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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Distributed energy management for community microgrids considering phase balancing and peak shaving

Here, a distributed energy management for community microgrids considering phase balancing and peak shaving is introduced. In each iteration, the house energy management system (HEMS) installed in each house minimises its electricity costs and the costs associated with the discomfort of customers due to deviations in indoor temperature from customers’ set points. At the community level, the microgrid central controller (MCC) schedules the distributed energy resources (DERs) and energy storage based on the received load profiles from customers and the forecast energy price at the point of common coupling. The MCC updates the energy price for each phase based on the amount of unbalanced power between generation and consumption. The updated energy price and unbalanced power for each phase are distributed to the HEMSs on corresponding phases. When the optimisation converges, the unbalanced power of each phase is close to zero. Meanwhile, the schedules of DERs, energy storage systems and the energy consumption of each house are determined by the MCC and HEMSs, separately. Specifically, the phase balancing and peak shaving are considered in the proposed distributed energy management model. The effectiveness of the proposed distributed energy management has been illustrated by case studies.

25 ENERGY STORAGE↗
DOE OSTI2019

The Role of Building Codes and Controls in Enhancing Community Resilience

Countries, states, and cities around the world are seeking to enhance power sector resilience through a combination of policy and technology. However, few of these efforts fully incorporate the built environment into power sector planning. Buildings account for more than a third of the global annual energy consumption and more than 60% of the annual electricity consumption. As such, buildings play a critical role in enhancing resilience in the power sector. Buildings can aid in power sector resilience by increasing power system flexibility, shaving and shifting demand, and providing on-site energy generation. All of these strategies require incentives to encourage participation. This paper presents an overview of energy management strategies to better incorporate building design and operation in power sector resilience planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Evaluation of rice husk ash as filler in tread compounds

Rice which is one of the largest agriculture crops produces around 22% of rice rusk during its milling process. This material is mainly used as fuel for energy generation, which results in an ash, which disposal represents an environmental issue. The rice husk ash (RHA) contains over than 70% of silica in an amorphous form and a lot of applications is being developed for it all over the world. The use of silica as a filler in the tire industry is growing since it contributes significantly to the reduction of fuel consumption of the automobiles, allowing at the same time better traction (safety). This paper presents an evaluation of the use of RHA as filler in rubber tread compounds prepared in lab scale and compares its performance with compounds prepared with commercial silica and carbon black, the fillers normally used in tire industry. Mechanical and rheological properties are evaluated, with emphasis for tan delta as an indicator of tread performance related with rolling resistance (fuel consumption) and wet grip/traction (safety)

36 MATERIALS SCIENCE↗
DOE OSTI2015

Spin-orbit torque induced spike-timing dependent plasticity

Nanoelectronic devices that mimic the functionality of synapses are a crucial requirement for performing cortical simulations of the brain. In this work, we propose a ferromagnet-heavy metal heterostructure that employs spin-orbit torque to implement spike-timing dependent plasticity. The proposed device offers the advantage of decoupled spike transmission and programming current paths, thereby leading to reliable operation during online learning. Possible arrangement of such devices in a crosspoint architecture can pave the way for ultra-dense neural networks. Simulation studies indicate that the device has the potential of achieving pico-Joule level energy consumption (maximum 2 pJ per synaptic event) which is comparable to the energy consumption for synaptic events in biological synapses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Determinants of CO{sub 2} emissions in ASEAN countries using energy and mining indicators

Carbon dioxide (CO{sub 2}) is the main greenhouse gas emitted from human activities. Industrial revolution is one of the triggers to accelerate the quantity of CO{sub 2} in the atmosphere which lead to undesirable changes in the cycle of carbon. Like China and United States which are affected by the economic development growth, the atmospheric CO{sub 2} level in ASEAN countries is expected to be higher from year to year. This study focuses on energy and mining indicators, namely alternative and nuclear energy, energy production, combustible renewables and waste, fossil fuel energy consumption and the pump price for diesel fuel that contribute to CO{sub 2} emissions. Six ASEAN countries were examined from 1970 to 2010 using panel data approach. The result shows that model of cross section-fixed effect is the most appropriate model with the value of R-squared is about 86%. Energy production and fossil fuel energy consumption are found to be significantly influenced to CO{sub 2} emissions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Hydrogen-based power generation from bioethanol steam reforming

