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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

2023 FORCE Development Status Update

Technical and economic analysis of integrated energy systems (IES) using software models is a complex process requiring multiple commodity market decision analysis, optimal control, process modeling, and stochastic analysis. Many assumptions used in traditional energy analysis tools do not hold in future energy markets with significant storage and variable renewable energy sources (VRE), let alone with multiple commodity markets. Capturing these intricate elements for accurate techno-economic analysis of IES led to the development of the Framework for Optimization of ResourCes and Economics (FORCE) tool suite under the U.S. Department of Energy’s Integrated Energy Systems crosscutting technology program. With the aim of a full framework release in 2025, many improvements to the FORCE tool suite were developed in fiscal year 2023 (FY23). These improvements broadly fit into three focuses for development of FORCE: capability, accessibility, and reliability. Capability refers to the ability of FORCE to accurately model the technical and economic viability of various IES. Accessibility refers to ease-of-use for new and existing IES analysts to efficiently set up, analyze, and produce results using FORCE. Reliability refers to the consistency of the software, allowing consistency to analysis regardless of erstwhile changes to the software. In addition to many smaller changes, there are three major capability improvements in FORCE in FY23. In summary, FORCE developments in FY23 have moved us close to all the capability requirements for FORCE 1.0 to be delivered in FY25. Inclusion of Bayesian optimization, resilience metrics, and levelized cost analysis expand the capability, accessibility, and reliability of FORCE.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Parallelized POD-based suboptimal economic model predictive control of a state-constrained Boussinesq approximation

Motivated by an energy efficient building application, we want to optimize a quadratic cost functional subject to the Boussinesq approximation of the Navier-Stokes equations and to bilateral state and control constraints. Since the computation of such an optimal solution is numerically costly, we design an efficient strategy to compute a sub-optimal (but applicationally acceptable) solution with significantly reduced computational effort. We employ an economic Model Predictive Control (MPC) strategy to obtain a feedback control. The MPC sub-problems are based on a linear-quadratic optimal control problem subjected to mixed control and state constraints and a convection-diffusion equation, reduced with proper orthogonal decomposition. Finally, to solve each sub-problem, we apply a primal-dual active set strategy. The method can be fully parallelized, which enables the solution of large problems with real-world parameters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Incorporating Operational Uncertainties into the Dispatch of an Integrated Solar and Storage System

The economic assessment of hybrid energy systems (HES) pairing battery energy storage systems (BESSs) and photovoltaics (PV) is highly important for advancing their deployment in power systems. This paper presents an innovative assessment framework, including an optimal control policy for dispatch under uncertainty and procedures for exploring control parameters that maximize economic benefits. The proposed dispatch policy consists of two steps using system forecast information. The first step is to determine whether a BESS will be used within an operational scheduling time frame based on the probability of events and their thresholds. Once the dispatch of BESS is triggered, a model predictive control (MPC) is carried out in the second step for scheduling using the expected value of system information. By exercising this policy with different thresholds, one can explore the trade-offs between short-term benefits and battery lifetime, and identify an optimal threshold that maximizes the total economic benefits within the battery lifetime. An evaluation study in a real-world HES project is presented to illustrate the proposed framework. Compared with traditional optimal dispatch algorithms, the proposed method can significantly improve the economic benefits of an HES scheduled under forecast uncertainties.

Ma, Xu↗
DOE OSTI2021

REopt Lite User Manual

REopt Lite evaluates the economic viability of grid-connected solar photovoltaics, wind, combined heat and power, and electric and thermal storage at commercial and small industrial sites. It allows building owners to identify the system sizes and dispatch strategies that minimize the site’s life cycle cost of energy. REopt Lite also estimates the amount of time on-site generation and storage can sustain the site's critical load during a grid outage and allows the user the choice of optimizing for energy resilience. It is primarily used to inform project development decisions and to support research on the factors that drive project feasibility for market development and policy analysis. It is available through a web interface, application programing interface, and open-source code. This user manual provides an overview of the model, including its capabilities and typical applications; inputs and outputs; economic calculations; technology descriptions; and model parameters, variables, and equations. The model is highly flexible and is continually evolving to meet the needs of each analysis. Therefore, this report is not an exhaustive description of all capabilities, but rather a summary of the core components of the model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

