Evaluation Of Energy Consumption Research Articles

University-Campus-Based Zero-Carbon Action Plans for Accelerating the Zero-Carbon City Transition

After three decades of global climate initiatives, local governments’ capabilities to implement policies and solutions have not always been effective in making the urban environment more resilient and adaptive to climate change. All the previous climatic initiatives and decisions were mostly carried out by governments or affiliated actors on global or regional scales. However, the lack of notable climate actions at the community level is evident in the current crisis of urban sustainability. To drive a radical change toward a zero-carbon transition at the city scale, massive decarbonization is required at the institutional level (academic/nonacademic campus) of a city. Among all the nongovernmental actors, it is always expected that Higher Education Institutes (HEIs) would take the lead in promoting a resilient and sustainable future for the cities through their education, research, and innovation. HEIs’ multidimensional activity resembles the “small scale model of a city” interacting with different subsystems like education, administration, transport, housing, health, etc. However, the present studies were found to be mostly based on specific regions and developed countries. In addition, the previously developed methods of assessing energy consumption and CO2 emissions at the university level lack adaptability for other countries and urban settings. Following the need for a comprehensive method of evaluating energy consumption and accelerating the zero-carbon practice to a broader scale, a new framework is proposed here for a university campus. It can be implemented regardless of the campus type and geographic and weather conditions. After implementing the evaluation methods on a 753-acre campus of Rajshahi University, the campus typology and natural resources were identified. Following that, the behavior patterns of the users in terms of energy usage and waste generation were also determined. Finally, the results show that 1900.71 tons of CO2 was emitted in the academic year 2022. The per-capita CO2 emission was 0.041 tons of CO2. To boost the zero-carbon city transition, three core parameters of scaling-up methods were taken into consideration to evaluate the benefits of zero-carbon campuses. The scalability of the zero-carbon practices was evaluated based on the ideas of (1) expansion—how educating future generations about the environment can have a long-lasting impact, (2) demonstration—adopting innovative practical and technological solutions to exhibit the benefits of zero-carbon practices to society, and (3) collaboration—building strong alliances with state and nonstate actors of the city to promote sustainability through sharing knowledge, innovation, and technology.

Micro-Factors-Aware Scheduling of Multiple Autonomous Trucks in Open-Pit Mining via Enhanced Metaheuristics

Traditional open-pit mineral transportation systems are typically subject to manual command, frequently leading to vehicular delays and traffic congestion. With the advancement of automation and electrification technologies, this study proposes a highly accurate scheduling method for multiple autonomous trucks in an open-pit mine. This model considers micro-level temporal and spatial factors to tackle the task of scheduling autonomous trucks within open-pit mines. The cost function of the concerned scheduling problem is a comprehensive evaluation of energy consumption, time, and output. Beyond the loading and unloading activities, the model also factors in the charging requirements of autonomous trucks in mining regions. The scheduling model integrates a Voronoi diagram search and optimal spatial path time matching, aiming to provide superior mission planning and decision-making solutions for autonomous trucks in mining regions. For an efficient solution to the scheduling problem, we propose an improved-evolution artificial bee colony (IE-ABC) algorithm. This algorithm improves the global search and re-initialization processes and conducts algorithm ablation experiments to closely examine their impact on optimization. Simulation results across various algorithms, cost function definition strategy, and encoding strategy show that our method can improve scheduling performance in energy consumption and time. Experimental results demonstrate that the proposed model and algorithm can effectively solve the scheduling decision-making problem in an unmanned open-pit mine.

Adaptive neural control of microgravity active vibration isolation system subject to output constraint and unexpected disturbance

The objective of this investigation is to explore the issue of microgravity vibration isolation control within a space station, while considering constraints on output and unexpected disturbances. Drawing upon an analysis of the environment and operating conditions within the space station, the uncertainties resulting from variable payloads and unforeseen disturbances are depicted as combined disturbances. On this basis, an actor–critic neural network with energy consumption evaluation is used to estimate the combined disturbances and devise strategies for compensatory control. Furthermore, an adaptive robust term is devised to handle errors generated by the estimation process of the neural network. Additionally, to ensure that the output of the isolation system remains within specified bounds, an improved predefined performance function is introduced, thereby ensuring adherence to constraints regardless of initial conditions. Simulations conducted under different operational scenarios demonstrate the effectiveness of the proposed controller in achieving system stability. The results indicate a remarkable suppression of onboard vibration amplitude, amounting to approximately 60 dB within the frequency range of 2 to 100 Hz.

