Lower Total Energy Consumption Research Articles

Assessing the Influence of Occupancy Factors on Energy Performance in US Small Office Buildings

Office buildings are responsible for about 35% of the total electricity in the US and over 70% of building energy consumption occurs during occupancy periods. Therefore, understanding occupancy behavior is crucial for reducing building energy consumption. However, given the stochastic nature of occupant behavior, identifying which occupancy parameters have the most impact on energy consumption poses a considerable challenge. This study aims to investigate and quantify the impact of various occupancy parameters on the energy performance of a US small-sized office building using an EnergyPlus-based nationwide energy simulation. First, dynamic occupancy schedules are created based on different occupancy parameters using an agent-based model. Next, the generated dynamic occupancy schedules are integrated into a small office building model from the Department of Energy’s prototypes. This creates a dataset of occupancy parameters and building energy performance across various climate zones. Finally, various feature selection and statistical analysis methods are applied to the generated dataset. This helps identify significant occupancy parameters and quantify their impact on building energy performance across different climate zones. According to the results of the study, buildings located in cool marine, mixed marine, and warm marine climate zones had lower total energy consumption compared to other zones. Additionally, feature selection methods identified “Occupant Density” as the primary significant variable impacting energy consumption, across all climate zones. These findings offer valuable insights into the influential occupancy parameters across various climate zones, highlighting the importance of tailoring occupancy schedules to enhance energy efficiency. They provide practical guidance that can be directly applied to optimize energy consumption and achieve significant energy savings in small office settings with different weather conditions.

Design and multiperformance evaluation of the ternary azeotrope separation process via extractive distillation based on different extractants

Resource utilization and sustainable wastewater treatment have received widespread attention because of their efficient use of energy. In this study, an ethanol (EtOH)/ethyl tert-butyl ether/water ternary azeotropic system was used to explore the separation efficiency of various extractants. The relative volatility, toxicity, and process modeling of extractants were analyzed to provide a theoretical basis and practical guidance for screening the optimal extractant among nine commonly used extractants. Extractive distillation (ED) was optimized for six processes with a focus on total energy consumption (TEC) and total annual cost (TAC). The ED-EtOH process was the most economical, whereas the extractive ED-DMSO process had the lowest TEC. After heat integration (HI) treatment, the TAC and TEC of each process were reduced, among which HI-ED-EtOH and HI-ED-glycerol (GLY) had the best and lowest economy, respectively. Although high-boiling point and high latent heat extractants (such as GLY and EtOH) increase the heat demand and operating costs, their high latent heat characteristics can effectively recycle heat energy during the HI process. The optimal balance between economy and energy consumption was determined through multi objective optimization considering the physical and chemical properties, environmental impact, and adaptability of extractants.

Energy Performance of Zeolite-Based Drying Bead Desiccants Used to Dry Paddy Rice.

This study utilizes differential scanning calorimetry and thermogravimetric analysis to assess the total energy required to regenerate saturated zeolite-based drying beads (DBs) used to dry paddy rice. We quantify the required heat energy for DB regeneration by calculating the area under the curve in a heat flow rate versus time graph, with the end of the regeneration process indicated by stabilization of the DB weight. Our findings suggest that at DB regeneration temperatures ranging from 120 to 350 °C, the process varied from 813 to 22 min, demonstrating that higher temperatures lead to faster regeneration speeds. The total energy used for regeneration showed similar values at 250 and 350 °C, averaging around 2032 and 2136 kJ per kg of dried DB, respectively. Additionally, the study showed that DBs can hold water between 28.7% and 54.4% higher than the manufacturer's specifications, suggesting a reduced quantity of DBs required for effective paddy rice drying. The overall required heat energy for the regeneration process was calculated at 4.86 MJ/kg, with a carbon intensity of approximately 275.61 g of CO2-eq per kg of water removed, resulting in lower values compared to conventional drying methods. The study underscores DB's possibility of lower total energy (thermal and electrical) consumption and greenhouse gas emissions, alongside its flexibility to regenerate with intermittent energy sources.

