction.
For over 20 years, the Cryogenics Test Laboratory at NASA Kennedy Space Center (KSC) (CSA CSM) has stood as a one-of-a kind capability for research, development, and application of cross-cutting technologies to meet both government and industry needs. With four overarching technology focus areas—Thermal insulation systems, Integrated refrigeration systems, Advanced propellant transfer systems, and Low-temperature materials and applications—and a theme of Energy Efficient Cryogenics, the Cryo Test Lab has pioneered technologies such as Integrated Refrigeration and Storage (IRAS) for advanced liquid hydrogen (LH2) operations; aerogel blanket insulation, the world’s best insulation material in ambient pressure and soft-vacuum; and the patented-pending Cryogenic Flux Capacitor3 for high-density storage, and on-demand supply of cryogenic fluids.
Integration of a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problem requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs) including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperformed other benchmark controllers regarding computation time without compromising operational performance.
Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.