Comparative evaluation of greenhouse gas emissions and specific energy consumption of different drying techniques in pear slices

AbstractIn recent years, global warming, climate change, and carbon emissions have emerged due to the uncontrolled use of fossil fuels and the lack of widespread use of renewable energy sources on a global scale. This research investigated specific energy consumption (SEC) and greenhouse gases (GHG) emissions (carbon dioxide [CO2] and nitrogen oxides [NOX]) during the drying of pear samples by five different types of dryers, namely, convective (CV), infrared (IR), microwave (MW), combined IR/CV, and MW/CV. Moreover, the quality properties of dried pears, such as shrinkage, rehydration (RR), and color change were determined. The results showed that the highest shrinkage (72.53%) and color change (ΔE = 33.41) values were obtained in CV drying at 50 °C and thickness of 2 mm and IR dryer 1000 W and thickness of 6 mm, respectively. The greatest rehydration rate (4.25) was also determined in MW/CV drying at 450 W and an air temperature of 60 °C. The lowest SEC was observed for the MW/CV dryer with a power of 630 W and air temperature 70 °C (20.25 MJ/kg), while the highest SEC (267.61 MJ/kg) was obtained in the CV drying (50 °C, sample thickness of 6 mm). The highest CO2 and NOX emissions (GT-GO power plant) were 280.45 and 1.55 kg/kg water in the CV dryer at 50 °C and a thickness of 6 mm. In conclusion, the increases in IR and MW power and temperatures led to reduced CO2 and NOX emissions, while the increases in sample thickness led to increase CO2 and NOX emissions.

Heat transfer characterization with alternative heating element layout in electric ‘Injera’ baking technology

The quantitative understanding of the heat transfer mechanism of injera baking technology is critical to evaluate energy consumption, cooking time, and thermal loss of the technology. However, the impact of the heating element layout on the heat transfer process has not been studied. Here, this paper studies four heating element layout arrangements consisting of a fixed power input with a varying power density as a function of layout design to investigate wiring layout impact on product performance. The conduction heat transfer of each heating element layout modelled using transient finite element simulation. Results indicate that higher power density bear a strong, positive correlation with startup time, which showed a 13% better performance when compared with the benchmark. The temperature distribution, however, incurs a 32% higher deviation. Whereas the model with the least favourable startup time shows a threefold higher performance than the benchmark. The results show wiring layout has influence over the key performance parameter of the technology.

Preparing microcrystalline cellulose‐reinforced polylactic acid composites by an energy saving method

AbstractMicrocrystalline cellulose (MCC) fibers are co mmonly used to reinforce polymers; however, their freeze‐drying process consumes a lot of energy. In this study, MCC dried at different temperatures, oven‐dried at 25, 50, 75, and 103°C and freeze‐dried, was evaluated based on their effect on the reinforced composites. The dried MCC was compounded with polylactic acid (PLA) by melt extrusion and compressed into an MCC/PLA composite film. The morphology, structure, and crystallinity of the dried MCCs and MCC/PLA composites were analyzed using scanning electron microscopy, laser particle size analysis, x‐ray diffraction, mechanical testing, and Fourier transform infrared spectroscopy. It was proved that MCC dried at 103°C was more uniformly dispersed and tightly bound to the PLA matrix than freeze‐dried MCC. Tensile measurements showed that the MCC dried at 103°C had nearly the same tensile strength (58.35 MPa) as that of the freeze‐dried MCC (58.7 MPa) and was higher than that of the other oven‐dried MCC. Energy consumption evaluation revealed that oven‐drying consumed much less energy than freeze‐drying MCC for 24 h to obtain the same final moisture content. MCC dried at 103°C has significantly better properties than MCC dried at 25, 50, and 75°C, similar to freeze‐drying. Concerning performance and energy consumption, drying at 103°C is determined the optimal choice to support the preparation of MCC‐reinforced PLA composites.Highlights Drying temperature effects aggregation of MCC. MCC Dried at 103°C can present similar properties to freeze‐dried MCC but save more energy. Oven‐drying can be a good way to dry MCC for the preparation of MCC/PLA composite.