White Paper: Research & Development for the Time at Temperature Approach

Recent advancements in nuclear power research are greatly improving reactor safety and performance through the development of Accident Tolerant Fuel (ATF) and Low-Enriched Uranium Plus (LEU+). These innovations can address Departure from Nucleate Boiling (DNB) margins, which are vital for reactor safety. DNB happens when the coolant switches to film boiling, significantly decreasing heat transfer and posing a risk of fuel cladding failure. The U.S. Nuclear Regulatory Commission (NRC) employs conservative DNB criteria, which can potentially restrict the operational flexibility and efficiency of reactors. The Time at Temperature (TaT) approach could provide a more detailed and adaptable operational guideline by establishing acceptable time-temperature limits, accounting for the duration a material can withstand elevated temperatures without losing its integrity. This method allows reactors to operate more efficiently and safely, offering additional operational margins, faster power adjustments, and improved fuel cycle economics. TaT criteria allow for higher power levels and more flexible responses to operational transients, particularly applicable for anticipated operational occurrences (AOOs) that result in short durations of post-DNB conditions. It enhances plant operational flexibility, allows faster startup times, and enables quicker power level adjustments, optimizing fuel loading patterns and improving fuel cycle economics. Implementing TaT limits reduces core design constraints, lowers fuel usage, and reduces costs, essential for the long-term sustainability of Light Water Reactors (LWRs). TaT maximizes the use of advanced fuel technologies like ATF and LEU+, further enhancing their economic and environmental benefits. To apply the TaT approach in existing LWRs, collaborative research activities among various DOE-sponsored programs are essential. These efforts should incorporate fuel experiments, physics-based high-fidelity modeling, ML-based surrogate modeling, and optimization techniques. This whitepaper proposes four research and development areas: 1) Investigation of the feasibility of new operations of LWR with updated safety limits; 2) Assessment of reactor operation limits through uncertainty reduction; 3) Evaluation of power uprate in virtual environment; and 4) Lattice and reactor core design for power uprate. Each area includes why this research is in need and a suggested scope of work. These comprehensive research areas ensure practical and beneficial advancements for existing reactors, translating innovations in nuclear fuel and cladding technology into improved reactor performance and safety.

42 - ENGINEERING↗
DOE OSTI2023

Distributed Rules-Based Deconfliction of ADMS Applications - Part 2: Conceptual Implementation

This work introduces a rules-based deconfliction methodology for resolving conflicting device control commands issued by advanced power applications considering a range of technical, economic, environmental, and social objectives. The methodology is designed to serve as one of multiple alternative implementations (along with application cooperation and global optimization) for the numerical component of the Deconfliction Pipeline. Development of the methodology is divided into two parts. The first document previously defined the requirements, context, and methods for decomposing the deconfliction problem using the Laminar Coordination Framework and Variable Grid Structures. The deconfliction problem was decomposed into a distributed optimization problem based on the concept of quasi-static grid segments, which form independent distributed areas for control and coordination. It was recommended that selection of the optimal number of decompositions of the deconfliction problem be made based on a tradeoff analysis between computational speed and global optimality. This second document defines an initial set of technical, economic, and environmental criteria, as well as thirty specific qualitative rules that are used as part of the deconfliction methodology to eliminate non-viable setpoint alternatives. The deconfliction optimization problem is converted into a ranking of individual discrete setpoints, which are scored by the extent to which they satisfy specific decision criteria. The ranking is determined through the concepts of deconfliction exclusivity, priority, and preference. Several multi-criteria decision-making frameworks are examined with the simple multi-attribute rating technique exploiting ranks (SMARTER) recommended as a simple implementation alternative that aligns with the steps of the rules-based deconfliction methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Blueprinting Electrified Transit System Implementation

To achieve a more affordable and reliable transportation system, we need to smartly upgrade our power systems and install a large number of charging stations, but conventional planning methods are not up to the task. By applying advanced simulation and optimization tools, we can design a smarter, more cost-effective electric transportation network. The initial focus was on public transit systems, demonstrating how this approach can deliver broader economic, reliability, and air quality benefits nationwide.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Cost optimization of low-salt-rejection reverse osmosis

