Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “energy optimization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Transient Optimization for the Betterment of Turbine Electrified Energy Management

Gas turbine engine transients are associated with degraded compressor operability, which must be addressed by the engine control system and accounted for in the engine design. Failure to do so may result in events such as compressor stall/surge and combustor blow out. Transient operability concerns constrain the engine design and can result in sacrifices of efficiency and/or thrust responsiveness. The traditional approach to transient operability management is control logic that limits the fuel flow command. A companion paper presents a strategy for optimizing the transient fuel flow control logic taking into consideration transient operability and thrust responsiveness. The study covered here extends this idea to an electrified gas turbine engine that employs a power/energy management concept known as Turbine Electrified Energy Management (TEEM). TEEM uses an electric power system interfaced with the engine (hence the term ‘electrified gas turbine engine’) to further improve transient operability and alleviate associated design constraints. There can be costs associated with implementing TEEM in terms of power and energy requirements that impact the size of the electrical power system. However, the results of this study show that through optimization of the transient limit logic, power and energy requirements needed to implement TEEM can be significantly reduced. Among the conclusions that can be drawn from the results of the illustrative application covered herein are: (1) there is a reduction in the electric machine power requirement to manage operability during accelerations by 200 to 400 hp, and (2) power transfer from the low pressure spool (LPS) to the high pressure spool (HPS) is the most effective option for improving operability during decelerations, followed by the options of only injecting power on the HPS or only extracting power from the LPS.

transient↗
NASA NTRSDate not supplied

Transient Optimization for the Betterment of Turbine Electrified Energy Management

Gas turbine engine transients are associated with degraded compressor operability, which must be addressed by the engine control system and accounted for in the engine design. Failure to do so may result in events such as compressor stall/surge and combustor blow out. Transient operability concerns constrain the engine design and can result in sacrifices of efficiency and/or thrust responsiveness. The traditional approach to transient operability management is control logic that limits the fuel flow command. A companion paper presents a strategy for optimizing the transient fuel flow control logic taking into consideration transient operability and thrust responsiveness. The study covered here extends this idea to an electrified gas turbine engine that employs a power/energy management concept known as Turbine Electrified Energy Management (TEEM). TEEM uses an electric power system interfaced with the engine (hence the term ‘electrified gas turbine engine’) to further improve transient operability and alleviate associated design constraints. There can be costs associated with implementing TEEM in terms of power and energy requirements that impact the size of the electrical power system. However, the results of this study show that through optimization of the transient limit logic, power and energy requirements needed to implement TEEM can be significantly reduced. Among the conclusions that can be drawn from the results of the illustrative application covered herein are: (1) there is a reduction in the electric machine power requirement to manage operability during accelerations by 200 to 400 hp, and (2) power transfer from the low pressure spool (LPS) to the high pressure spool (HPS) is the most effective option for improving operability during decelerations, followed by the options of only injecting power on the HPS or only extracting power from the LPS.

transient↗
DOE OSTI2026

Harnessing Ocean Thermal Gradients Using Thermoelectric Based Submersibles for Ocean Power Applications