This paper is evaluating two power generation concepts based on hydrogen produced from bioethanol steam reforming at industrial scale without and with carbon capture. The power generation from bioethanol conversion is based on two important steps: hydrogen production from bioethanol catalytic steam reforming and electricity generation using a hydrogen-fuelled gas turbine. As carbon capture method to be assessed in hydrogen-based power generation from bioethanol steam reforming, the gas-liquid absorption using methyl-di-ethanol-amine (MDEA) was used. Bioethanol is a renewable energy carrier mainly produced from biomass fermentation. Steam reforming of bioethanol (SRE) provides a promising method for hydrogen and power production from renewable resources. SRE is performed at high temperatures (e.g. 800-900°C) to reduce the reforming by-products (e.g. ethane, ethene). The power generation from hydrogen was done with M701G2 gas turbine (334 MW net power output). Hydrogen was obtained through catalytic steam reforming of bioethanol without and with carbon capture. For the evaluated plant concepts the following key performance indicators were assessed: fuel consumption, gross and net power outputs, net electrical efficiency, ancillary consumptions, carbon capture rate, specific CO{sub 2} emission etc. As the results show, the power generation based on bioethanol conversion has high energy efficiency and low carbon footprint.

08 HYDROGEN↗
DOE OSTI2016

A study experiment of auto idle application in the excavator engine performance

The purpose of this study was to analyze the effect of applying auto idle to excavator engine performance, such as machine unitization and fuel consumption in Excavator. Steps to be done are to modify the system JA 44 and 67 in Vehicle Electronic Control Unit (V-ECU). The modifications will be obtained from the pattern of the engine speed. If the excavator attachment is not operated, the engine speed will return to the idle speed automatically. From the experiment results the auto idle reduces fuel consumption in excavator engine.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Ideas That Work! The Midnight Audit

The midnight audit provides valuable insight toward identifying opportunities to reduce energy consumption—insight that can be easily overlooked during the normal (daytime) energy auditing process. The purpose of the midnight audit is to observe after-hour operation with the mindset of seeking ways to further minimize energy consumption during the unoccupied mode and minimize energy waste by reducing unnecessary operation. The midnight audit should be used to verify that equipment is off when it is supposed to be, or operating in set-back mode when applicable. Even a facility that operates 2 shifts per day, 5 days per week experiences fewer annual hours in occupied mode than it does during unoccupied mode. Minimizing energy loads during unoccupied hours can save significant energy, which is why the midnight audit is an Idea That Works.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Energy savings and usability of zero-client computing in office settings

This study provides a detailed comparison of the power consumption, usability, and applicability of virtual machines (VMs) - accessed through zero-client devices - and traditional laptop computers in office settings. The study analyzed high-level plug loads across two office spaces, one using traditional laptops, the other using zero clients. In addition, the individual power consumption of four workstations was monitored and compared. Each workstation user switched between using a laptop or zero client for one week and then using the alternate system the second week. Results of the high-level and workstation analysis show that average workstation plug loads are lower for occupants using zero clients. However, this does not include power consumed by the data center managing VMs. This study calculates the affiliated data center power draw of VMs and shows that server-related loads push total zero-client computing energy higher than that of traditional laptops. Finally, a questionnaire was administered to building occupants to determine the appropriateness of zero-client computing for various user groups, with the results indicating that VMs are most appropriate for more basic software functions. The findings of this study suggest that advances in server technology can help improve both the overall efficiency and the usability of zero-client computing.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Energy savings modelling of re-tuning energy conservation measures in large office buildings