Prediction of building energy performance using mathematical gene-expression programming for a selected region of dry-summer climate

Developing energy-efficient buildings considering building design parameters can help reduce buildings' energy consumption. The energy efficiency of residential buildings is considered a top priority for the energy policies of a country. Thus, this study utilizes gene-expression programming (GEP) to estimate the energy performance of residential buildings. The energy consumption evaluations were carried out using the Etotect energy simulation software. Eight building parameters with 768 data points were considered to generate the database for the heating load (HL) and cooling load (CL), including relative compactness, surface area, wall area, roof area, overall building height, glazing orientation, glazing area, and distribution of glazing area. Different GEP predictive models with varying parameters for building HL and CL were developed, and the best-performing prediction model was selected. In addition, several statistical indices were utilized to measure the accuracy of the proposed GEP models. The results revealed that GEP14 gives the most robust prediction model for HL having R2-value greater than 0.9 for both the training and validation set. Likewise, R2-value >0.9 is achieved for best- CL (GEP11). Furthermore, the mean absolute error (MAE) values for both the predictive HL’ and CL’ by prediction models were relatively less for both the training and testing databases. The sensitivity and parametric analysis reveal that the overall height (Ho), roof area (Af), and glazing area (Ag) were the most influential parameters for both predictive models. Thus, GEP results demonstrate the robust performance in predicting the building energy.

Turbidity Removal from a Model Solution by Continuous Mode Electrocoagulation and Evaluation of Energy Consumption

The purpose of the research has been the construction of a new electrocoagulation (EC) equipment and its technical evaluation in the treatment of a model solution with a high level of turbidity. The EC system contains six cells installed in series, coupled to a flocculator and a clarifier (sludge decanter), each cell unit is composed of a cylindrical aluminum (Al) anode and a solid stainless-steel rod as cathode in connection with a DC power supply, the aluminum anodes are replaced by iron (Fe) according to the proposed tests. The influence of two factors, such as the applied electric potential and the type of electrode used, on turbidity removal performance, total dissolved solids (TDS) and electrical energy consumption were examined. The tests were carried out using a two-factor factorial design, electrical potential at (0, 3, 6 and 9 V) and type of anode (aluminum and iron). The investigation of the operating parameters was carried out in continuous mode. The initial turbidity of the water to be treated was set at 84.5 NTU, a value generally found in surface water. The results showed that the best conditions for turbidity removal were at an electrical potential of nine volts reaching a removal of 82.29 % and an energy consumption for aluminum electrodes of 0.7142 kWh/m3. It is also observed that the value of total dissolved solids after treatment is still slightly high. In conclusion, electrocoagulation with Al/steel electrodes proved to be an appropriate technology for water treatment due to its turbidity removal efficiency and low electrical energy consumption.

基于能耗最优的改进动态窗口法的电动拖拉机避障方法

In order to solve the real-time obstacle avoidance problem in electric tractor operation, an improved dynamic window approach (DWA) based on optimal energy consumption is proposed for electric tractor obstacle avoidance. Firstly, energy consumption model of tractor is established based on the transmission system of electric tractor, then energy consumption evaluation sub-function is introduced to improve the evaluation function of original DWA algorithm, and finally, the trajectory is evaluated and the optimal solution of the trajectory is determined by using new evaluation function. Based on the kinematics model of YL254ET electric tractor in Yancheng Yueda, a model predictive controller is designed. The obstacle avoidance planning and tracking control of electric tractor are simulated jointly on Simulink and CarSim simulation platform. Finally, the obstacle avoidance planning test is carried out. The simulation and experimental results show that after the algorithm improvement, the energy consumption of electric tractors is reduced, the generated path is smoother, and the lateral error is smaller.