The urgent need for energy solutions in marine environments has accelerated the development of innovative technologies capable of leveraging natural resources for power generation. This study introduces a buoyancy-driven submersible system designed to harness ocean thermal gradients using thermoelectric generators (TEGs) and phase change materials (PCMs). The technology aims to provide autonomous power to offshore aquaculture farms, unmanned underwater vehicles (UUVs), offshore platform illumination, and ocean sensors, significantly reducing dependence on fossil fuels. Ocean thermal gradients, especially prevalent in mid-latitude regions, exhibit temperature differences between surface and deep waters ranging from 7 degrees Celsius to 30 degrees Celsius depending on seasonal variations. The proposed submersible technology utilizes TEGs to convert thermal energy from these gradients into electrical power, generating between 0.2 and 0.5 watts, while PCMs are employed to store and regulate this energy, ensuring a stable and continuous power supply. The buoyancy-driven mechanism of the submersible enhances its capability to navigate through varying depths, optimizing its exposure to different thermal gradients and maximizing energy harvesting. The performance of this submersible system is analyzed through detailed thermodynamic assessments and computational fluid dynamics (CFD) modeling focused on heat transfer. These analyzes consider real-world ocean temperature profiles and seek to refine the interaction between TEGs and PCMs to optimize energy extraction. The evaluation encompasses several key performance metrics, including power output and energy efficiency. Results confirm the potential of this innovative technology to provide a continuous and reliable power source for marine applications. By demonstrating the feasibility of using ocean thermal gradients for energy generation, this study contributes to the broader efforts of innovation in energy technologies for harsh, remote marine environments. The implementation of such promises is significant advancements in the autonomy of marine operations. The ongoing research will further investigate scalability ensuring that the system can be effectively adapted to various marine settings and operational demands.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

The Uniform Methods Project: Smart Thermostat Evaluation Protocol

A smart thermostat is an internet-connected device that controls home heating, ventilation, and air-conditioning (HVAC) equipment and can automatically adjust temperature set points to optimize performance and achieve energy savings. Smart thermostat features often include two way communication, occupancy detection (such as geofencing and occupancy sensors), schedule learning, and seasonal optimization algorithms. Smart thermostats can control most conventional HVAC systems, including central air conditioners, heat pumps, and forced air furnaces. Several types of residential utility programs offer smart thermostats as replacements measures. Working with smart thermostat vendors, utilities can offer separate optimization programs to produce energy savings beyond those achieved by installing a smart thermostat. From an evaluation perspective, smart thermostat programs have several noteworthy features. First, the energy savings from a smart thermostat may change over the life of the device. As a smart thermostat is connected to the internet, original equipment manufacturers can update the thermostat software to improve the thermostat's energy efficiency. Likewise, users can adjust the thermostat settings and schedules over time in response to changes in weather, thermal comfort, energy prices, or preferences for energy efficiency. Additionally, many thermostat manufacturers offer seasonal optimization programs that recommend changes or make minor, automated adjustments to the thermostat settings to improve energy efficiency. These opt-in programs are now standard offerings for many smart thermostat manufacturers and provided at no additional cost to users. The potential for software updates and continuous optimization and the evolving nature of user interactions mean future energy savings may differ from first-year savings and the energy savings of smart thermostats may need to be evaluated more than once. Second, smart thermostats often have small unit energy savings relative to a home's total energy consumption, especially in comparison to whole- home retrofit programs. This can make it difficult to detect the smart thermostat savings in billing or advanced metering infrastructure (AMI) meter consumption data. For example, as cooling loads in many regions average about 20% of annual electricity consumption, smart thermostat savings of 10% of cooling energy use would equate to a 2% reduction in home electricity consumption. Evaluators should use regression analysis of whole-home billing consumption or advanced metering infrastructure (AMI) meter consumption data to evaluate smart thermostat savings because, as explained at greater length below , these data are usually available to evaluators and regression can control for the impacts of weather and other potentially confounding factors on a home's energy consumption. Finally, as with other energy efficiency programs, participation in smart thermostat programs is self-selective. As discussed at greater length below , smart thermostat participants tend to be, among other things, younger, higher-income, and more likely to adopt electric vehicles (EVs) and internet connected devices than nonparticipants. These differences are often unobservable to the evaluator and correlated with a home's energy consumption, creating the potential for bias in estimating savings. Due to the small unit savings of thermostats, errors and biases from self-selection that may not be very consequential when evaluating a whole- home retrofits (e.g., ±2% of home electricity consumption) can have a major impact when evaluating the savings and cost-effectiveness of smart thermostat programs. A percentage point change in the estimated savings could affect the cost-effectiveness of a program. This means it is important for evaluators to assess and to minimize the potential for error from selection bias in estimating smart thermostat program savings. The Uniform Methods Project provides model protocols for determining energy savings and demand reductions that result from specific energy efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol ; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The UMP protocols can be used by utilities, program administrators, public utility commissions, evaluators, and other stakeholders for both program planning and evaluation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Distributed Optimization in Distribution Systems: Use Cases, Limitations, and Research Needs

