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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Nuclear-Integrated Energy Units: Advancing Cybersecurity for Resilient Energy Systems

Rapidly increasing usage of nuclear-integrated energy units has created new challenges in terms of cybersecurity. This paper discusses the potential cyberthreat challenges and cyber risks associated with the widespread adoption of these units, and the role of artificial intelligence (AI) and machine learning (ML) techniques in enhancing the security and resilience of these systems.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Review and Modeling of Integrated Energy Systems with Nuclear Reactor Coupled Desalination and District Heating

Detailed reviews of a past advanced nuclear reactor based integrated energy system, as well as other nuclear reactor and fossil fuel based integrated energy systems have been performed for this work. Review of the utilization of heat from nuclear reactors for various applications and cogeneration has been done. The heat can be utilized by extraction of the steam from the turbine while the steam is still at a desired temperature. While use of nuclear process heat for district heating in countries like Finland, France, China, Poland, and elsewhere is discussed, more focus of the review has been given on nuclear desalination processes. Integrated energy systems (IES) where distinct types of reactors like PWR, BWR, sodium cooled fast reactor, heavy water reactor and other advanced reactors are coupled with various nuclear desalination processes like multi-effect distillation (MED), multi-stage flashing (MSF) and reverse osmosis (RO) methods have been discussed. The nuclear desalination plant at Aktau has been discussed in more detail due to its decades of successful operation. The IES of the Aktau plant coupled with 5-effect MED desalination plant has been taken as a reference for modeling the Open Modelica (OM) based IES of this work. Here, the OM IES model shows good agreement with the MED plant output of Aktau and can be extended for future applications of IES.

42 ENGINEERING↗
NASA NTRS1979

Integrated energy management study. Energy efficient transport program

The Integrated Energy Management (IEM) Study investigated the practicality and feasibility of a closed-loop energy management system for transport aircraft. The study involved: (1) instrumentation and collection of in-flight data for a United Airlines 727-200 flying 80 revenue flights throughout the United Airlines network,(2) analysis of the in-flight data to select representative city pairs and establish operational procedures employed in flying a reference flight profile, (3) simulation of the reference profile in a fast-time model to verify the model and establish performance values against which to measure IEM benefits, (4) development of IEM algorithms, and (5) assessment of the IEM concept.

Source record↗
DOE OSTI2022

IRES Microgrid Energy Integration Report Version 1.0

This report presents technical information and guidance for the planned Integrated Renewable Energy System (IRES) microgrid project. This deployment of the microgrid and its associated assets was initiated in the beginning of 2022 at the Marine and Coastal Research Laboratory (MCRL) facility of Pacific Northwest National Laboratory (PNNL)-Sequim, Washington. The information in the report is organized under two main focus areas: electrical power interface, or interconnection, information of planned IRES assets; and communication and control interface, or interoperability, information of the planned IRES assets. The information will provide technical input for the development of the IRES microgrid controller technical specification, and also provide input for PNNL’s evaluation of adequacy of the electrical service infrastructure at MCRL to support the IRES project and help identify any gaps that will require facility-based upgrades. From an R&D aspect, this study and report will build on PNNL’s research and development work relating to energy storage (ES) codes and standards (C&Ss), including hybrid systems, performed on behalf of the Department of Energy (DOE) Office of Electricity (OE) ES. The current state of C&Ss for advanced technologies and their application, including microgrid-based technology is limited. For cases where formal standards issued by recognized Standards Developing Organizations do not yet exist, guidance is provided based on emerging best practices, including industry-group references that can be leveraged for microgrid technology which is in its early stages of development and use.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Integrated Energy Systems: 2020 Roadmap

This roadmap defines potential industrial scale integrated energy systems (IES) and identifies key technology gaps to achieving commercial deployment of such systems. IES under consideration could include multiple energy generation resources and energy use paths, with a focus on low-emission technologies, such as nuclear and renewable generators. Together these technologies provide affordable, reliable, and resilient energy while simultaneously reducing environmental emission of CO 2 and greenhouse gases (GHGs). System design and optimization would consider both technical performance and economic viability within various deployment markets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Design, modeling and simulation of nuclear-powered integrated energy systems with cascaded heating applications

Nuclear-renewable integrated energy systems (IES) consist of a variety of energy generation and conversion technologies and can be used to meet heterogeneous end uses (e.g., electricity, heat, and cooling demands). In addition to supply-demand balance, end-use heat demands usually require heat supply of certain temperature ranges. The effective and efficient utilization of heat produced within an IES is, therefore, a critical challenge. Here, this paper examines design options of an IES that includes heating processes of multiple temperature grades. We investigate a cascaded design configuration, where the remaining residual heat after high-grade heating processes [e.g., hydrogen production through high-temperature steam electrolysis (HTSE)] is recovered to meet the low-grade heating needs [e.g., district heating (DH)]. Additionally, a thermal energy storage system is integrated into the DH system to address the imbalance between heat supply and demand. This paper primarily focuses on the design and modeling of the proposed system and evaluates its operation with a 24-h transient process simulation using a DH demand profile with hourly resolution. The results indicate that the residual heat from the HTSE exhaust is insufficient for the DH demand, and additional topping heat directly from the reactor process steam is needed. Furthermore, the inclusion of thermal energy storage within the DH system provides the necessary balance between thermal generation and demand, thereby ensuring a consistent rated temperature of the DH supply water. This approach helps minimize the control actions needed on the reactor side.