A hierarchical reinforcement learning approach for energy‐aware service function chain dynamic deployment in IoT

AbstractTraffic volume is increasing dramatically due to the quick development of technologies like online gaming, on‐demand video streaming, and the Internet of Things (IoT). The telecommunications industry's large‐scale expansion is increasing its energy usage and carbon footprint. Given the desire to minimize energy consumption and carbon emissions, one of the most essential concerns of future communication networks is ensuring rigorous performance restrictions of IoT services while improving energy efficiency. In this regard, a convolutional neural network‐based hierarchical reinforcement learning approach is provided to lower total energy consumption and carbon emissions in the dynamic service function chaining situations. This method can more effectively lower energy consumption and carbon emissions when compared to other hierarchical algorithms based on conventional deep neural networks and non‐hierarchical algorithms. The suggested method is tested in three typical complicated networks with different network parameters to show its suitability in different network scenarios.

Energy saving performance analysis for future fifth generation millimetre-wave cellular networks

The deployment of fifth generation (5G) millimetre-wave (mmWave) base stations (BSs) will consume more energy over time due to the limited time available, despite the increasing interest in developing 5G mmWave wireless communication technology. Constructing 5G mmWave cellular network infrastructure can improve energy efficiency, which is a challenge to implement in heterogeneous networks. This paper presents analytical frameworks for monitoring the effectiveness of 5G mmWave cellular networks. Based on the state management of BS, a system model for 2-tier heterogeneous networks is developed, and particle swarm optimization (PSO) is then used to compute the total energy consumption of the heterogeneous networks. Energy consumption was compared and analysed by leveraging state switching and the aggregate delay for three methods: fundamental separation, conventional separation, and a proposed energy-saving method that introduced a sleep state. Simulation shows that the proposed energy-saving method, which is a combination of conventional separation approaches, has the lowest total energy consumption and offers a 9% reduction compared to other related works. The results validate the accuracy of the power usage used in the 5G mmWave cellular network of the proposed method.

Comparison of drying methods for biochemical composition, energy aspects, and color properties of alfalfa hay

AbstractAlfalfa is a crucial feed source for livestock, necessitating proper drying to achieve optimal moisture levels before consumption. This study aims to reveal alfalfa's drying characteristics and quality properties, defined as the queen of feed, by drying it under different drying conditions. Alfalfa samples were dried using different drying techniques: Open-sun, shade, greenhouse, hybrid (microwave-air-convective), air-convective, microwave, and freeze-drying. The influence of drying techniques on the drying kinetics, energy aspects, biochemical properties, mineral composition, fatty acids, carotene, and color attributes of alfalfa were investigated. Present findings revealed that shade and high-temperature drying conditions increased the crude fiber content (23.18%) of alfalfa samples. The highest protein values were found in open-sun drying (22.01%) and 60 °C air-convective drying (22.10%). The highest values for mineral composition were determined in freeze drying, and the greatest Zn (33.68 ppm) and Fe (135.45 ppm) contents were determined in 100 °C air-convective drying. The highest saturated fatty acids open-sun (21.27%) and freeze dryer (21.07%), unsaturated fatty acids at 60 °C (84.51%) and 80 °C (84.26%), poly unsaturated fatty acids at 60 °C (78.36%), 80 °C (78.14%) and 100 °C (77.74%) were obtained. The drying kinetics of alfalfa were best modeled with the Jena&Das, and in terms of a* (greenness) values, the hybrid drying yielded the best results. The lowest total energy consumption (54.00 kWh) was seen in 200W + 80 °C hybrid drying and the highest (324.72 kWh) in 100 °C air-convective drying. The color attributes and energy consumption findings showed that hybrid drying could efficiently be used for alfalfa drying. In addition, freeze drying was determined to be the best drying method in terms of nutrient preservation.

Can We Talk about Degrowth, Yet?

Degrowth entails the downscaling of material and energy throughput of high-income societies in order to mitigate the metabolic rift between geographies of capital accumulation and the vast territories and populations whose resources they unsustainably consume. It calls for a convergence between “imperial modes of living” and regimes of structural scarcity, and for the need to lower total global energy consumption while reducing gradients of inequality. This article posits the architectural design studio as a significant pedagogical space for exercising a close accountability of energy and material flows as a practice of resource management that demands negotiating the physical limits to growth with distributional social justice.