Today, many large commercial buildings use sophisticated building automation systems (BASs) to manage a wide range of building equipment. While the capabilities of BASs have increased over time, many buildings still do not fully use the BAS’s capabilities and are not properly commissioned, operated or maintained, which leads to inefficient operation, increased energy use, and reduced lifetimes of the equipment. This paper investigates the energy savings potential of several common HVAC system re-tuning measures on a typical large office building, using the Department of Energy’s building energy modeling software, EnergyPlus. The baseline prototype model uses roughly as much energy as an average large office building in existing building stock, but does not utilize any re-tuning measures. Individual re-tuning measures simulated against this baseline include automatic schedule adjustments, damper minimum flow adjustments, thermostat adjustments, as well as dynamic resets (set points that change continuously with building and/or outdoor conditions) to static pressure, supply-air temperature, condenser water temperature, chilled and hot water temperature, and chilled and hot water differential pressure set points. Six combinations of these individual measures have been formulated – each designed to conform to limitations to implementation of certain individual measures that might exist in typical buildings. All the individual measures and combinations were simulated in 16 climate locations representative of specific U.S. climate zones. The modeling results suggest that the most effective energy savings measures are those that affect the demand-side of the building (air-systems and schedules). Many of the demand-side individual measures were capable of reducing annual total HVAC system energy consumption by over 20% in most cities that were modeled. Supply side measures affecting HVAC plant conditions were only modestly successful (less than 5% annual HVAC energy savings for most cities for all measures). Combining many of the re-tuning measures revealed deep savings potential. Some of the more aggressive combinations revealed 35-75% reductions in annual HVAC energy consumption, depending on climate and building vintage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Methodology and analytical approach to investigate the impact of building temperature setpoint schedules

This work presents a method for generating a large set of stochastically varying temperature setpoint schedules for building performance simulations. It analyses tradeoffs resulting from specific changes to those schedules in terms of three quantities: total electricity consumption per day; maximum hourly electricity consumption per day and predicted percentage dissatisfied (occupant thermal comfort). The method for generating schedules requires a single base schedule as the starting point and, using a few clearly defined parameters, transforms it into a set of schedules that can be used for modelling an existing building stock or for performing parametric studies. Temperature setpoint schedules are generated and simulated for a small office building in a cool-dry climate in three different case studies pertaining to changing temperature setpoint schedules. Tradeoffs between the three output metrics are significant and vary based on the temperature setpoint schedules and the time of the year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Cost-effective retrofit technology for reducing peak power demand in small and medium commercial buildings

We describe a cost-effective retrofit technology that uses collective control of multiple rooftop air conditioning units to reduce the peak power consumption of small and medium commercial buildings. The proposed control uses a model of the building and air conditioning units to select an operating schedule for the air conditioning units that maintains a temperature set point subject to a constraint on the number of units that may operate simultaneously. A prototype of this new control system was built and deployed in a large gymnasium to coordinate four rooftop air conditioning units. Based on data collected while operating this prototype, we estimate that the cost savings achieved by reducing peak power consumption is sufficient to repay the cost of the prototype within a year.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data

New technologies, such as connected and automated vehicles, have attracted more and more researchers for improving the energy efficiency and environmental impact of current transportation systems. The green routing strategy instructs a vehicle to select the most fuel-efficient route before the vehicle departs. It benefits the current transportation system with fuel saving opportunity through identifying the greenest route. This paper introduces an evaluation framework for estimating benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption of actual routes and comparing to routes procured by navigation systems. A route-based fuel consumption estimation model, considering road traffic conditions, functional class, and road grade is proposed and used in the framework. An experiment using a large-scale data set from the California Household Travel Survey global positioning system trajectory data base indicates that 31% of actual routes have fuel savings potential with a cumulative estimated fuel savings of 12%.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Data-Enabled Building Energy Savings (D-E BES)

