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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 73 records · Page 4

Energy Management Information System Powers NREL's Intelligent Campus

NREL's Intelligent Campus program leverages its own laboratory buildings as research instruments to study renewable energy, energy efficiency, and energy storage, integration, and analysis with real, quantitative measurements. At the heart of NREL's Intelligent Campus program is its Energy Management Information System (EMIS), a family of tools and services used to manage building and campus energy use. NREL's EMIS includes capabilities, such as benchmarking and monthly utility tracking, interval meter analytics, equipment fault detection and diagnostics, condition-based monitoring, and supervisory control, enabling unprecedented energy management capabilities. The system serves as a demonstration project for other federal facilities interested in learning about its design, features, and benefits.

EMIS↗

Innovations in Renewable Energy Technologies, Systems, and Energy Analysis

Costs for renewable energy technologies have declined rapidly in the past decade and their use for residential, commercial, and utility scale electricity has therefore grown exponentially. As the energy mix diversifies, energy analysis becomes increasing important, requiring renewable energy to integrate with other reduced emission energy sources, such as small modular nuclear reactors and carbon capture and utilization. Energy analysis can also explore the expansion of clean energy into new sectors, such as industrial processes and electrification. The U.S. National Renewable Energy Laboratory (NREL) and the Joint Institute for Strategic Energy Analysis (JISEA), which is a partnership of NREL and universities, study the integration and application of clean energy technologies into existing and new sectors. This presentation includes an overview of NREL and JISEA and summarizes innovations in renewable energy technologies and energy systems analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Integrated Energy Systems White Paper

This analysis compares how the existing critical infrastructure continues to be vulnerable and with smart grid technologies being implemented exposes IES, power systems, the grid, and renewable energy in new ways. Continued work in cybersecurity will thwart efforts against adversaries having an opportunity to penetrate these systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗

FORCE Regression Testing

Via programs including the Light Water Reactor Sustainability and Integrated Energy Systems, the U.S. Department of Energy has invested in the Framework for Optimization of ResourCes and Economics (FORCE) software framework (Idaho National Laboratory 2024a) for the technical and economic analysis of nuclear-integrated energy systems (IES). Nuclear IES expand the use of nuclear from traditional baseload electricity generation to a flexible and adaptive source of combined heat and power. Nuclear heat can be used in the production of a variety of energy currencies such as hydrogen and ammonia as well as other heat applications including water desalination and district heating. FORCE is designed with the intent to provide interconnected analysis tools that enable the accurate technical and economic assessment of specific nuclear IES configurations for individual energy markets. FORCE consists of three main analysis pathways: HYBRID (Idaho National Laboratory 2024b), which contains high-resolution physical models for IES; Holistic Energy Resource Optimization Network (HERON) (Idaho National Laboratory 2024c), which analyzes IES long-term economic viability; and Optimization of Real-time Capacity Allocation (ORCA) (Idaho National Laboratory 2024d), designed for real-time control of IES via digital twins and optimal decision making, including autonomous and remote operation research. Development of the FORCE ecosystem is guided by three pillars: capability, which assures that the computational requirements of IES analysis are met by the software tools; reliability, which provides for consistent code performance and expected behaviors; and accessibility, which lowers the barrier to entry for using the software and accelerates analysis by users beyond the FORCE primary developers. Reliability of the FORCE ecosystem is established according to the American Nuclear Society?s Nuclear Quality Assurance (NQA-1) program [American Society of Mechanical Engineers 1982], with specific levels of software quality assurance (SQA) within NQA-1 applied to each software tool in FORCE. As the tools within FORCE have matured, some integration algorithms to accurately connect the software tools for holistic analysis have been developed and deployed within the FORCE software repository. In accordance with NQA-1 standards, regression tests are required to guarantee the software performs consistently even when new capabilities are added to the software. In this report, we document the deployment of both unit tests, which test the consistent behavior of small pieces of the FORCE code base, as well as integration tests, which test the consistent performance of full use cases for the FORCE integration algorithms. We further document the encapsulation of these tests within a test harness, which collectively checks for each successful test completion on demand. Finally, we document the automation of the test harness using GitHub Actions [GitHub 2024], which require all tests succeed before any new capability or other changes can be added to the FORCE integration software

