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At least 127 records · Page 7

Economic Optimal Control for Minimizing Fuel Consumption of Heavy-Duty Trucks in a Highway Environment

This paper provides a comparative assessment of three economic optimal control strategies, aimed at minimizing the fuel consumption of heavy-duty trucks in a highway environment, under a representative lead vehicle model informed by traffic data. These strategies fuse a global, offline dynamic programming (DP) optimization with online model predictive control (MPC). We then show how two of the three strategies can be adapted to accommodate the presence of traffic and optimally navigate signalized intersections using infrastructure-to-vehicular (I2V) communication. The MPC optimization, which is local in nature, makes refinements to a coarsely (but globally, subject to grid resolution) optimized target velocity profile from the DP optimization. The three candidate economic MPC formulations that are evaluated include: a nonlinear time-based formulation that directly penalizes predicted fuel consumption, a nonlinear time-based formulation that penalizes braking effort as a surrogate for fuel consumption, and a linear distance-based convex formulation that maintains a tradeoff between energy expenditure and tracking of the coarsely optimized velocity profile obtained from DP. Using a medium-fidelity Simulink model, based on a Volvo truck's longitudinal and engine dynamics, we analyze the optimization's performance on four highway routes under various traffic scenarios. Results demonstrate 3.7-8.3% fuel economy improvement on highway routes without traffic and 6.5-10% on the same routes with traffic included. Furthermore, we present a detailed analysis of energy usage by "type" (aerodynamic losses, braking losses, and comparison of brake-specific fuel consumption), under each candidate control strategy.

33 ADVANCED PROPULSION SYSTEMS↗

Paternal preconception alcohol consumption increased Angiotensin II‐mediated vasoconstriction in male offspring cerebral arteries via oxidative stress‐AT1R pathway

Abstract Alcohol consumption is popular worldwidely and closely associated with cardiovascular diseases. Influences of paternal preconception alcohol consumption on offspring cerebral arteries are largely unknown. Male rats were randomly given alcohol or water before being mated with alcohol‐naive females to produce alcohol‐ and control‐sired offspring. Middle cerebral artery (MCA) was tested with a Danish Myo Technology wire myograph, patch‐clamp, IONOPTIX, immunofluorescence and quantitative PCR. Alcohol consumption enhanced angiotensin II (AngII)‐mediated constriction in male offspring MCA mainly via AT1R. PD123,319 only augmented AngII‐induced constriction in control offspring. AngII and Bay K8644 induced stronger intracellular calcium transient in vascular smooth muscle cells (VSMCs) from MCA of alcohol offspring. L‐type voltage‐dependent calcium channel (L‐Ca 2+ ) current at baseline and after AngII‐stimulation was higher in VSMCs. Influence of large‐conductance calcium‐activated potassium channel (BK C a ) was lower. Caffeine induced stronger constriction and intracellular calcium release in alcohol offspring. Superoxide anion was higher in alcohol MCA than control. Tempol and thenoyltrifluoroacetone alleviated AngII‐mediated contractions, while inhibition was significantly higher in alcohol group. The mitochondria were swollen in alcohol MCA. Despite lower Kcnma1 and Prkce expression, many genes expressions were higher in alcohol group. Hypoxia induced reactive oxygen species production and increased AT1R expression in control MCA and rat aorta smooth muscle cell line. In conclusion, this study firstly demonstrated paternal preconception alcohol potentiated AngII‐mediated vasoconstriction in offspring MCA via ROS‐AT1R. Alcohol consumption increased intracellular calcium via L‐Ca 2+ channel and endoplasmic reticulum and decreased BK Ca function. The present study provided new information for male reproductive health and developmental origin of cerebrovascular diseases.

Zhang, Ze↗

Simultaneous numerical representation of soil microsite production and consumption of carbon dioxide, methane, and nitrous oxide using probability distribution functions