Low-salt-rejection reverse osmosis (LSRRO) is an emerging membrane-based desalination technology for concentrating brines with potentially lower energy consumption and cost than thermally driven processes. We assess the technoeconomic performance of LSRRO by using an optimization model that minimizes the levelized cost of water (LCOW). We develop detailed models for the RO module and other equipment using WaterTAP (Water treatment Technoeconomic Assessment Platform), an open-source simulation and optimization software for water treatment. We improve upon previous LSRRO cost optimization studies by optimizing the salt permeability for each stage, which has significant implications for technoeconomic performance. We present the cost-optimal design, operation, and performance for three cases: 35 g/L TDS feed at 70% recovery, 70 g/L at 55%, and 125 g/L at 35%. The cost-optimal LCOW and specific energy consumption (SEC) for these cases are 0.70, 1.89, and 7.41 $/m 3 and 3.9, 8.4, and 30.4 kWh/m 3 , respectively. For each case, we use sensitivity analyses to provide guidance on key factors that impact economic viability. We also present the cost-optimal LCOW and SEC for feed concentrations between 5 and 220 g/L TDS and recoveries between 30 and 90%. So, we compare LSRRO to other high-salinity desalination technologies and find that it may be cost-competitive below feed concentrations of 125 g/L.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High-Temperature Aquifer Thermal Energy Storage (HT-ATES) Projects in Germany and the Netherlands—Review and Lessons Learned

Aquifer thermal energy storage (ATES) is a concept that can help to address heating and cooling needs through the use of the subsurface as a seasonal thermal energy storage (STES) system. Over 2800 ATES systems have been deployed with storage temperatures typically below 25 °C and only a few with higher temperatures (>40 °C), which would increase the energy density and utility of the stored thermal fluids. Until now, only a few high-temperature aquifer thermal energy storage (HT-ATES) projects have been initiated and are still in operation. These HT-ATES projects have encountered a range of technical and non-technical challenges. This study reviews ten such projects: four in Germany and six in the Netherlands. The non-technical issues include public acceptance, a lack of regulatory framework for these systems, managing overlapping uses of the subsurface, managing changes with the providers and off-takers of thermal energy, and obtaining financing to implement these projects. Common technical issues include geological factors such as incomplete characterization of the subsurface and reservoir heterogeneity; geochemical issues such as mineral scaling, corrosion, and biofouling; lower than expected thermal recovery; and issues with system design and reliability. This review highlights benefits and challenges faced by HT-ATES projects with the goal to use the lessons learned to improve the siting, design, development, and operation of such systems. Recommendations include improved initial subsurface site characterization, use of coupled process models to optimize system design and predict system performance, cascaded uses of stored thermal energy to better utilize the stored heat, monitoring networks to provide feedback on system performance, and expanded system scale to allow for continued operation even when maintenance of some system components is required. Techno-economic modeling and risk analysis could be used to optimize such HT-ATES project design and identify key factors that will affect sustained economic viability. In addition, design flexibility is important for these systems to allow for changing conditions regarding the supply and demand of thermal energy. Adopting these findings should improve the performance and reduce the risks for future HT-ATES projects worldwide.

15 - GEOTHERMAL ENERGY↗
DOE OSTI2025

Hybrid renewable energy systems

In the pursuit of ecologically sustainable and resilient energy systems, increasingly more attention is being devoted to a diversity of energy generation and storage methods. As the landscape of generation technology gains nuance and complexity, a wide-ranging set of technical questions has emerged, touching on topics that range from control and optimization of hybrid systems to finance and economic viability to multi-fidelity modeling and scientific machine learning. In the context of this special issue, hybrid renewable energy systems are any systems that consider the combined dynamics of more than one form of generation, storage, or grid subsystem. Research endeavors have delved into improving the flexibility of energy systems by utilizing existing resources, introducing novel operational strategies, deploying enhanced renewable forecasts, and exploring emerging technologies. In conclusion, the interconnection among various sectors has garnered heightened attention, not only due to the provision of additional tradable energy products but also for furnishing flexible headroom to system operators.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Resilience and economics of microgrids with PV, battery storage, and networked diesel generators

Current designs and assessments of microgrids have ignored component reliability, leading to significant errors in predicting a microgrid’s performance while islanded. Existing life cycle cost studies on hybrid microgrids—which combine photovoltaics (PV), battery storage and networked emergency diesel generators—also have not identified all the potential economic opportunities. Reducing the number of emergency diesel generators through reliance on PV and battery, retail bill savings, and demand response and wholesale market revenue streams are all important. This paper provides a new statistical methodology that calculates the impact of distributed energy reliability and variability on a microgrid’s performance and a novel use of the optimization platform REopt to explore multiple cost savings and revenue streams. We examine the impacts for microgrids in California, Maryland, and New Mexico and show that a hybrid microgrid is a more resilient and cost-effective solution than a diesel-only system. Under realistic conditions, a hybrid microgrid can provide higher system reliability when islanded and have a lower life cycle cost under multiple market conditions than a traditional diesel generator-based system. The improved performance of the hybrid system is resilient to conditions experienced over the last 20 years in solar irradiance and sees little degradation in performance immediately after a hurricane. The cost savings to provide this more resilient backup power system as compared to a diesel-only microgrid are significant. The net present cost for a hybrid microgrid is 19% lower in New Mexico and 35% lower in Maryland than a diesel-only microgrid. In California, the net present cost of the hybrid microgrid is negative because, unlike a diesel-only microgrid, a hybrid microgrid has lower life cycle costs than the power costs without a microgrid.