An SRN-based model for quantitative evaluation of IoT quality attributes

Today, the Internet of things (IoT) is widely used in various fields, including health control, smart cities, intelligent buildings, and so on. One of the severe concerns in IoT systems is the issue of energy consumption and its management. IoT systems have limited energy resources, and in this regard, these limited resources must be managed appropriately. To design and build IoT systems, various aspects such as usable chips, types of communication protocols, timing of sending and receiving data, and so on, directly affect the system's energy consumption. Therefore, it is necessary to model and evaluate the energy consumption of IoT systems before building and implementing the system. Using an appropriate model makes it possible to investigate and understand how much the system consumes energy and how it is in conformity with the system's demands. This paper presents a stochastic reward net (SRN)-based model for modeling and quantitative evaluation of system energy consumption. To solve and evaluate the model, the proposed model is converted into an SRN model based on a series of automatic transformations. The proposed model is used in a case study to show how the model works and the results are given in the paper.

Evaluation of energy consumption in mobile ad hoc network routing protocols

Rapidly evolving wireless network technology continues to be one of the focal points in academic research. Mobile Ad hoc Networks (MANETs) consist of mobile nodes and the efficient transmission of data among these nodes is crucial for the network's operation. In this study, four of the most common routing protocols, namely AODV(Ad Hoc On-Demand Distance Vector), DSR(Dynamic Source Routing), OLSR(Optimized Link State Routing), and DSDV(Destination-Sequenced Distance Vector) were evaluated using different scenarios in the NS-2 simulation environment. As known, the lifetime of a wireless network is proportional to the battery limits of its nodes. Therefore, the choice of routing protocol for mobile ad hoc networks is critical for the network's lifetime. In this study, the energy consumption of the aforementioned routing protocols was analyzed under different conditions, and it was concluded that table-driven routing protocols, especially DSDV, demonstrated the best energy performance in various scenarios.

Evaluation of energy consumption and motion accuracy for underwater gliders based on quadrant analysis

Underwater gliders are well known as a type of enduring platform for underwater exploration; nevertheless, they have also been criticised in terms of their compromised course-keeping capability, particularly in harsh ocean environments. A motion controller that can improve motion accuracy while maintaining a low energy demand is preferred by developers and operators. In this paper, a motion controller based on a combined feedforward and Linear Quadratic Regulator (LQR) control is proposed. The controller has been evaluated in terms of energy consumption and motion accuracy with a fully coupled numerical model integrating the vehicle dynamics, the energy consumption and the control system. A energy-accuracy chart and a quadrant analysis are then introduced to support the analysis of the controller performance and the identification of the optimum operating conditions. Based on the prototype underwater glider that has been developed at Tianjin University, various case studies in different ocean environmental conditions are performed. The results show that the method proposed can quantitatively evaluate the performance of the vehicle to effectively achieve the balance between energy consumption and motion accuracy which can support the decision-making process for the best operation strategy.

Heat loss optimization and economic evaluation of a new fourth generation district heating triple pipe system

In response to the heat loss caused by the temperature difference between the heating pipes and external environment during the pipe transportation, heat contradiction between the total heat loss of the piping system and heat transfer between tubes, as well as economic balance between the cost of heat loss and cost of material loss. Based on TOTS (Two-supply/One-return, triple pipe structure) heat loss theory of the fourth-generation district heating system, this paper optimizes structure of pipes by setting dimensionless characteristic parameters θ and β. Finally, a mathematical model is proposed to calculate economic efficiency of pipeline network by considering the cost of initial construction material loss and operation heat loss of the pipe. Results show that, from energy perspective, comprehensive heat as system energy consumption evaluation index is positively correlated with θ, decreases first and then increases as β increases. Total heat loss of system dominates comprehensive heat. Lowest comprehensive heat of system is 18.12 w/m for θ of 0.1945 and β of 0.0739. From economic perspective, total system loss cost as system economic evaluation index is positively correlated with both θ and β. Total system heat loss cost dominates total system loss cost. Lowest total system loss cost is $29.39/m for θ of 0.1945 and β of 0.0509.