97 MATHEMATICS AND COMPUTING↗

Analysis of a fuel cell on-site integrated energy system for a residential complex

The energy use and costs of the on-site integrated energy system (OS/IES) which provides electric power from an on-site power plant and recovers heat that would normally be rejected to the environment is compared to a conventional system purchasing electricity from a utility and a phosphoric acid fuel cell powered system. The analysis showed that for a 500-unit apartment complex a fuel OS/IES would be about 10% more energy conservative in terms of total coal consumption than a diesel OS/IES system or a conventional system. The fuel cell OS/IES capital costs could be 30 to 55% greater than the diesel OS/IES capital costs for the same life cycle costs. The life cycle cost of a fuel cell OS/IES would be lower than that for a conventional system as long as the cost of electricity is greater than $0.05 to $0.065/kWh. An analysis of several parametric combinations of fuel cell power plant and state-of-art energy recovery systems and annual fuel requirement calculations for four locations were made. It was shown that OS/IES component choices are a major factor in fuel consumption, with the least efficient system using 25% more fuel than the most efficient. Central air conditioning and heat pumps result in minimum fuel consumption while individual air conditioning units increase it, and in general the fuel cell of highest electrical efficiency has the lowest fuel consumption.

Simons, S. N.↗

Prediction of Transition-State Scaling Relationships and Universal Transition-State Vibrational and Entropic Correlations for Dehydrogenations

Linear scaling relationships (LSRs) and Brønsted–Evans–Polanyi (BEP) or transition-state scaling (TSS) relations aid with the prediction of electronic energies. However, temperature effects and pre-exponentials are often taken as constants across metal surfaces or a homologous series. Vibrational scaling relationships (VSRs) offer a way to determine such parameters. Transition-state VSRs (TSVSRs) between local minima and transition states of AH X (A = C, N, O) surface diffusions correlate with BEP relations and broaden to thermochemical property scaling. Using density functional theory, we extend TSVSRs to AHX dehydrogenation reactions on transition-metal surfaces, relating vibrational modes of local minima to transition states. We first predict the slopes of the TSS relations by incorporating bond angles using the Slater–Koster structure factors and hybridization through crystal orbital overlap population analysis and energy overlap integrals between adsorbates and metal surfaces. Additionally, we uncover universal thermochemical property scaling, enabling the estimation of entropies and temperature corrections to enthalpies across a homologous series. Here, we demonstrate both significant vibrational corrections in reactions with low intrinsic electronic barriers and considerable variation in the pre-exponential of a simple dehydrogenation reaction across metals and AH X adsorbates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Healthy Buildings Initiative: Pacific Northwest National Laboratory Pilot Study

Fact sheet describes Pacific Northwest National Laboratory’s pilot of its framework for evaluating indoor environmental quality metrics and quantifying the potential financial costs and gains related to improving occupant productivity in federal buildings. The framework was piloted at PNNL’s Richland, Washington, campus to investigate how integrated energy and health analysis could benefit building retrofit and operation strategies.

FEMP↗

Integration of Energy Storage in Fossil Energy Power Plants (ES-FE) Market Analysis

This analysis consists of identifying the economic signals for the integration of ES-FE concepts in major Independent System Operators (ISOs), such as Mid-Continent (MISO), Electric Reliability Council of Texas (ERCOT), California (CAISO), and Pennsylvania, Jersey, Maryland Power Pool (PJM). This piece of work came from our interest in understanding how and at what level an electricity market would renumerate a fossil energy power plant that integrates energy storage, meaning a fossil power plant that adds any type of energy storage to their power plant.