Daylight and energy performance of side lighting systems in an office room in a subtropical climate

In office buildings, daylight is an important natural resource, as it is profusely available during occupied hours. However, its use can increase energy consumption for air conditioning. Therefore, combining this resource with side lighting systems and promoting its integration with electric lighting is essential to obtain an energy balance. This paper aims to analyze daylight performance and the energy consumption for lighting and air conditioning considering four types of glazing, four orientations, from window-to-wall ratios varying between 40% to 100% for bare and shaded window models in an office room located in a subtropical city in southern Brazil. The methodology was based on Useful Daylight Illuminance levels of 500 to 2,500 lx, Daylight Autonomy levels of 500 lx, and total energy consumption through simulation in DesignBuilder software. The results showed that L13 glazing is not recommended for bare and shaded windows, regardless of window orientation. M76 presented the best performance for energy consumption for West shaded windows. For the West, shading is necessary irrespective of the glazing type (except L13, whose best performance is for bare windows) from WWR 50%. M76 and M52 had the lowest total energy consumption. The findings of this study add to an understanding of the energy savings and lighting performance of different types of glazing, combined with window apertures, and solar orientations for a subtropical climate. Furthermore, the study shows that the choice of glazing depends not only on the presence of shading but also on the orientation and WWR, without a linear behavior.

Food Consumption and Weight Recurrence in Patients Undergoing Bariatric Surgery with a Minimum of 2 Years Post-surgery.

Eating habits are one of the factors that directly affect weight recurrence after bariatric surgery, and therefore, this study assessed the association between food consumption and weight recurrence in patients who underwent bariatric surgery a minimum of 2 years. A cross-sectional observational study was conducted with patients who underwent bariatric surgery a minimum of 2 years through SUS, in the city of Palmas, Tocantins. Food consumption was assessed through two 24-h dietary recalls (R24). The foods were classified into groups by degree of processing following the NOVA classification system. Also, macronutrients and fiber contents were quantified. Anthropometric variables were evaluated and weight recurrence (WR) was defined as 15%. Ninety-three (93) patients participated in the study, being 83.9% female, with mean age of 43.5 ± 9.13 years, mean post-surgery time of 4 years, and 58% present WR. A lower total energy consumption was found in patients without WR compared to those with WR (p = 0.05). Among the WR group, calories from processed foods (p = 0.00) and culinary ingredients (p = 0.05) were higher. However, carbohydrate consumption (percentage) was lower in the WR group (p = 0.04). A positive correlation was found between total energy (p = 0.03), processed foods (p = 0.03) and weight recurrence (p = 0.03). Weight recurrence is associated with total daily energy intake, carbohydrates and food groups classified according to NOVA.

Effects of microwave dryers on the properties of Jerusalem artichoke: physico-chemical, thermo-physical, energy consumption

Effects of pretreatments and drying methods on physico-chemical, thermo-physical, energy values were investigated. The longest drying duration was seen in control samples dried in hybrid microwave dryer at 350 W + 50 °C and the shortest in citric acid-treated samples dried in temperature-controlled microwave dryer. Citric acid-treated samples dried in temperature-controlled microwave dryer at 70 °C had the closest color values to fresh ones. Effective diffusion values of dried Jerusalem artichoke samples varied between 4.66 x 10−8 − 1.33 x 10−7 m2 s−1 and activation energy values varied between 14.53 − 41.74 kJ mol−1. Drying date was estimated with the Midilli-Küçük model. The highest specific heat, thermal conductivity and thermal diffusivity values were observed in control samples dried in temperature-controlled microwave oven at 60 °C and the highest density values were seen in citric acid-treated samples dried in hybrid microwave oven at 70 °C. The highest SMER value was observed in control samples dried in temperature-controlled microwave dryer at 60 °C. The lowest SEC value was seen in control samples dried in temperature-controlled microwave dryer at 60 °C. The lowest total energy consumption was encountered in citric acid-treated samples dried in temperature-controlled microwave dryer at 70 °C.