Production and consumption of nitrous oxide (N 2 O), methane (CH 4 ), and carbon dioxide (CO 2 ) are affected by complex interactions of temperature, moisture, and substrate supply, which are further complicated by spatial heterogeneity of the soil matrix. This microsite heterogeneity is often invoked to explain non-normal distributions of greenhouse gas (GHG) fluxes, also known as hot spots and hot moments. To advance numerical simulation of these belowground processes, we expanded the Dual Arrhenius and Michaelis-Menten (DAMM) model, to apply it consistently for all three GHGs with respect to the biophysical processes of production, consumption, and diffusion within the soil, including the contrasting effects of oxygen (O 2 ) as substrate or inhibitor for each process. High-frequency chamber-based measurements of all three GHGs at the Howland Forest (ME, USA) were used to parameterize the model using a multiple constraint approach. The area under a soil chamber is partitioned according to a bivariate lognormal probability distribution function (PDF) of carbon (C) and water content across a range of microsites, which leads to a PDF of heterotrophic respiration and O 2 consumption among microsites. Linking microsite consumption of O 2 with a diffusion model generates a broad range of microsite concentrations of O 2 , which then determines the PDF of microsites that produce or consume CH 4 and N 2 O, such that a range of microsites occurs with both positive and negative signs for net CH 4 and N 2 O flux. Results demonstrate that it is numerically feasible for microsites of N 2 O reduction and CH 4 oxidation to co-occur under a single chamber, thus explaining occasional measurement of simultaneous uptake of both gases. Simultaneous simulation of all three GHGs in a parsimonious modeling framework is challenging, however it increases confidence that agreement between simulations and measurements is based on skillful numerical representation of processes across a heterogeneous environment.

59 BASIC BIOLOGICAL SCIENCES↗

Extracellular Acidic pH Inhibits Acetate Consumption by Decreasing Gene Transcription of the Tricarboxylic Acid Cycle and the Glyoxylate Shunt

Escherichia coli produces acetate during aerobic growth on various carbon sources. After consuming the carbon substrate, E. coli can further grow on the acetate. This phenomenon is known as the acetate switch, where cells transition from producing acetate to consuming it. In this study, we investigated how pH governs the acetate switch. When E. coli was grown on a glucose-supplemented medium initially buffered to pH 7, the cells produced and then consumed the acetate. However, when the initial pH was dropped to 6, the cells still produced acetate but were only able to consume it when little (<10 mM) acetate was produced. When significant acetate was produced in acidic medium, which occurs when the growth medium contains magnesium, amino acids, and sugar, the cells were unable to consume the acetate. To determine the mechanism, we characterized a set of metabolic mutants and found that those defective in the tricarboxylic acid (TCA) cycle or glyoxylate shunt exhibited reduced rates of acetate consumption. We further found that the expression of the genes in these pathways was reduced during growth in acidic medium. The expression of the genes involved in the AckA-Pta pathway, which provides the principal route for both acetate production and consumption, was also inhibited in acidic medium but only after glucose was depleted, which correlates with the acetate consumption phase. On the basis of these results, we conclude that growth in acidic environments inhibits the expression of the acetate catabolism genes, which in turn prevents acetate consumption.

59 BASIC BIOLOGICAL SCIENCES↗

Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States

This report is the second in a series of Electrification Futures Study (EFS) publications, a multi-year research project to explore widespread electrification in the future energy system of the United States. The report presents scenarios of electric end-use technology adoption and resulting electricity consumption in the United States. The scenarios are used to characterize changes to end-use sectors under futures with increased electrification and to quantify how those changes might impact the amount and shape of electricity consumption. These scenarios were developed primarily using expert judgment and an energy system accounting framework. Of course, technology adoption will ultimately depend on a set of complex considerations that are not fully assessed using our methodology, but which are discussed extensively throughout the report. These interacting factors include technology and fuel cost trade-offs, infrastructure needs, environmental policies, and consumer preference. Within each of these factors are barriers that might challenge increased electrification - such as higher upfront costs or unfamiliarity with new electric technologies - but also opportunities that could yield greater adoption - such as increased productivity or expanded value streams enabled by electric and/or grid-connected technologies. Understanding and quantifying these factors are needed to both evaluate the implications of a potential increased electrification future and to influence the degree of future electrification. Overall, the report represents an initial step to inform researchers and decision-makers with data and context to plan for a potential future in which electricity powers an expanded share of the U.S. energy economy.This report is the second in a series of Electrification Futures Study (EFS) publications, a multi-year research project to explore widespread electrification in the future energy system of the United States. The report presents scenarios of electric end-use technology adoption in all major sectors - transportation, commercial and residential buildings, and industry - and resulting electricity consumption in the United States. The scenarios are used to characterize changes to end-use sectors under futures with increased electrification and to quantify how those changes might impact the amount and shape of electricity consumption. These scenarios were developed primarily using expert judgment and an energy system accounting framework. Of course, technology adoption will ultimately depend on a set of complex considerations that are not fully assessed using our methodology, but which are discussed extensively throughout the report. These interacting factors include technology and fuel cost trade-offs, infrastructure needs, environmental policies, and consumer preference. Within each of these factors are barriers that might challenge increased electrification - such as higher upfront costs or unfamiliarity with new electric technologies - but also opportunities that could yield greater adoption, such as increased productivity or expanded value streams enabled by electric and grid-connected technologies. Understanding and quantifying these factors are needed to both evaluate the implications of a potential increased electrification future and to influence the degree of future electrification. Overall, the report represents an initial step to inform researchers and decision-makers with data and context to plan for a potential future in which electricity powers an expanded share of the U.S. energy economy.

