Evaluation Of Energy Consumption Research Articles

Evaluation of Field Performance and Energy Consumption of a Medium-sized Combine Harvester for Harvesting Glutinous Rice in Malaysia

A medium-sized combine harvester has been recently deployed to harvest newly introduced high-value glutinous rice in Malaysia. Thus, efficient utilisation of combine harvesters during harvest is essential to minimise operating costs and grain loss. This study evaluated a medium-sized combine harvester’s performance and energy consumption for harvesting glutinous rice. The experiment was carried out on a one-hectare paddy field with three sub-plots using a central composite design (CCD). A time-motion study was conducted during the harvesting operation to determine the combine harvester’s performance parameters, which included field operating speed (FS), field efficiency (FE), theoretical field capacity (TFC), effective field capacity (EFC), grain throughput capacity (GTC), fuel consumption (FC) and field machine index (MI). The energy expended during the operation, which included machinery energy (ME), fuel energy (FCE), human energy (HE), and total energy (TE) input, were also computed. The average FS, FE, TFC, EFC, FC, and MI values were 2.42 km/h, 59.78%, 0.56 ha/h, 0.33 ha/h, 14.89 l/ha, and 0.30, respectively. The mean values of ME, FCE, HE, and TE were 305.35, 711.69, 3.62, and 1020.66 MJ/ha, respectively. The combine harvester achieved an average grain throughput capacity (GTC) of 1796.91 kg/h, demonstrating its effectiveness in handling glutinous rice harvesting. The average time distribution for the harvesting operation, such as effective harvesting time, turning/reversing time, and unloading time, was 1.85 h/ha, 0.38 h/ha, and 1.05 h/ha, respectively. Based on the results, it is concluded that the medium-sized combine harvester is technically and economically suitable for harvesting glutinous rice.

Fuzzy logic Based Seagull Optimization Algorithm for Efficiency and Security in Wireless Sensor Networks

Wireless sensor networks (WSN) find applications in diverse fields such as environmental monitoring, healthcare, and industrial control systems. The pivotal components of these networks are the sensor nodes, which, unfortunately, consume a substantial amount of energy when transmitting information directly to the base station (BS). To mitigate energy consumption associated with direct transmission, this paper proposes a two-phase approach utilizing hybrid clustering and routing algorithms. The proposed approach incorporates fuzzy and seagull techniques for clustering and adopts optimal CH (cluster head) selection, CBRP (Cluster-Based Routing Protocol), and AES (Advanced Encryption Standard) for secure routing. The system employs rule-based fuzzy logic to correlate input values in both clustering and routing algorithms. Decision-making is based on factors such as the residual energy of sensor nodes, distance from the BS, and the number of nodes within the communication range. Input variables' crisp values are transformed into diverse fuzzy values, and the fuzzy output values are converted back to crisp values using the centroid defuzzification method. Selection of cluster heads and routers is determined by the output values, with sensor nodes being allocated to respective cluster heads based on their load-handling capacity. The routing path is then generated considering the capacity of routers. Simulations are conducted to evaluate energy consumption, active sensor nodes per round, and the sustainability period of the network. This proposed hybrid clustering and routing system aim to enhance the overall efficiency of wireless sensor networks by optimizing energy consumption and ensuring secure data transmission. The optimization model identifies the most suitable nodes in the routing cycle, starting with chosen cluster heads. The overarching goal is to enhance network indicators, including network lifespan, power consumption per node, and packet delivery percentage. The proposed solution achieved a network lifetime of 100 hours and a data delivery rate of 98%. additionally, it consumed the least amount of energy, measuring at 95,000 joules.

Evaluation and Automation of Energy Consumption: A Tool for National Development

In developing countries like Nigeria, high energy inefficiency and poor technology have led to increased energy costs and wastage. This paper focuses on the second goal of the African Union Agenda 2063, which emphasizes the importance of science, technology, and innovation in creating well-educated citizens and a skills revolution. The objective is to investigate how evaluating and automating energy consumption can contribute to national development. The study utilizes a mixed-methods approach, gathering qualitative and quantitative data. The quantitative phase includes data collection from surveys via wellstructured questionnaires to quantify energy usage patterns and assess the potential for automation. The qualitative phase includes in-depth interviews with energy users on their perspectives on energy evaluation and automation. For data analysis, ETAP, SPSS, and Microsoft Excel version 2016 are utilized. Consequently, hardware and software applications are developed to automate energy consumption through the utilization of a microcontroller and a mobile app. The key findings reveal eight loads measured over a year that an automated meter consumed 806.65 Joules of energy, whereas the existing meter consumed 1447.23 Joules. This demonstrates that automated systems consume less energy compared to the existing meters. The study emphasizes the significance of efficient energy consumption for achieving sustainable development goals and explores the potential of automation in optimizing energy usage.