Investigating spatio-temporal characteristics and influencing factors for green energy consumption in China

The green transformation of energy consumption is beneficial for promoting green development in China. This study constructed a green energy consumption evaluation index system and measured the green energy consumption levels in 30 provinces of China from 2000 to 2019 using the fuzzy comprehensive evaluation method. This study further employed the spatial Durbin model to examine influencing factors and spillover effects of green energy consumption. The results showed that, temporally, China’s green energy consumption levels had a fluctuating upward trend. While, spatially, the overall levels of green energy consumption in China showed apparent characteristics of “high in the west and low in the east”. In terms of influencing factors, environmental regulations played an important role in promoting green energy consumption in the region, while economic development, opening up, and industrial structure had considerably inhibiting effects. Additionally, economic development, opening up, and industrial structure of neighboring regions showed marked positive spillover effects, while urbanization level and technological innovation showed substantial negative spillover effects. The regional heterogeneity test results showed that environmental regulation and industrial structure rationalization were the important factors for promoting green energy consumption in the eastern region, environmental regulation played an important driving role in the central region, and opening to the outside world and technological innovation helped improve the level of green energy consumption in the western region.

Influence of oxalic additive on etidronic acid anodizing of aluminum alloy

The anodizing in etidronic acid (HEDP) and oxalic acid (H2C2O4) mixed electrolytes was conducted. The anodizing parameters were optimized based on the evaluation of energy consumption, growth efficiency, and hardness of PAA film. The results indicate that continuous and uniform PAA films can be fabricated in HEDP/H2C2O4 solutions in any proportion, and both the anodizing voltages and roughnesses of PAA films decreased with the H2C2O4 content. The moderate amount of H2C2O4 could lead to an increase in the formation efficiency of PAA films. The hardness of the PAA film prepared in HEDP/H2C2O4 electrolyte could reach up to ∼660 HV. Moreover, a surface resembling lotus leaves could be formed due to the corrosion of PAA films with sub-micron interpore distance by H2C2O4 during anodizing, and a superhydrophobic surface with a contact angle of ∼153° could be obtained after it was modified via stearic acid.

Analysis and Evaluation of Indoor Environment, Occupant Satisfaction, and Energy Consumption in General Hospital in China

Different functional areas within general hospitals have varying environmental requirements, with relatively high energy consumption. A comprehensive evaluation of the operational performance’s rationality is of great significance in hospitals’ energy conservation efforts. This study conducted an annual post-occupancy evaluation of a general hospital located in a hot summer and cold winter area in east of China. Two hundred and seventy-eight valid online satisfaction questionnaires, sixty valid point-to-point questionnaires, indoor environment data of each typical season, and energy consumption data were obtained. The overall indoor environment of the selected hospital met the standard requirements. The results showed that occupant satisfaction was influenced by gender, working hours, and length of stay. The annual energy consumption level of this building was 84.7 kWh/m2, which is significantly lower than that of other public general hospitals in China and general hospitals in developed countries. The energy consumption of the inpatient department was directly related to the hospital days, with an increase of 12.2 kWh/m2 for every 1000 additional hospital days. A new indoor environment quality (IEQ) model and a new comprehensive evaluation model for energy efficiency were established. Overall, the outpatient department exhibited superior performance compared to the inpatient department. These evaluation models can help owners and decision-makers in the identification of environmental performance in hospitals.

Evaluation of operation cost and energy consumption of ports: comparative study on different container terminal layouts

Automatic container terminals (ACTs) have emerged as the development direction of upgrading and transformation for traditional manual container terminals. A number of terminal layouts are devised and implemented. However, it is the lack of a comprehensive comparison of different container terminal layouts from aspects of operation cost and energy consumption. In view of this, a Time-Driven Activity-Based Costing approach is used to identify the ACT profitability bottlenecks. A multi-agent based simulation model considering four main terminal layouts is established. The multi-level handling of ACTs is simulated and the corresponding operation time and energy consumption are calculated. Simulation results show that automated guided vehicles (AGVs) are the key to improving the cost-effectiveness of ACTs. The cost-effectiveness of ACTs with non-cantilever automated rail-mounted gantries (ARMGs) is more vulnerable than that of ACTs with bilateral cantilever ARMGs. On average, ACTs with bilateral-cantilever ARMGs consume less energy per container task than ACTs with non-cantilever ARMGs. This study provides management insights into resource allocation, layout design, and sustainable development.