A modified beluga whale optimization for optimizing energy-efficient no-idle permutation flow shop scheduling problem

Attention to energy-efficient permutation flow shop scheduling problems is increasing in the context of globalization and environmental awareness. However, the energy-efficient no-idle permutation flow shop scheduling problem (NIPFSP) has rarely been studied. This study proposes a procedure using Beluga Whale Optimization (BWO) to solve the energy-efficient NIPFSP issue to reduce total energy consumption (TEC). The offered procedure is tested using four job and machine variations and compared with the PSO algorithm. An independent sample t-test was performed to test the optimization results of the BWO and PSO in 4 cases. The results indicate that the offered procedure produces lower total energy consumption than the PSO algorithm. In addition, the algorithm also provides more competitive results when solving the energy-efficient NIPFSP problem with a larger number of jobs. The implications of this academic research show that the proposed procedure can be applied to solve the problem of energy-efficient NIPFSP, which is indicated by low energy consumption.

A chemically enhanced backwash model for predicting the instantaneous transmembrane pressure of flat sheet membranes in constant flow rate mode

In this study, a new model was proposed based on the cascade process of the chemical reaction and the physical removal mechanism to predict the instantaneous transmembrane pressure (p(t)) of yeast-fouled 0.1 μm polyacrylonitrile (PAN) membranes in the chemically enhanced backwash (CEB) process. The results indicated that the model predictions were in good agreement with the experimental data. Additionally, the transition point of the CEB mechanism, which changed from a combined cleaning (pore cleaning and cake cleaning) mechanism to an individual cake cleaning mechanism, appeared earlier at higher NaOCl concentrations or CEB fluxes. The corresponding available membrane area ratio also tended to stabilise earlier. In addition, the model predictions for different suspensions or solutions, membranes (0.1 μm polyethersulfone (PES) and polyvinylidene fluoride (PVDF) membranes), and chemical reagents were also in good agreement with the experimental data. Moreover, the integral of p(t) was used to correct Masse's energy consumption equation. The results show that the calculation method for the corrected equation is theoretically more accurate. Lower total energy consumption was obtained at a higher NaOCl concentration or lower CEB flux.

Distributed total-amount optimal coordinated control of multi-motors with input and output saturation

Specific to the double saturation constraints of input and output in multimotor network systems, an anti-windup control framework with distributed total-amount optimal coordination is constructed, and a new saturated super-twisting sliding mode control strategy is designed in this paper. First, a mathematical model of direct torque and flux control of a multipermanent magnet synchronous motor is established. Next, the consistency of the total amount and output saturation are taken as the constraint conditions. Considering the lowest total energy consumption, the optimal multi-axis total-amount coordinated allocation algorithm is designed on the basis of the Karush-Kuhn-Tucker (KKT) condition. Then, the input saturation is introduced into the dynamic integral part of the super-twisting algorithm. A new saturated super-twisting sliding mode tracking control algorithm is designed, and the barrier Lyapunov function is used to prove the input constraint. Finally, the Matlab/Simulink simulation and RT-LAB semi-physical experiments verify that the anti-windup control strategy of distributed total-amount optimal coordination can effectively solve the double saturation constraints of input and output.

Development and Simulation of Natural Gas Refining Mechanism Based on Exergy Study

Abstract: This study will examine a domestic gas field in Bayelsa, Nigeria, to improve the natural gas purification process. This study's main goals are to reduce energy use and improve purification levels. A complete technical and economic assessment was carried out utilizing Aspen Plus TM software. The absorption parameters reflux ratio and stage number were estimated using single-factor sensitivity analysis. The energy system's energy-saving technique was used to examine the heat transfer mechanism and recommend a change. The optimization results show that the suggested system has better purifying performance, lower total energy consumption, and 9 percent improved energy efficiency.