08 HYDROGEN↗
DOE OSTI2021

ARIES: Advanced Research on Integrated Energy Systems Research Plan

The Advanced Research on Integrated Energy Systems (ARIES) platform is one of the most powerful research environments anywhere for addressing the speed and scale of change on power systems. This research plan details ARIES capabilities, current and upcoming, and how they relate to objectives for advanced energy systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Energy-dependent and Energy-integrated Two-moment General-relativistic Neutrino Transport Simulations of a Hypermassive Neutron Star

Abstract We compare two-moment-based energy-dependent and three variants of energy-integrated neutrino transport general-relativistic magnetohydrodynamics simulations of a hypermassive neutron star. To study the impacts due to the choice of the neutrino transport schemes, we perform simulations with the same setups and input neutrino microphysics. We show that the main differences between energy-dependent and energy-integrated neutrino transport are found in the disk and ejecta properties, as well as in the neutrino signals. The properties of the disk surrounding the neutron star and the ejecta in energy-dependent transport are very different from the ones obtained using energy-integrated schemes. Specifically, in the energy-dependent case, the disk is more neutron-rich at early times and becomes geometrically thicker at later times. In addition, the ejecta is more massive and, on average, more neutron-rich in the energy-dependent simulations. Moreover, the average neutrino energies and luminosities are about 30% higher. Energy-dependent neutrino transport is necessary if one wants to better model the neutrino signals and matter outflows from neutron star merger remnants via numerical simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Clean Energy Integration in Natural Gas Compressor Station Operations

Integrating renewable energy into oil and gas operations could reduce emissions and maximize higher-value use of produced hydrocarbons. In this study, analysts from the Joint Institute for Strategic Energy Analysis (JISEA) and the National Renewable Energy Laboratory (NREL) evaluated clean power technologies for a natural gas compressor station in Texas, using NREL’s REopt tool. Different configurations of distributed energy resources were evaluated based on the technologies available and the load they can satisfy, available land, and hypothetical carbon pricing. The analysis is part of a collaborative program with industry to understand site-specific energy consumption and prices in the oil and gas supply chain and determine under what conditions clean energy options are economically attractive. This work was sponsored by a consortium including Kinder Morgan, Interstate Natural Gas Association of America Foundation, Extraction Oil & Gas, Baker Hughes, and ConocoPhillips.

03 NATURAL GAS↗
DOE OSTI2023

Summary of INL Integrated Energy Systems Research for the Global National Laboratories Consortium on IES

The DOE Office of Nuclear Energy (DOE-NE) program on Integrated Energy Systems (IES) is led by researchers at Idaho National Laboratory (INL), and work is conducted in partnership with an array of other DOE laboratories, industry, and academia. IES research and development activities are additionally complimented by the DOE-NE Light Water Reactor Sustainability (LWRS) program, where work under the Flexible Plant Operations & Generation pathway supports analysis of opportunities for non-electric applications of current fleet nuclear plants and collaborates with multiple plants on near-term hydrogen production demonstration opportunities. The DOE-NE programs additionally partner with the Hydrogen and Fuel Cell Technologies Office under the DOE Office of Energy Efficiency and Renewable Energy to jointly fund the development of analysis tools, technologies, and nuclear-integrated hydrogen demonstration projects. This document provides a brief, high-level summary of IES work as contribution to the annual report for the Global National Laboratories Consortium on IES.

08 HYDROGEN↗
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 OSTI2024

An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems

Deep Reinforcement Learning (DRL)-based control shows enhanced performance in the management of integrated energy systems when compared with Rule-Based Controllers (RBCs), but it still lacks scalability and generalisation due to the necessity of using tailored models for the training process. Transfer Learning (TL) is a potential solution to address this limitation. However, existing TL applications in building control have been mostly tested among buildings with similar features, not addressing the need to scale up advanced control in real-world scenarios with diverse energy systems. This paper assesses the performance of an online heterogeneous TL strategy, comparing it with RBC and offline and online DRL controllers in a simulation setup using EnergyPlus and Python. The study tests the transfer in both transductive and inductive settings of a DRL policy designed to manage a chiller coupled with a Thermal Energy Storage (TES). The control policy is pre-trained on a source building and transferred to various target buildings characterised by an integrated energy system including photovoltaic and battery energy storage systems, different building envelope features, occupancy schedule and boundary conditions (e.g., weather and price signal). The TL approach incorporates model slicing, imitation learning and fine-tuning to handle diverse state spaces and reward functions between source and target buildings. Results show that the proposed methodology leads to a reduction of 10% in electricity cost and between 10% and 40% in the mean value of the daily average temperature violation rate compared to RBC and online DRL controllers. Moreover, online TL maximises self-sufficiency and self-consumption by 9% and 11% with respect to RBC. Conversely, online TL achieves worse performance compared to offline DRL in either transductive or inductive settings. However, offline Deep Reinforcement Learning (DRL) agents should be trained at least for 15 episodes to reach the same level of performance as the online TL. Therefore, the proposed online TL methodology is effective, completely model-free and it can be directly implemented in real buildings with satisfying performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Digital Twin for Optimizing Real-time Economy of the Integrated Energy Systems