Building sector energy consumption represents a significant fraction of the overall energy consumption in urban communities. While there has been increasing focus on the development of smart environments to support energy savings in urban commercial buildings, the development of smart environments for the residential sector has been less common. Instead, urban residential energy-saving efforts have focused on improving a building's physical infrastructure, introducing energy-saving appliances, and motivating residents to adopt energy conservation practices. Herein this paper illustrates that creating an affinity between a building resident's thermal preferences and a building apartment's unregulated thermal environment represents an alternative means of generating an energy-efficient environment for multi-family, residential buildings. Two years of 15-min interval summer data, obtained from smart cyber-physical systems installed in 310 apartments across two New York City buildings, is used to develop data-enabled (D-E) models of resident thermal preference and unregulated apartment temperatures. Both of these models use a linear mixed-effects approach. The alignment of optimal resident-apartment pairs is then formulated as an integer-programming problem to explore the building energy saving (BES) potential associated with minimizing the difference between unregulated apartment temperature and the residents' thermal preference based on summer cooling loads. The work shows that the energy saving potential vary with a building's physical characteristics as well as the variation in residents' thermal preferences. The work further demonstrates that both the unregulated temperature and the resident's preferred temperature in a given apartment are not only affected by outside temperature and external relative humidity, but also strongly affected by the apartment's geographic orientation. For the specific buildings considered, up to 28% cooling energy saving is possible with full alignment. The paper provides all building monitoring data as an open source data set.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A Critical Exploration of the Efficiency Impacts of Demand Response From HVAC in Commercial Buildings

Increasing quantities of renewable energy generation has yielded a need for greater energy storage capacity in power systems. Thermal storage in variable air volume (VAV) heating, ventilation, and air conditioning (HVAC) in commercial buildings has been identified as an inexpensive source of grid storage, but the true costs are not known. Recent literature explores the inefficiency associated with providing grid services from these HVAC-based demand response (DR) resources by employing a battery analogy to calculate round-trip efficiency (RTE). Results vary significantly across studies and in some cases reported efficiencies are strikingly low. This article has three objectives to address these prior results. First, we synthesize and expand on insights into existing literature by systematically exploring the potential causes for the discrepancies in results. We reinforce previous work indicating baseline modeling may drive differences across studies and deduce that control accuracy plays a role in the major differences between experiments and simulation. Second, we discuss why the RTE metric is problematic for DR applications, discuss another proposed metric, additional energy consumption (AEC), and propose an extension, which we call uninstructed energy consumption (UEC), to evaluate DR performance. Finally, we explore the merits of different metrics using experimental data and highlight UEC's reduced sensitivity to the characteristics of the DR signal than previously proposed metrics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

The Opportunities and Controversies of Reversible Computing

Industry's inability to reduce logic gates' energy consumption is slowing growth in an important part of the worldwide economy. Some scientists argue that alternative approaches could greatly reduce energy consumption. Lastly, these approaches entail myriad technical and political issues.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Opportunities for nonvolatile memory systems in extreme-scale high-performance computing

For extreme-scale high-performance computing systems, system-wide power consumption has been identified as one of the key constraints moving forward, where DRAM main memory systems account for about 30 to 50 percent of a node's overall power consumption. As the benefits of device scaling for DRAM memory slow, it will become increasingly difficult to keep memory capacities balanced with increasing computational rates offered by next-generation processors. However, several emerging memory technologies related to nonvolatile memory (NVM) devices are being investigated as an alternative for DRAM. Moving forward, NVM devices could offer solutions for HPC architectures. Researchers are investigating how to integrate these emerging technologies into future extreme-scale HPC systems and how to expose these capabilities in the software stack and applications. In addition, current results show several of these strategies could offer high-bandwidth I/O, larger main memory capacities, persistent data structures, and new approaches for application resilience and output postprocessing, such as transaction-based incremental checkpointing and in situ visualization, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Short-Term Load Forecasting Considering EV Charging Loads with Prediction Interval Evaluation

Short-term load forecasting plays a critical role in power system planning and operation. Along with the electrification of various loads, electricity demands are becoming increasingly hard to predict. Notably, the recent rise in electric vehicles (EVs) has further contributed to this unpredictability. To address this issue, this paper proposes a probabilistic load forecasting strategy utilizing Gaussian process regression, structured in a day-ahead manner. While many works focus on deterministic prediction, probabilistic forecasting offers additional insights into variability and uncertainty, enabling more flexible and reliable operation for power systems. To enhance the accuracy of the load forecasting model, the inputs include features related to EV charging habits as well as commonly used weather information. The load forecasting results are evaluated using various metrics, including conventional ones that assess the accuracy of point forecasts, as well as additional metrics that test the reliability of prediction intervals. The proposed load forecasting method is finally tested on real residential power consumption data and EV charging data sampled from real-world sources. The results prove that the new features can greatly improve the performance of the load forecasting method.

electrical vehicle↗