We report electric distribution grid operations typically rely on both centralized optimization and local non-optimal control techniques. As an alternative, distribution system operational practices can consider distributed optimization techniques that leverage communications among various neighboring agents to achieve optimal operation. With the rapidly increasing integration of distributed energy resources (DERs), distributed optimization algorithms are growing in importance due to their potential advantages in scalability, flexibility, privacy, and robustness relative to centralized optimization. Implementation of distributed optimization offers multiple challenges and also opportunities. This paper provides a comprehensive review of the recent advancements in distributed optimization for electric distribution systems and classifications using key attributes. Problem formulations and distributed optimization algorithms are provided for example use cases, including volt/var control, market clearing process, loss minimization, and conservation voltage reduction. Finally, this paper also presents future research needs for the applicability of distributed optimization algorithms in the distribution system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Operando Revealing Dynamic Reconstruction of NiCo Carbonate Hydroxide for High-Rate Energy Storage

Transition metal carbonate hydroxide (CH) has been widely explored as a promising battery-type electrode for high-rate energy storage. However, its genuine active sites under realistic operating conditions remains elusive. In this work, by virtue of the cutting-edge operando X-ray absorption spectroscopy, we unfold the dynamic evolution of the local electronic and geometric structures for the CH electrode upon cycling. Our results reveal that the irreversible redox of Co cations at the early stage of cyclic voltammetry (CV) cycling induces a phase transition in the NiCo CH nanowires forming oxygen vacancies-enriched NiCo layered double hydroxide (LDH) nanosheets with superior high-rate energy storage ability. Theoretical modeling demonstrates that the unsaturated 5-coordinated Co sites exhibit optimal redox reaction energy barrier and immensely promote the performance. These findings not only elucidate the electrochemical susceptibility of the Co-based carbonate hydroxide under operando conditions, but also highlight an electrochemical coordination-engineering strategy for the rational design of high-performance electrode.

25 ENERGY STORAGE↗
NASA NTRS1994

Homodyning and heterodyning the quantum phase

The double-homodyne and the heterodyne detection schemes for phase shifts between two synchronous modes of the electromagnetic field are analyzed in the framework of quantum estimation theory. The probability operator-valued measures (POM's) of the detectors are evaluated and compared with the ideal one in the limit of strong local reference oscillator. The present operational approach leads to a reasonable definition of phase measurement, whose sensitivity is actually related to the output r.m.s. noise of the photodetector. We emphasize that the simple-homodyne scheme does not correspond to a proper phase-shift measurements as it is just a zero-point detector. The sensitivity of all detection schemes are optimized at fixed energy with respect to the input state of radiation. It is shown that the optimal sensitivity can be actually achieved using suited squeezed states.

Dariano, Giacomo M.↗
DOE OSTI2023

Nuclear–Electronic Orbital QM/MM Approach: Geometry Optimizations and Molecular Dynamics

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods allow simulations of chemical reactions in atomistic solvent and heterogeneous environments such as proteins. Herein, the nuclear–electronic orbital (NEO) QM/MM approach is introduced to enable the quantization of specified nuclei, typically protons, in the QM region using a method such as NEO-density functional theory (NEO-DFT). This approach includes proton delocalization, polarization, anharmonicity, and zero-point energy in geometry optimizations and dynamics. Expressions for the energies and analytical gradients associated with the NEO-QM/MM method, as well as the previously developed polarizable continuum model (NEO-PCM), are provided. Geometry optimizations of small organic molecules hydrogen bonded to water in either dielectric continuum solvent or explicit atomistic solvent illustrate that aqueous solvation can strengthen hydrogen-bonding interactions for the systems studied, as indicated by shorter intermolecular distances at the hydrogen-bond interface. We then performed a real-time direct dynamics simulation of a phenol molecule in explicit water using the NEO-QM/MM method. Furthermore, these developments and initial examples provide the foundation for future studies of nuclear–electronic quantum dynamics in complex chemical and biological environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Improving Data Center Energy Efficiency Through End-to-End Cooling Modeling and Optimization. Final Report