2050↗

Oxygen consumption of animals under conditions of hypokinesia

The influence of hypokinesia on the oxygen consumption of rats, dog, and squirrels was investigated. Three periods of gaseous exchange were revealed in rats under conditions of a limited motor activity. During the first 10-15 days O2 consumption displayed a sharp elevation; on the 20th-30th day, it became stabilized at a higher level (in comparison with control) and it sharply rose again on the 40th-100th day. In dogs, hypokinesia produced a reduction of O2 consumption and then a tendency to its elevation was seen. A short period of physical exercises in squirrels after hypokinesia led to increased oxygen consumption at rest.

Loginova, Y. N.↗

Measured effect of wind generation on the fuel consumption of an isolated diesel power system

The Block Island Power Company (BIPCO), on Block Island, Rhode Island, operates an isolated electric power system consisting of diesel generation and an experimental wind turbine. The 150-kW wind turbine, designated MOD-OA by the U.S. Department of Energy is typically operated in parallel with two diesel generators to serve an average winter load of 350 kW. Wind generation serves up to 60 percent of the system demand depending on wind speed and total system load. Results of diesel fuel consumption measurements are given for the diesel units operated in parallel with the wind turbine and again without the wind turbine. The fuel consumption data are used to calculate the amount of fuel displaced by wind energy. Results indicate that the wind turbine displaced 25,700 lbs. of the diesel fuel during the test period, representing a calculated reduction in fuel consumption of 6.7 percent while generating 11 percent of the total electric energy. The amount of displaced fuel depends on operating conditions and system load. It is also shown that diesel engine throttle activity resulting from wind gusts which rapidly change the wind turbine output do not significantly influence fuel consumption.

Stiller, P. H.↗

Influence of simulated microgravity on the maximal oxygen consumption of nontrained and trained rats

The effects of microgravity and endurance training (TR) on maximal O2 consumption was investigated in trained and nontrained (NT) rats subjected to head-down suspension (HDS) by comparing maximal O2 consumption, treadmill run time (RT), and mechanical efficiency (ME) of treadmill running in HDS rats, both NT and TR, and in respective cage controls. It was found that HDS for 28 days was associated with significant reduction in absolute maximal O2 consumption in both TR and NT rats. Relative maximal O2 consumption, however, was significantly reduced in TR but not NT rats. Reductions in RT and ME occurring in both TR and NT rats after 28 days of HDS were similar. The TR rats exhibited greater diuretic, natriuretic, and kaliuretic responses to HDS than the NT rats.

Woodman, Christopher R.↗

Development of a Complete Landsat Evapotranspiration and Energy Balance Archive to Support Agricultural Consumptive Water Use Reporting and Prediction in the Central Valley, CA

Mapping evapotranspiration (ET) from agricultural areas in Californias Central Valley is critical for understanding historical consumptive use of surface and groundwater. In addition, long histories of ET maps provide valuable training information for predictive studies of surface and groundwater demands. During times of drought, groundwater is commonly pumped to supplement reduced surface water supplies in the Central Valley. Due to the lack of extensive groundwater pumping records, mapping consumptive use using satellite imagery is an efficient and robust way for estimating agricultural consumptive use and assessing drought impacts. To this end, we have developed and implemented an algorithm for automated calibration of the METRIC remotely sensed surface energy balance model on NASAs Earth Exchange (NEX) to estimate ET at the field scale. Using automated calibration techniques on the NEX has allowed for the creation of spatially explicit historical ET estimates for the Landsat archive dating from 1984 to the near present. Further, our use of spatial NLDAS and CIMIS weather data, and spatial soil water balance simulations within the NEX METRIC workflow, has helped overcome challenges of time integration between satellite image dates. This historical and near present time archive of agricultural water consumption for the Central Valley will be an extremely useful dataset for water use and drought impact reporting, and predictive analyses of groundwater demands.