Pena-Cabra, Ivonne A.↗

Optimizing Grid Regulation with Gravity Energy Storage Systems: A Comparative Analysis with Different Motor Inertias

The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid imbalances in generation and demand is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS scenarios provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 s from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS based on a highinertia motor may be able to operate over a broader range of frequency variations, whereas a low-inertia system may be limited by thermal constraints of the motor.

ENERGY STORAGE,POWER TRANSMISSION AND DISTRIBUTION↗

Electrification of residential and commercial buildings integrated with hybrid renewable energy systems: A techno-economic analysis

Here, this study assesses the techno-economic viability of city-scale building electrification, comparing a base case scenario with conventional HVAC systems to an electrified scenario with heat pump systems. EnergyPlus simulations reveal a 28% increase in annual electricity consumption in the electrified scenario, shifting the peak consumption from summer to winter with a 49% surge. Hybrid renewable energy systems (HRESs) are then evaluated using HOMER Pro, considering renewable penetration from 0% to 100%. The net present cost (NPC) of the base case and electrified scenarios range from $\$10.34$ to $\$24.38$ billion and $\$8.79$ to $\$50.31$ billion, respectively. Sensitivity analysis explores the impact of carbon tax, fuel price, and renewable subsidies on HRESs in the electrified scenario. Results indicate that applying a carbon tax up to $\$120$/tonne of CO 2 increases the optimum renewable fraction from 5% to 26%, while higher fuel prices and renewable subsidies further enhance the feasibility by shifting the optimum renewable fraction to 60% and 54%, respectively, demonstrating the interplay between economic factors and renewable integration in electrified urban contexts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An analysis of physics limited dispatch of nuclear renewable integrated energy systems using deep reinforcement learning and dynamic modeling

Previous approaches to dispatching nuclear integrated energy systems (NIES) have focused on the profitability and flexibility of these systems to operate on energy grids with highly variable pricing. However, due to the complexity involved in modeling and designing these systems, there has been less emphasis on ensuring that these dispatch strategies are physically achievable. It is imperative to develop methods that allow the system to remain within the desired NIES operating conditions and perform this based on realistic limited forecasted information. This research employs next generation artificial intelligence, namely deep reinforcement learning (DRL), and a dynamic system model written in Modelica to find a safe and profitable dispatch strategy for a solar nuclear hybrid design. The DRL agent is shown to find a novel dispatch strategy that manages both power ramping and power levels while respecting operational limits. This DRL-based dispatch is compared to other dispatching strategies including an optimal design solution from mixed integer linear programming (MILP). It is found that incorporating the physics of such a tightly coupled NIES limits the profitability of the MILP-based dispatch strategy. As a result, the MILP solution overestimates the design’s generated revenue. In contrast, DRL significantly reduces the number of breaches of safe operational conditions during energy arbitrage while maintaining profitability. Furthermore, this work paves the way for a more detailed assessment of NIES profitability and could be used to aid operator decisions on future NIES projects.

14 - SOLAR ENERGY↗

Analysis of pumped thermal energy storage using particle media integrated with concentrating solar power