A digital twin-based multi-objective optimization method for technical schemes in process industry

ABSTRACT To solve problems of technical objective conflicts, untimely feedback, and inaccurate decision making, a multi-objective optimization method was developed for technical schemes in process industry based on digital twin. According to actual requirements, a multi-objective optimization problem was established with key technical parameters and constraints determined. A digital twin model was built to achieve a real-time interaction between physical and virtual production systems and assist in optimization. For optimization efficiency and adaptability to different working conditions, a dynamic acquisition function-based Bayesian method was adopted to fit original complicated functions and obtain Pareto optimal solutions. A rapid decision-making was carried out by comprehensively utilizing dynamic parameter set correlation evaluation, entropy weight method, and technique for order preference by similarity to ideal solution. A typical case study of optical fiber preform drawing process was presented to prove the method effectiveness. Results demonstrated that the proposed method was valuable for actual application with better product quality (an improvement by 0.71% for preform rod diameter precision control), higher utilization rate of raw materials (an increase by 3.64%), and lower total energy consumption (a reduction by 4.37%).

Effect of the Surface Treatment Process of Filter Bags on the Performance of Hybrid Electrostatic Precipitators and Bag Filters

Hybrid electrostatic precipitators consisting of electrostatic precipitation (ESP) and a bag filter are potential devices for ultralow emissions. The ESP captures and charges the particles; subsequently, the charged particles that escape enter the bag filter. The charged particles can cause the electric field of the filter bag to develop, thereby enhancing the filtration efficiency due to the force of the electric field. Experiments based on the coupling-reinforced electrostatic–fabric integrated precipitator system were conducted to investigate the outlet total dust concentration, dust removal efficiency, pressure drop, energy consumption of bag filter, and hybrid electrostatic precipitators with various filter bags. The measured results demonstrate that the removal performance of filter bags with smaller fiber diameters was superior. However, the pressure drop and energy consumption were high due to the increased filtration resistance. Compared to bag filters, hybrid electrostatic precipitators had lower total and grade dust mass concentrations at the outlet, higher total and grade dust removal efficiencies, a minor average pressure drop variation per minute, and lower total energy consumption. Consequently, the quality factor was utilized to comprehensively evaluate the overall performance of dust collectors. The hybrid electrostatic precipitators had a significant greater quality factor; their overall performance was superior to that of bag filters. Overall, a smaller filter bag’s fiber diameter resulted in more effective dust removal capabilities. Hybrid electrostatic precipitators with various filter bags were significantly better than bag filters in terms of dust removal performance, cycle life, and energy consumption.

Multi-objective analysis of evacuated tube solar-electric hybrid drying setup for drying lotus bee pollen

This work aims to develop an evacuated tube solar-electric hybrid drying setup and enhance its performance using evacuated collector and photovoltaic systems. The setup performance was evaluated by dehydration of lotus bee pollen using two different strategies inducing solar heating drying and mixed heating drying at three different temperatures (40, 50, and 60 °C). The system was also compared with open sun drying. Compared with open sun drying, about 45%, 23%, 30%, and 41% reduction in the process time was induced by solar heating drying and mixed heating drying (40, 50, and 60 °C), respectively. For both solar heating and mixed heating drying, the mechanical energy, thermal energy generated by electric heating tubes, and radiation thermal energy accounted for were in the range of 12.2–38.5%, 0.0–15.3%, and 60.5–87.8%, respectively. From the perspective of drying efficiency and energy consumption, the developed evacuated tube solar-electric hybrid drying setup was more beneficial under mixed heating drying at 40 and 50 °C. The dryer efficiencies under the cases of mixed heating drying at 40, 50 °C were 48% and 34% higher than that of solar heating drying, while mixed heating drying had lower total energy consumption, specific energy consumption and specific electric energy consumption. The developed equipment can effectively reduce greenhouse gas emissions and has a short payback period of 1.24 years. Based on the findings of this research, it could be concluded that, resulting in decreased drying time, GHG emissions and enhanced energy efficiency, the developed equipment is a promising drying technology.