Evaluation of energy consumption and environmental impacts of strawberry production in different greenhouse structures using life cycle assessment (LCA) approach

This study employed the Life Cycle Assessment (LCA) to evaluate the environmental impacts of two types of greenhouse structures (Quonset and Spanish) used for strawberry production. The IMPACT World + method was used to quantify environmental impacts for 1 ha of greenhouse (structure and strawberry) as the functional unit. The energy results indicated that the average total energy consumption was 388,898 MJha−1 for Quonset and 658,646 MJha−1 for Spanish structures. Human labor (197,655 MJha−1) and electricity (214,922 MJha−1) were found to have the highest contribution to the total energy consumption in both types of structures. The environmental results showed that the human health index and ecosystem quality were 0.019 and 0.042 DALY.ha−1 and 4592 and 10,169 PDF.m2.yr.ha−1 for Quonset and Spanish structures, respectively. The environmental impacts of Spanish structures were found to be higher than those of Quonset structures due to their higher use of polyethylene and steel. Specifically, the values of climate change (kg CO2eq), fossil-nuclear resources (MJ deprived), and ozone layer depletion (kg CFC-11eq) per hectare were 12,818, 142,109, and 0.002 for Quonset and 30,094, 400,251, and 0.004 for Spanish structures, respectively. The environmental hotspots were identified as chemical fertilizers, electricity, and polyethylene, which had the highest environmental impacts.

Liquified hydrogen vs. liquified renewable methane: Evaluating energy consumption and infrastructure for sustainable fuels

This study aims to assess the energy consumption characteristics of various fuels, namely liquified natural gas, liquefied renewable methane, and liquefied hydrogen from production to overseas transportation, by covering broad color spectra of grey, blue, and green. A quantitative assessment is implemented to calculate how much energy is consumed to produce, store, and transport fuels. Carbon capture scenarios are also considered, along with boil-off gas recovery and utilization options for increased value chain effectiveness. Thereafter, a qualitative assessment is performed to compare the use of fuels from four perspectives: (i) technology, (ii) infrastructure, (iii) scalability, and (iv) regulations. The obtained quantitative results indicate that the energy consumption to produce liquified natural gas, liquefied renewable methane, and liquefied green hydrogen is about 0.49, 31.4, and 62.3 kWhe/kg of fuel, respectively. The energy consumption to store liquified hydrogen in a 2,000 m3 on-land storage tank for one day while recovering 100% of the generated boil-off gas is about 4,840 kWh. Moreover, the qualitative results indicate that the infrastructure is ready, and regulations are available to use liquefied renewable methane as fuel, whereas the infrastructure of liquified hydrogen still needs to be ready, and the associated regulations require amendments.

Evaluation and comparative analysis of the mixed traffic flow on urban roads considering the green cost

Evaluating vehicles’ energy consumption and emissions is significant to ease energy shortages and prevent environmental pollution. This study focuses on evaluating energy consumption and emissions of the mixed traffic flow with human-driven and autonomous vehicles from both economic and environmental perspectives. The proposed Green Cost Model is comprised of the energy consumption models and emissions models, taking energy recovery of electric vehicles and specific power of fuel vehicles into consideration. Based on the Energy, Economic and Environment theory, the fuel price, electricity price and carbon taxation are utilized to analyze the cost of energy usage and emissions. The feasibility and effectiveness of the Green Cost Model are verified by simulations in several typical traffic scenarios. The simulation results indicate the green cost of both fuel powered and electric vehicles. In different scenarios, the electric vehicles have less green cost than fuel vehicles, and the total green cost of the fleet decreases as the penetration of autonomous battery electric vehicles (ABEV) increases. In addition, lower average green cost and higher service level are obtained by taking green cost into account in the intersection timing scheme. Finally, scientific and rational policy implications are put forward for the government, drivers and automakers.