Pumped Thermal Energy Storage (PTES) is an electricity storage system that converts electricity into thermal energy which is stored and later transformed back into electricity. Previous work has illustrated that particles have low capital costs and can be operated over a wide range of temperatures. PTES with particle storage achieves higher round-trip efficiency and specific power output than when molten salt thermal energy storage is used. This article explores hybrid systems that combine PTES with Concentrating Solar Power (CSP). Hybrid systems share the majority of components thereby reducing costs compared to two stand-alone devices. In addition, hybrid systems can provide multiple services (such as renewable power generation and electricity storage services). Using particle thermal storage in these hybrid concepts provides freedom in choosing the design conditions, since a wide range of operating temperatures is allowable, therefore making it possible to identify hybrid system designs that have good performance. In this article, two concepts for hybrid PTES-CSP are introduced. Thermodynamic models are developed and these are used to evaluate the performance of two hybrid systems. These models account for turbomachinery efficiency, and approach temperature and pressure loss in heat exchangers, as well as other sources of inefficiency, such as motor-generator losses, and air fan power. The “Solar Top-Up” Concept uses CSP to increase the temperature delivered by the charging heat pump. The discharging system uses a topping gas cycle and a bottoming steam cycle to fully exploit the available energy. Using solar heat to increase the maximum temperature from 750 K to 1100 K increases the round-trip efficiency from 41 % to 62 % and the specific work output from 88 kJ/kg to 301 kJ/kg. The second concept is a “Dual-Mode” device which provides both electricity storage and solar electricity generation with the same set of components. The PTES-mode and CSP-mode performance are optimized at different design values but careful parameter selection leads to good performance of both modes: one design produces PTES round-trip efficiency > 60 %, CSP heat engine efficiency > 40 %, and specific work outputs > 150 kJ/kg (for both cycles), when the particle receiver temperature is > 1200 K and maximum heat pump temperature is 1100 K.

14 SOLAR ENERGY↗

Design and Analysis of an Integral MPPT Control Law for Wave Energy Conversion Systems

In this paper, we propose an integral-based maximum power point tracking (MPPT) algorithm for point absorber wave energy conversion (WEC) systems. A permanent magnet synchronous generator (PMSG) is coupled to the point absorber and its drive implements the proposed MPPT control. While the rotating frame of reference of the PMSG implements power control, the slower mechanical frequency of the incident waves are processed with an additional transformation that yields another set of dc dynamics. The computed dc power in the new reference frame, which is focused on slow wave dynamics, is input to the MPPT control law that tunes the emulated resistance of the machine drive to extract peak power from the wave absorber device. We derive a stability condition for the proposed controller and validate our control design on a simulated 10kW system.

wave energy, maximum power point tracking (MPPT), ↗

Cybersecurity Assessment in DER-rich Distribution Operations: Criticality Levels and Impact Analysis

The integration of distributed energy resources (DERs) in distribution networks has become a pivotal strategy for achieving decarbonization, enhancing grid resilience, and optimizing grid efficiency. Remote monitoring and control op- erations of such resources rely on a network of sensors and communication infrastructure, exposing the system to potential cyber threats. Therefore, as the deployment of DERs increases, ensuring secure monitoring and control becomes an imperative challenge. This paper utilizes real-time feeder models, which are instrumental in developing cybersecurity testbeds tailored for hardware-in-loop (HIL) systems. These models enable users to simulate cyber attacks in a real-world environment and analyze the power distribution operations during vulnerabilities. Furthermore, we discuss several practical sets of grid parameters to identify critical levels of DERs and evaluate various scenarios that simulate cyber threats on sensitive DERs. The modified IEEE 123-bus model is used as the test case for demonstrating the proposed scenarios. The findings from this study provide valuable insights into the vulnerabilities and potential consequences of cyber attacks on DERs, allowing for better mitigation strategies and improved cyber resilience in future distribution networks.

Maharjan, Manisha↗

Analysis of a fuel cell on-site integrated energy system for a residential complex

Declining supplies of domestic oil and gas and the increased cost of energy resulted in a renewed emphasis in utilizing available resources in the most efficient manner possible. This, in turn, brought about a reassessment of a number of methods for converting fossil fuels to end uses at the highest practical efficiency. One of these is the on-site integrated energy system (OS/IES). This system provides electric power from an on-site power plant and recovers heat from the power plant that would normally be rejected to the environment. An OS/IES is potentially useful in any application that requires both electricity and heat. Several OS/IES are analyzed for a residential complex. The paper is divided into two sections; the first compares three energy supply systems, the second compares various designs for fuel cell OS/IES.

Simons, S. N.↗