Augmentation of natural convection heat transfer in enclosures via ultrasound: Effects of power, frequency and temperature

• Ultrasonication improves convective heat transfer in enclosures by as much as 77%. • Effect of ultrasonic power heightens at higher frequencies. • Acoustic streaming observed to contribute the most to the observed enhancement. • Per unit ultrasonic power, the observed enhancement is proportional to frequency. • Only at higher frequencies, integration of ultrasound results in energy-saving. The integration of ultrasound to enhance the natural convection heat transfer in an enclosure was experimentally investigated. The effects of ultrasonic power, ultrasonic frequency and surface temperature on convective heat transfer coefficient were analyzed to optimize the ultrasonic input. A novel dimensionless number is defined that indicates the ultrasound-induced convective heat transfer enhancement per added unit of delivered ultrasonic power. To determine and justify the effectiveness of incorporating ultrasound from an energy-savings point of view, the total energy to the system to increase the temperature to a certain degree in non-ultrasonic and ultrasound-assisted experiments was compared. With respect to ultrasonic power, application of ultrasound at any power level enhances the convective heat transfer coefficient by as much as 77% while the effect of power heightens with an increase in frequency. Amongst the three examined frequencies, integration of ultrasound was observed to enhance heat transfer more at higher frequencies. The surface temperature appears to have a negative effect on the observed ultrasound-enhanced heat transfer where higher temperatures abate the enhancement. Per unit ultrasonic power added to the system, higher frequencies show greater improvement in convective heat transfer. Comparing the trends in variation of the augmented heat transfer, the kinematic momentum resulting from acoustic streaming and the acoustic cavitation critical bubble radius with the ultrasonic frequency revealed that at lower frequencies acoustic cavitation is the augmenting mechanism and at higher frequencies acoustic streaming induces the enhancement with acoustic streaming having a higher impact in augmenting natural convection heat transfer. In terms of energy savings, a novel analysis focusing on the energy intensity of utilizing ultrasound unveiled that only at higher frequencies does integration of ultrasound result in lower total energy consumption.

Effects of Tool-Workpiece Friction Condition on Energy Consumption during Piercing Phase of Seamless Tube Production

During the hot piercing phase of seamless tube production, friction and contact conditions between tools and workpiece significantly influence final product quality and energy consumption. The friction effects on the production of high alloyed steels like Super Cr13 steel are critical. This study analyses the effect of different friction conditions at the workpiece-tool interface in the piercing of Super Cr13 steel bars to minimize total energy consumption in such a manufacturing process. For this purpose, a three-dimensional finite element method (FEM) is employed to simulate and analyze the piercing process. The variety of tools (plunge, rollers, and Diescher disks) and contact conditions lead to differences in the applied stress at different workpiece areas. Consequently, various friction models and friction coefficients were selected for different interfaces. The relation between strain rate, temperature, and geometry of pierced tube are discussed, and the selected friction relation with total power and energy consumption is presented. Experimental tests have been used for FEM validation and result analysis, and finally, the most effective conditions with lower total energy consumption are presented.

Latency-aware computation offloading and DQN-based resource allocation approaches in SDN-enabled MEC

The proposed mobile edge computing can transfer the computing tasks in mobile applications to the nearby edge devices, effectively reducing the processing pressure of local servers and avoiding delays in backhaul and core networks, thus better solving the problem that cloud computing cannot effectively handle resource allocation. However, the complexity of the wireless environment during the communication process leads to the fact that the computing tasks are easily caused by the increase in the number of traffic and packet loss when they are uploaded to the MEC side through the wireless link, which cannot guarantee a lower total system energy consumption and shorter total delay. To address the problem that mobile devices cannot handle many computationally intensive tasks in a timely manner, this paper proposes a task offloading optimization scheme for SDN-enabled MEC environments. Modeling the computation offloading problem based on Lyapunov optimization, and then analyzes the offloading delay with respect to the offloading gain. In order to guarantee application requirements, minimize energy consumption and latency, and better satisfy user QoS requests, this paper proposes a resource allocation strategy based on deep reinforcement learning. The strategy designs a DQN-based resource allocation algorithm to deploy a joint optimal offloading decision and resource allocation scheme in a mobile edge computing environment under the limited computational resources and the latency constraints of the computational tasks. Based on the experimental results, it is shown that the proposed task offloading strategy can reduce the overall latency; the proposed resource allocation strategy can reduce the total energy consumption and total latency of the system and improve the successful execution rate of tasks.