R290 Refrigerant Performance in a Commercial Refrigerator

In this study, we investigated the impact of the environmentally friendly R290 refrigerant, which has a higher Coefficient of Performance (COP), on the operating performance of the cooling system, as an alternative to the commonly used R404A refrigerant, which has a negative effect on global warming. The boundary conditions in the refrigeration cycle were designed to be -10°C evaporation and +45°C condensation, and the performance of the system referenced in the TS EN ISO 23953-2 standard was experimentally compared for both refrigerants. The temperature and energy consumption values of the M-packs, whose location and quantity are specified in the relevant standard, have been evaluated in terms of the cooling performance of the cabinet. As a result of the study, the heat removal performance of the system using R290 fluid in the condenser showed better results compared to R404A. According to the relevant standard, the system using R290 is in the C and D classes in the energy consumption evaluation.

Retraction Note: Photodegradation of ibuprofen laden-wastewater using sea-mud catalyst/H2O2 system: evaluation of sonication modes and energy consumption.

Retraction Note: Photodegradation of ibuprofen laden-wastewater using sea-mud catalyst/H2O2 system: evaluation of sonication modes and energy consumption.

Evaluation of energy consumption and carbon emission in EDM

Evaluation of energy consumption and carbon emission in EDM

Novel ethane recovery process from natural gas using ZIF-8/water–glycol slurry: Techno-economic and energy consumption evaluation

Ethane recovery is a vital step in natural gas processing and can provide raw material for ethylene production. The widely used cryogenic separation process is energy intensive, and the absorption-adsorption coupling process based on porous ZIF-8 slurry (SorbPro I) has been proven to be more energy-efficient. To further reduce energy consumption, this paper proposes a novel process with two absorption-adsorption columns (SorbPro II) and establishes its mathematical model by equilibrium stage method. Taking the natural gas with an ethane content of 6.19 mol% at 300,000 Nm3/d as a case study, the operating parameters of SorbPro I and SorbPro II are optimized by sensitivity analysis, and ethane recovery ratio of both processes can reach 90 %. The techno-economic/energy consumption evaluations of the two processes are conducted. Results show that the total annualized cost and the energy consumption per Nm3 feed gas of SorbPro II are 41.7 % and 47.7 % lower than those of SorbPro I, respectively. It indicates that SorbPro II has the same separation performance as SorbPro I, but is more economical.

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

AbstractEdge computing is essential to handle increasing data volumes and processing capacities. It provides real-time and secure data processing near data sources, like smart devices, alleviating cloud computing energy use, and saving network bandwidth. Specialized accelerators, like GPUs and FPGAs, are vital for low-latency edge computing but the requirements to customized code for different hardware and vendors suppose important compatibility issues. This paper evaluates the potential of SYCL in addressing code portability issues encountered in edge computing. We employed the Polybench suite to compare various SYCL implementations, specifically DPC++ and AdaptiveCpp, with the native solution, CUDA. The disparity between SYCL implementations was negligible, at just 5%. Furthermore, we evaluated SYCL in the context of specific edge computing applications such as video processing using three different optical flow algorithms. The results revealed a slight performance gap of 3% when transitioning from CUDA to SYCL. Upon evaluating energy consumption, the observed difference ranged from $$\pm 10\%$$ ± 10 % , depending on the application utilized. These gaps are the price one may need to pay when achieving the ability to successfully run the same code on two distinct edge boards. These findings underscore SYCL’s capacity to increase productivity in terms of development costs and facilitate IoT deployment without being locked into a particular platform or manufacturer.

Energy consumption evaluation of passenger electric vehicle based on ambient temperature under Real-World driving conditions

Electric vehicles are affected by ambient temperature, which is closely related to the driving range. This study conducted a comprehensive evaluation of the energy efficiency using both a chassis dynamometer and actual driving environments. Under various temperature conditions, the motor energy, battery energy, regenerative energy, and energy efficiency were analyzed using a Combination US06 mode of the chassis dynamometer and the Konkuk University route to realize real-world driving scenario. The results revealed that low temperatures increased the motor and battery energy consumptions (compared to 24 ℃ ambient temperature, −15 ℃ required 35.4 % more.) while hindering regenerative energy recovery during driving. This study confirmed that the optimal energy efficiency for electric vehicles is attained at approximately (20 to 30) ℃. Notably, the energy efficiencies were real- higher than the certified values under real-world driving conditions. Moreover, when the HVAC system is turned on, it increases battery energy consumption by 5.4 % in the summer and by 12.0 % in the winter, influencing the overall energy efficiency with higher battery energy consumption during its operation in both seasons. Therefore, the study findings highlight the importance of considering the ambient temperature and HVAC system usage when evaluating vehicle energy efficiency and driving range. Furthermore, this study emphasizes the need for future vehicle designs and energy management systems to optimize the performance under various ambient conditions, thereby enhancing the overall energy efficiency and extending the driving range.