valleys↗

USING TIME VARIANT VOLTAGE TO CALCULATE ENERGY CONSUMPTION AND POWER USE OF BUILDING SYSTEMS

Buildings are the main consumers of electricity across the world. However, in the research and studies related to building performance assessment, the focus has been on evaluating the energy efficiency of buildings whereas the instantaneous power efficiency has been overlooked as an important aspect of total energy consumption. As a result, we never developed adequate models that capture both thermal and electrical characteristics (e.g., voltage) of building systems to assess the impact of variations in the power system and emerging technologies of the smart grid on buildings energy and power performance and vice versa. This paper argues that the power performance of buildings as a function of electrical parameters should be evaluated in addition to systems’ mechanical and thermal behavior. The main advantage of capturing electrical behavior of building load is to better understand instantaneous power consumption and more importantly to control it. Voltage is one of the electrical parameters that can be used to describe load. Hence, voltage dependent power models are constructed in this work and they are coupled with existing thermal energy models. Lack of models that describe electrical behavior of systems also adds to the uncertainty of energy consumption calculations carried out in building energy simulation tools such as EnergyPlus, a common building energy modeling and simulation tool. To integrate voltage-dependent power models with thermal models, the thermal cycle (operation mode) of each system was fed into the voltage-based electrical model. Energy consumption of systems used in this study were simulated using EnergyPlus. Simulated results were then compared with estimated and measured power data. The mean square error (MSE) between simulated, estimated, and measured values were calculated. Results indicate that estimated power has lower MSE when compared with measured data than simulated results. Results discussed in this paper will illustrate the significance of enhancing building energy models with electrical characteristics. This would support different studies such as those related to modernization of the power system that require micro scale building-grid interaction, evaluating building energy efficiency with power efficiency considerations, and also design and control decisions that rely on accuracy of building energy simulation results.

Makhmalbaf, Atefe↗

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL's Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

47 OTHER INSTRUMENTATION↗

International Actions to Reduce Miscellaneous Electrical Loads Energy Consumption

Miscellaneous electric loads (MELs) research dates back over 30 years, with the earliest publications about MELs originating in the late 1980s. As the number and types of MELs have grown during the intervening decades, so has the body of minimum energy performance standards (MEPS) and regulations put in place to control what is now a significant energy end use in the residential and commercial sectors. In particular, these MEPS are designed to control off-mode, standby, and connected standby power consumption to prevent energy waste. Research on MELs focuses a great deal on analyzing the characteristics of MELs, approaches for measuring their consumption, and at a higher level what constitutes a MEL. Despite these advances, there have been few comparisons of different approaches to curtail MELs energy consumption across regulatory bodies of MELs—both between and within countries—to identify similarities, gaps, and opportunities for crafting common language and standards. This study provides an analysis of international MELs-related voluntary and mandatory MEPSs across 12 economies to address this gap. The analysis demonstrates that although economies may share the commitment to regulate the energy consumption of MELs, there still is no common language for framing MELs, nor is there a shared understanding for harmonizing MEPS for MELs.

Butzbaugh, Josh↗

International Actions to Reduce Miscellaneous Electrical Loads Energy Consumption

Miscellaneous electric loads (MELs) research dates back over thirty years, with the earliest publications on MELs originating in the late 1980s. As the number and types of MELs grew over the subsequent decades, so did the body of minimum energy performance standards (MEPS) and regulations put in place to control what is now an ever-growing source of energy consumption in the residential and commercial sectors. In particular, these MEPS are designed to control off-mode, standby, and connected standby power consumption to prevent energy waste. Research on MELs focuses a great deal on analyzing the characteristics of MELs, approaches for measuring their consumption, and at a higher level what constitutes a MEL. Despite these advances, there has yet to be a comparison of different approaches across regulatory bodies of MELs – both between and within countries – to identify similarities, gaps, and opportunities for crafting common language and testing procedures. This study provides an international analysis of MELs-related voluntary and mandatory MEPS across 12 economies to address this gap. The analysis demonstrates that even while economies may participate in shared commitments to regulated MELs energy consumption, there remains no common language for framing MELs, nor is there a shared understanding of updating aging test procedures used globally for verifying MELs-related MEPS.