Economic and safe operation of integrated energy systems (IES) requires real-time optimization (RTO) of the control and actions conducted on each system component. In this regard, digital twins (DTs), which consist of a physical system, a virtual system, and the data communication that occurs between the two, are essential for effective RTO. Through the data warehouse, the virtual system is constantly updated with real-time data from the physical system, and functions as the model in the optimization framework. The reduced-order model of the dynamic process model in the virtual system is used in the optimization framework. The optimization results are then returned, via the data warehouse, as control actions to the physical system. This work demonstrates the software capabilities of DT assets for an IES in the context of preparing a DT for an experimental system comprised of Idaho National Laboratory (INL)’s Thermal Energy Delivery System and battery system. For the virtual demonstration, the DTs encompass (1) a physical system, including the Modelica models of the Thermal Energy Delivery System and the battery system; (2) virtual optimization via the Optimization of Real-Time Capacity Allocation (ORCA) platform; and (3) the open-source data warehouse software DeepLynx. This work assesses the performance of ORCA, which utilizes a reduced-order model built using the Risk Analysis Virtual Environment (RAVEN) and trained on the Modelica models and real-time data pipeline through the graph database hosted in DeepLynx. The proposed optimization workflow will be an RTO model based on DTs and the data they generate.

25 ENERGY STORAGE↗
DOE OSTI2023

Advanced Reactors Integrated Energy System: Thermal Energy Storage Island Design

The main topic of this research is integrated energy systems (IES) designed for pairing industrial thermal energy loads with advanced reactors (ARs). The Idaho National Laboratory (INL) Crosscutting Technology Development IES program and the National Reactor Innovation Center (NRIC) are seeking to develop, design, and construct an AR-IES demonstration platform that couples the thermal output from an AR operating at the INL/NRIC Demonstration of Microreactor Experiments (DOME) test bed in the Experimental Breeder II dome to a variable capacity load emulator (i.e., air-cooled radiator) and sensible thermal energy storage (TES) via a molten salt thermal energy transfer fluid. In the rapidly evolving landscape of energy supply and distribution, flexibility has emerged as a prized attribute, surpassing the traditional notions of stability and baseload generation capability. This shift in priorities is particularly evident in the context of nuclear power plants (NPPs), where adaptability over constant output is becoming more important. As our energy infrastructure and resources embraces the rise of distributed energy generation, the inherent variability in net demand continues to grow. Moreover, the use of nuclear energy as a source of heat for decarbonizing the industrial sector is becoming a very pressing topic. In such environment, advanced NPPs are poised to enter a more competitive energy market, delivering both, flexible electricity and heat. This shift motivates the exploration of TES systems, designed to empower NPPs with nimble responsiveness to market fluctuations, flexible heat delivery capabilities, and redefine their role in the energy field. TES systems offer the unique advantage of storing nuclear energy in its original form as heat, thereby affording unparalleled flexibility in its subsequent utilization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

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↗
DOE OSTI2024

Optimal operations of a nuclear-based integrated energy system: A mixed integer program approach

A nuclear-based integrated energy system (IES), consisting of multiple carbon-free energy generation and conversion technologies to meet heterogeneous end-use demands, offers a promising approach to decarbonizing the U.S. economy. Operating such an IES is challenging due to its complexity and the diverse end-use demands, such as heating and electricity. This paper aims to address the optimal operation of an IES composed of a small modular reactor (SMR), a steam manifold, a balance of plant (BOP), a high-temperature steam electrolysis (HTSE) system, a district heating (DH) network, and electrical grids. We formulate the system’s operation as a mixed integer linear programming (MILP) problem to maximize net revenues from sales of electricity and hydrogen. To evaluate the efficacy of the proposed model, we conduct a 24-hour simulation considering day-ahead (DA) electricity prices from CAISO and a varying DH demand profile with hourly resolution. The simulation results show that our model effectively optimizes the operation by selling electricity during on-peak periods and purchasing electricity for hydrogen production during off-peak periods, while satisfying operating constraints within the IES.

08 HYDROGEN↗
DOE OSTI2022

A High Temperature Gas Reactor Integrated Energy System Using Energy Storage as a Buffer for Hydrogen Production

Analysis of an integrated energy system producing hydrogen in a high temperature steam electrolysis system via steam provided by a sensible heat thermal energy storage system charged by a high temperature gas reactor. Preliminary results over a continuous discharge cycle and single charging cycle shows minimal reactor impact despite 25% electrical power load change. Hydrogen production is held constant with steam provided by the thermal energy storage system.

08 HYDROGEN↗