25 ENERGY STORAGE↗
DOE OSTI2025

Impact of organic acids on extraction of rare earth elements: Mechanisms and optimization

Organic acids are increasingly recognized as an environmentally friendly and efficient selective leaching agent of critical minerals. However, their impact on subsequent extraction processes remains unclear. This study investigates the extraction behavior of rare earth elements (REEs), representative of critical minerals, in the presence of various organic acids, including citric acid, maleic acid, malonic acid, DL-malic acid, L(+)-tartaric acid, and L-ascorbic acid. The results show that organic acids slightly reduce the extraction of REEs but greatly increase the extraction of aluminum (Al³⁺), making it harder to separate REEs from other elements. To avoid this, it is best to keep organic acid concentrations as low as possible in practical applications. However, by optimizing extraction conditions, these negative effects can be minimized. Specifically, adjusting the contact time between solutions allows for efficient REE extraction while limiting unwanted aluminum extraction. Among the acids tested, malonic acid and L(+)-tartaric acid were found to be the most effective for selectively extracting REEs. Mechanistically, organic acids are likely to form complexes with REEs and D2EHPA during extraction, except for Y (III), offering practical guidelines for optimizing REE recovery. Beyond extraction, this study also highlights a way to recover organic acids by precipitating REEs from stripping solutions using oxalic acid, which adds both environmental and economic benefits. Furthermore, these findings provide useful insights for optimizing REE recovery and offer a reference for extracting other critical minerals from solutions containing organic acids.

D2EHPA↗
DOE OSTI2021

Survey on stochastic distribution systems: A full probability density function control theory with potential applications

Complex systems seen either in general engineering practice or economics are subjected to ever increased uncertainties that are mostly represented as random variables or parameters, and the characteristics of random variables are represented by their probability density functions (PDFs). Controlling their PDFs means to shape their stochastic distributions and in general it would provide a full treatment for system analysis and operational control and optimization. This leads to the development of stochastic distribution control (SDC) systems theory in the past decades, where the original aim of the controller design is to realize a shape control of the distributions of certain random variables in their PDFs sense for some engineering processes. Indeed, once the PDFs of these random variables or parameters are used to describe their distribution characters, the control task is to obtain control signals so that the output PDFs of stochastic systems are made to follow their target PDFs. The subject of SDC was initially originated for non-Gaussian stochastic control systems design but has found a wide spectrum of applications in general systems in terms of data-driven modeling, analysis, signal processing (filtering), data mining via multivariable statistics, decision-making (optimization) for systems subjected to uncertainties and even in economics. In this context, SDC constitutes an effective primer tool for complex system analysis, control and operational optimizations. In this review paper, a detailed survey of the developments on the research of SDC systems will be made together with their wide spectrum applications and future perspectives.

42 ENGINEERING↗
DOE OSTI2020

A Tchebycheff-based multi-objective combined with a PSO–SQP dynamic real-time optimization framework for cycling energy systems

The aim in this work is to develop an optimization framework to address cycling of baseload energy systems due to the penetration of renewables into the grid. The developed strategy corresponds to a multi-objective and dynamic real-time optimization (MOO-DRTO) framework applied to a postcombustion MEA-based CO 2 capture process from a baseload coal-fired power plant under cycling conditions. A Tchebycheff-based method is used for the multi-objective optimization (MOO) component. Also, a hybrid approach consisting of Particle Swarm Optimization (PSO) and Sequential Quadratic Programming (SQP) is implemented for the first time in process systems engineering to solve the dynamic real-time optimization (DRTO) component. The objectives considered in the MOO-DRTO framework are economic and environmental. The proposed MOO-DRTO strategy is successfully implemented and 24-h optimal output trajectories for the carbon capture system under cycling are generated. Also, the optimal compromise is chosen from the Pareto front according to a set of selected weights for the objectives with minimal interaction between the framework and decision maker. The results indicated that the developed framework has potential to be extended to plant-wide optimization applications under cycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Justice 40 Tool (J40 Tool) v1.0