Miscellaneous Electric Loads, MELs, Appliance and ↗

Online Calculator to Evaluate the Impact of Airtightness on Residential Building Energy Consumption and Moisture Transfer

Energy consumption in residential buildings is primarily driven by space conditioning applications. Space heating and cooling, on average, consume approximately 50% of the energy in the residential buildings in the U.S. The primary energy use due to infiltration is more than 2.8 Quads, which is 29% of primary energy consumption attributable to fenestration and building envelope components in residential buildings in US in 2010. There are advanced air barrier technologies and construction practices to reduce air leakage in buildings, which are currently available in the market. However, the lack of adequate information on their impact on energy consumption and the durability of buildings has caused the slow adoption of these technologies and methods. In the past, the authors developed an online calculator that estimates the potential energy and cost savings in major U.S., Canadian and Chinese cities from improvement in airtightness in commercial buildings. In 2018–2019, the calculator was expanded to add moisture transfer calculations, given that air leakage through the building envelope can have a significant impact on moisture transfer. The calculator is again being expanded by adding residential and additional commercial building data. In this paper, we present the impact of airtightness in residential buildings on energy consumption and moisture transfer. The study includes the analysis of airtightness in 52 major cities in the U.S. and five cities in Canada on a residential building that includes a crawlspace and has a gas furnace.

Kunwar, Niraj↗

Estimating Travel Energy Consumption Uncertainty Based on Inferred Travel Mode and Sensed Travel Length

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 8%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Electric train energy consumption modeling

For this paper we develop an electric train energy consumption modeling framework considering instantaneous regenerative braking efficiency in support of a rail simulation system. The model is calibrated with data from Portland, Oregon using an unconstrained non-linear optimization procedure, and validated using data from Chicago, Illinois by comparing model predictions against the National Transit Database (NTD) estimates. The results demonstrate that regenerative braking efficiency varies as an exponential function of the deceleration level, rather than an average constant as assumed in previous studies. The model predictions are demonstrated to be consistent with the NTD estimates, producing a predicted error of 1.87% and -2.31%. The paper demonstrates that energy recovery reduces the overall power consumption by 20% for the tested Chicago route. Furthermore, the paper demonstrates that the proposed modeling approach is able to capture energy consumption differences associated with train, route and operational parameters, and thus is applicable for project-level analysis. The model can be easily implemented in traffic simulation software, used in smartphone applications and eco-transit programs given its fast execution time and easy integration in complex frameworks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Self-consumption for energy communities in Spain: A regional analysis under the new legal framework

European climate polices acknowledge the role that energy communities can play in the energy transition. Self-consumption installations shared among those living in the same building are a good example of such energy communities. In this work, a regional analysis of optimal self-consumption installations under the new legal framework recently passed in Spain is performed. Results show that the optimal sizing of the installation leads to economic savings for self-consumers in all the territory, for both options with and without remuneration for energy surplus. A sensitivity analysis on technology costs revealed that batteries still require noticeably cost reductions to be cost-effective in a behind the meter self-consumption environment. In addition, solar compensation mechanisms make batteries less attractive in a scenario of low PV costs, since feeding PV surplus into the grid, yet less efficient, becomes more cost-effective. Furthermore, an improvement for the energy surplus remuneration policy in the context of the current legislation was proposed and analysed. It consists in the inclusion of the economic value of the avoided power losses in the remuneration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Minimizing Energy Consumption from Connected Signalized Intersections by Reinforcement Learning

Explicit energy minimization objectives are often discouraged in signal optimization algorithms due to its negative impact on mobility performance. One potential direction to solve this problem is to provide a balanced objective function to achieve desired mobility with minimized energy consumption. This research developed a reinforcement learning (RL) based control with reward functions considering energy and mobility in a joint manner-a penalty function is introduced for number of stops. Further, we proposed a clustering-based technique to make the state-space finite which is critical for a tractable implementation of the RL algorithm. We implemented the algorithm in a calibrated NG-SIM network within a traffic micro-simulator-PTV VISSIM. With sole focus on energy, we report 47% reduction in energy consumption when compared with existing signal control schemes, however causing a 65.6% increase in system travel time. In contrast, the control strategy focusing on energy minimization with penalty for stops yields 6.7% reduction in energy consumption with 27% increase in system travel time. The developed RL algorithm with a flexible penalty function in the reward will achieve desired energy goals for a network of signalized intersections without compromising on the mobility performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