This report summarizes the development and demonstration of the three features developed for the DOE project “Improving Data Center Energy Efficiency through End-to-End Cooling Modeling and Optimization” (Award No. DE-EE0007688). The development of the three software features, Feature 1: Optimization of Cooling System Operation, Feature 2: Optimization of Airflow Management System, and Feature 3: Simultaneous Optimization of Airflow Management and Cooling Systems, are described first. Feature 1 is implemented in Phase 1 of the project and demonstrates 15% energy savings from cooling system optimization by applying the proposed retrofit solutions. Feature 2 is implemented in Phase 2 and the assessments show cooling energy-saving potential between 19.3% and 54.0%, depending on the energy-saving measures employed. In addition, investigating the energy saving potential for a hypothetical simple data center shows about 6.8% energy savings by optimizing the server load placement. Feature 3 is implemented in Phase 3 and the results show energy savings of 53.4% and 74.6% for the two partner data centers, respectively, compared to the baselines defined in Phase 1. Lastly, the project outcomes including software releases and publications are discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1993

Transient development of perturbations in stratified shear flow

Transient development of perturbations in inviscid stratified shear flow is investigated. Use is made of closed form analytic solutions that allow concise identification of optimally growing plane-wave solutions for the case of an unbounded flow with constant shear and stratification. For the case of channel flow, variational techniques are employed to determine the optimally growing disturbances. The maximum energy growth attained over a specific time interval decreases continuously with increasing stratification, and no special significance attaches to Ri = 0.25. Indeed, transient growth can be substantial even for Ri = O(1). A general lower bound on the energy growth attained by an optimal perturbation in a stratified flow over a given time interval is the square root of the growth attained by the corresponding perturbation in unstratified flow. Enhanced perturbation persistence is found for mean-flow stratification lying in the range Ri between 0.1 and 0.3. Small but finite perturbations in mean flow with Ri less than 0.4 produce regions with locally negative total density gradient, which are expected to overturn. Although the perturbations are of wave form, buoyancy fluxes mediate transfer between perturbation kinetic and potential energy during transient development, thus implying that buoyancy flux is not a determinative diagnostic for distinguishing between waves and turbulence in stratified flows.

Farrell, Brian F.↗
DOE OSTI2024

Component-to-Optimization Workflow Demonstration

This report aims to demonstrate workflow-generating algorithms for optimizing dispatch across a broad range of Integrated Energy System applications using the Framework for Optimization of Resources and Economics (FORCE) tool suite. The optimization is performed at two different time scales. In the coarse time scale, the optimization focuses on a class of energy sources and consumers and aims to find the optimal combinations and flows of energy based on real-time price data information. In the fine time scale, the optimization focuses on a specific thermal energy delivery system and aims to find the optimal setpoints of components in order to meet the energy demands from coarse-time-scale optimizations. In this demonstration, the coarse-scale optimization is implemented using the newly developed Dispatch Optimization Variable Engine (DOVE), while the fine-scale optimization used Optimization of Real-Time Capacity Allocation (ORCA).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Energy storage planning for enhanced resilience of power systems against wildfires and heatwaves