The Justice 40 tool provides a quantitative framework to support decision-making around equitable energy interventions at the community level. The tool calculates the optimal portfolio of policy interventions that explicitly mitigates energy insecurity of an eligible population, by reducing its disproportionate energy burden. The place-based analysis assumes a spatial census tract-level resolution and distinguishes different sociodemographic groups within each tract. Instead of focusing on a specific technology, the underlying J40 model captures the combined effect of a set of policy interventions, currently including weatherization, rooftop solar, community solar and community wind. For each tract, the model chooses the optimal (least cost) combination of interventions to address the disproportionate burden, considering the specific population demographics and techno-economic potentials of technologies. Mathematically, this problem is formalized as an optimization model and formulated as a linear program.

Heleno, Miguel↗
DOE OSTI2022

Repurposing Fossil-Fueled Assets For Energy Storage

The annual retirement of U.S. coal-fired electricity generation units (CF-EGU) is at an all-time high and is expected to continue. This loss of reliable baseload generation, combined with predicted growth of variable renewable energy (VRE) generation, is expected to stress grid reliability as the number of load-following resources drops below the experienced load variability. Many regions are already experiencing challenges, and fossil retirement-related warnings by the North American Electric Reliability Corp. are becoming more dire. All CF-EGU retirements pose significant challenges to asset owners, local workforces, and their communities. Repurposing a retiring CF-EGU as a long-duration energy storage plant can address these challenges and offer a suite of additional benefits to asset owners, the grid, and society. This project performed a techno-economic evaluation and assessment of repurposing a Duke Energy fossil-fueled asset (in particular, a coal plant) into an energy storage system by integrating the retiring asset with a Malta long duration Pumped Heat Energy Storage (PHES) system. The project validated the technoeconomic benefits of repurposing retiring coal plants into long-duration energy storage using Malta’s PHES. Key findings for this project are summarized below: (1) Technical: (a) Retiring coal plants (and other steam turbine fossil generation) can be repurposed to enable the clean energy transition using Malta’s technology. (b) For older retiring coal plants, repurposing the site and electrical interconnection for a standalone PHES plant is the most economically favorable option. (c) For newer coal plants where there is also a local peaking capacity need, repowering the steam cycle into a hybrid integration with PHES is attractive. (d) A process was developed to assist fossil generation owners in choosing the best path for each plant’s circumstances. (2) Economic (a) Communities facing economic challenges caused by the retirement of fossil generation would benefit from repurposing the plant as long-duration energy storage using Malta’s PHES. (b) On a $/MW basis, repowering retiring coal units into Malta PHES plants can maintain the same number and types of jobs and economic activity. (c) For a 70% carbon reduction scenario, a 10-hour Malta PHES plant is more economic for the asset owner than similar-power 4-hour batteries. This project showed that repurposing a retiring coal unit into thermal energy storage, by integrating it with a Malta PHES system, makes techno-economic sense. At least two integration options are available, with the optimal solution depending on the coal plant and its location. Repurposing retiring coal plant into energy storage results in economic benefits for the plant owner and local communities.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Distributed Rules-Based Deconfliction of ADMS Applications: Part 1: Requirements & Decomposition

This work introduces a rules-based deconfliction methodology for resolving conflicting device control commands issued by advanced power applications considering a range of technical, economic, environmental, and social objectives. The methodology is designed to serve as one of multiple alternative implementations (along with application cooperation and global optimization) for the numerical component of the Deconfliction Pipeline. Development of the methodology is divided into two parts. This first document introduces the requirements, context, and methods for decomposing the deconfliction problem using the Laminar Coordination Framework and Variable Grid Structures. The deconfliction problem is decomposed into a distributed optimization problem based on the concept of quasi-static grid segments, which form independent distributed areas for control and coordination. Selection of the optimal number of decompositions of the deconfliction problem should be made based on a tradeoff analysis between computational speed and global optimality. This second document will define an initial set of technical, economic, and environmental criteria, as well as thirty specific qualitative rules that are used as part of the deconfliction methodology to eliminate non-viable setpoint alternatives. The deconfliction optimization problem is converted into a ranking of individual discrete setpoints, which are scored by the extent to which they satisfy specific decision criteria. The ranking is determined through the concepts of deconfliction exclusivity, priority, and preference. Several multi-criteria decision-making frameworks are examined with the simple multi-attribute rating technique exploiting ranks (SMARTER) recommended as a simple implementation alternative that aligns with the steps of the rules-based deconfliction methodology.

97 MATHEMATICS AND COMPUTING↗