Extreme weather events pose significant risks to power grid stability due to their severe consequences and potential for widespread failures. Energy storage systems hold great potential for enhancing grid resilience against such events by providing reliable power during peak demand periods. However, accurately quantifying the size, location, and investment costs of new energy storage assets is a complex task, as energy storage planning decisions depend on the investment choices of other generation technologies and the integration of new transmission projects. Here, this paper presents a novel capacity expansion planning framework that simultaneously optimizes investments in energy storage, generation, and transmission, determining their optimal size, location, and type, while incorporating extreme weather events into long-term planning. More specifically, our stress-event-informed planning framework integrates the impact of heatwaves and wildfires into the planning process, identifying least-cost investment solutions that comply with policy goals and enhance grid resilience. The proposed framework employs machine-learning-based modeling to project heatwave-induced loads and performance-based risk assessment to evaluate wildfire-driven transmission line derates. Using industry-standard datasets to accurately represent the transmission topology of the Western Interconnection (WI) system, the proposed framework is applied to the WI 40-zone system, with investment decisions reported for the years 2030, 2035, and 2040. Simulation results reveal that with just a 10% increase in investment costs, resilience against extreme events can be significantly improved, with investment decisions heavily favoring energy storage, particularly 4-hour energy storage systems.

25 ENERGY STORAGE↗
NASA NTRS2019

NASA Thermal Recovery Energy Efficient System (TREES) for Aircraft Exergy Optimization

Future air vehicles will increasingly incorporate electrical powertrains that require very tight integration of power, propulsion, thermal, and airframe technologies. These complex and highly integrated sub-systems present a new exergy utilization and thermo-economics challenge due to the significant and highly distributed low-grade waste heat being produced. One system-wide solution is proposed that utilizes acoustic thermal energy conversion technologies to simultaneously provide thermal management and waste energy recycling for the entire vehicle. This system level solution serves to optimize aircraft exergy utilization.

Dyson, Rodger↗
DOE OSTI2021

Combined Land Use of Solar Infrastructure and Agriculture for Socioeconomic and Environmental Co-Benefits in the Tropics

Solar photovoltaics (PV) are on the rise even in areas of low solar insolation. However, in developing countries with limited capital, land scarcity, or with geographically isolated agrarian communities, large solar infrastructures are often impractical. In these cases, implementation of low-density PV over existing crops may be required to integrate renewable energy services into rural communities. Here, using Indonesia as a model system, we investigated the land use, energy, greenhouse gas emissions, economic feasibility, and the environmental co-benefits associated with off-grid solar PV when combined with high value crop cultivation. The life cycle analyses indicate that small-scale dual land-use systems are economically viable in certain configurations and have the potential to provide several co-benefits including rural electrification, retrofitting diesel electricity generation, and electricity for processing agricultural products locally. A hypothetical full-density off-grid solar PV for a model village in Indonesia shows that electricity output (1907.5 GJ yr-1) is much higher than the total residential consumption (678 GJ yr-1), highlighting the opportunity to downscale the PV infrastructure by half to lower capital cost, to co-locate crops, and to support secondary income generating activities. Economic analysis shows that the 30-year net present cost of electricity from the half-density co-located PV system (12,257 million IDR) is significantly lower than that of the flat cost of diesel required to generate equivalent electricity (14,702 million IDR). Our analysis provides insights for smarter energy planning by optimizing the efficiency of land use and limiting conversion of agricultural and forested areas for energy production.

agrivoltaics↗
DOE OSTI2020

Scale and Regionality of Nonelectric Markets for U.S. Nuclear Light Water Reactors

This study assesses existing and potential industries that could conceivably be directly coupled to existing nuclear reactors. The goal is to identify the scale, location, and accessibility of the candidate industrial-product markets, as well as process feedstocks that are available near the plants to establish new industries. For example, CO 2 as a feedstock can be combined with H 2 to produce formic acid (FA), transportation fuels, and lubricants. These new plants can be entirely supported with the heat and electricity provided by a nearby NPP. The potential demand for nonelectric industrial products was assessed by documenting current and possible growth of nonelectricity product markets considered. This assessment used DOE- and industry-supported tools, data, and projections to capture regional industrial market opportunities. Electricity-capacity markets that reward large and reliable generators, such as NPPs, were considered because the electricity market will likely continue to be an important revenue source to NPPs. The key is to balance the needs of energy customers so as to optimize revenue for the affiliated energy customers or partners. In most cases, flexible plant energy delivery and power generation for the grid will require either energy storage or a stock of intermediate products to sustain the industrial customers when the NPP dispatches electricity to the grid. A diverse mix of temperate regions with operating NPPs around the U.S.—representing a variety of operating markets, local generation mix, and seasonal climates—were chosen for this market study. Both current and future market opportunities for candidate industrial-product markets surrounding these NPPs were studied. Figure 2 illustrates the regions chosen for this study. The success of developing nonelectric industrial-product markets as alternative revenue-generating sources for LWRs depends, not only on demand from growing existing markets, such as petroleum refining and NH 3 production, but also on the development of new markets such as light-duty (LD) and heavy-duty (HD) hydrogen FCEVs, synfuels, chemical production, biofuels, metal refining, injection of hydrogen into NG pipelines for gas power-generating units, FA, polymers, and close-coupled industrial heat applications, all of which can significantly increase demand relative to current levels while decarbonizing energy sectors. This study also presents a sample analysis of the economics of hydrogen production in an area of Minnesota, considering the capital and operating costs of a hydrogen plant as well as the local market demand for hydrogen. It includes some assumptions on electricity-grid pricing, showing how hydrogen could be integrated with an NPP and be competitive with the incumbent hydrogen-production process, steam methane reforming (SMR). The objectives of this study include: Provide U.S. NPP operators a robust sampling of the market demand location, scale, and accessibility (including storage and transportation) of the wide variety of industrial-product choices that can be produced using nuclear thermal energy and electricity proximate to a subset of U.S. NPPs to inform the industry of the potential opportunity; show examples and trade-off analyses of how U.S. LWR operators can access these markets, including storage and transportation of industrial products to their intended markets; and present a general analysis example for one industrial product (hydrogen) in one region (Minnesota area), including production, storage, and transportation, to show how nuclear-hybrid integrated energy systems (IESs) could access local markets and improve the profitability of an NPP.

03 NATURAL GAS↗
DOE OSTI2023

Summary: Techno-Economic Analysis of Solar Photovoltaics and Battery Energy Storage at a Vietnam Industrial Park

The Clean Energy Investment Accelerator conducted a case study analysis of battery energy storage system (BESS) feasibility for an industrial park in Vietnam using the National Renewable Energy Laboratory's (NREL's) REopt platform (a distributed energy modeling and optimization tool) to evaluate how BESS may reduce electricity costs, increase utilization of onsite renewable energy generation, and improve resilience to utility grid outages. This presentation summarizes the analysis and key takeaways.

batteries↗
DOE OSTI2024

LogPath: Log data based energy consumption analysis enabling electric vehicle path optimization

Vehicle navigation and path optimization require a more meticulous approach when it deals with EVs (electric vehicles) and SDVs (software-defined vehicles), due to lengthy charging times and the lack of charging infrastructure. Long-distance freight EV trucking needs path guidance with accurate energy consumption estimates to prevent charging-related failures. We developed a novel energy consumption estimation approach that only uses battery log data to extract major vehicle parameters to increase EV navigation accuracy without additional sensors. This is enabled by extracting multiple drive modes from the log data for analysis. The system provides 1) routes, 2) charge locations, 3) charging times, and 4) optimal vehicle speeds that guarantee the shortest travel time. Here we successfully validated the system using log data collected from an EV and Tesla's Supercharging map in the US and compared it with the commercially available navigation system, Tesla's trip planner, whose capabilities solely include charging time and routing.

EV (Electric vehicles) navigation↗