Role of nonionic natural dispersing agent Acacia Concinna on the slurryability and stability of concentrated iron ore suspension

The present study examines the impacts of saponin, extracted from the fruits of Acacia Concinna, in its effectiveness as a dispersant and stabilizer during the pipeline conveyance of iron ore particles. The basic fundamental characteristics of iron ore, which comprises a majority of hematite and has a size of (≤75 µm), have been examined and characterized. Iron ore water slurry (IWS) rheological behavior has been investigated as a function of saponin doses, pH, particle concentration, and the shear rate-shear stress correlation. The change in zeta potential with pH is used to compute the isoelectric point of IWS. An appropriate mechanism has been presented to explicate the interaction between saponin and particles of Iron ore. The surface-modified particles exhibit improved dispersion characteristics in the aqueous solution due to the modification of electrostatic force that the surface charge on each particle causes. Investigation indicates that the optimal proportion of saponin had a significant favorable effect on the fluidity and stability of the suspension. The analysis of the economic impact of the dispersant has been conducted through the evaluation of slurry head loss and specific energy consumption (SEC) pertaining to the implementation of the IWS pipeline in its intended commercial application.

Data-driven evaluation of electric vehicle energy consumption for generalizing standard testing to real-world driving

Data-driven evaluation of electric vehicle energy consumption for generalizing standard testing to real-world driving

Evaluation indicators for road traffic energy consumption: a review and prospect.

Indicators for evaluating road traffic energy consumption are critical parameters in the research field of road traffic energy consumption. Improving the applicability of energy consumption indicators can promote the development of green transportation in cities. However, there is currently a lack of systematic analysis of energy consumption indicators in research. Therefore, based on a comprehensive analysis of relevant literature, this study divides the indicators for evaluating road traffic energy consumption into two categories: macro (aimed at traffic systems or traffic flow) and micro (aimed at vehicles). These indicators are subdivided into four categories according to their application characteristics, including general, specific, predictive, and comprehensive. This paper provides a complete summary of various evaluation indicators, including their scope of application, advantages, and limitations, and highlights the relationships between them. Additionally, recommendations are made for the future development of evaluation indicators. Research has found that micro-level general indicators serve as the fundamental components of the mathematical structure for almost all other indicators. Specialized indicators primarily evaluate energy consumption in different driving states of vehicles. Predictive indicators are mainly used for assessing transportation energy consumption in simulation conditions. Comprehensive indicators are mainly applied to evaluate the life cycle energy consumption of vehicles or transportation systems. In future research, the performance of indicators can be improved through the design of standardized indicators, enhancement of energy consumption prediction accuracy, and integration of traffic flow parameters. The research contributes to upgrading energy-saving technologies in road transportation and developing sustainable urban transportation systems.

Developing a housing stock model for evaluating energy Performance: The case of Jordan

The housing stock is the long-lasting component of the settlement structure. The dwellings make up 72% of buildings and consume around 40% of the primary energy in Jordan. The government in Jordan aims to meet the goals of Paris Agreement by 2050 toward net zero carbon. Considering its importance, this study aims to provide an approach for developing a housing stock model for Jordan to evaluate energy consumption of the residential sector at national level, as a baseline for improving the energy performance of the entire housing stock.A bottom-up approach is used to generate models of the Jordanian housing stock based on available buildings datasets. The generated 21 archetype models are analysed and used to evaluate the energy consumption of the national housing stock. Two archetype models represent the highest contribution, more than 80%, of annual energy use from the entire housing stock. The uncertainty analysis figures out that the 8.3% discrepancy between the baseline results and the measured data, for the entire stock, can be explained by the expected variation in input data.The study can provide policymakers with valuable insights into the energy performance of Jordan’s housing stock and inform the development of effective policies and strategies to reduce energy consumption and promote sustainable development. For example, it can assist in identifying the most effective interventions for refurbishment of different archetypes in the current stock, and the improvements required in new-build dwellings and thereby facilitate the transition to a low-carbon building stock in Jordan.

Comprehensive evaluation of energy consumption and carbon emissions of asphalt pavement recycling technology

To assess the energy saving and emission reduction effects of recycling technology, the quantitative analysis of energy consumption and carbon emission of recycled asphalt pavement is conducted of asphalt mixture production, transportation, paving and compaction. Firstly, the calculation model for energy consumption and carbon emissions of recycled asphalt pavement is established during the construction stage. In addition, the energy consumption and carbon emission of four recycling technologies, including the HCPR, HIR, CCPR and CIR, were compared. Finally, the FCE method is used to evaluate the actual effect of energy saving and emission reduction from the perspectives of the ecological benefit and the economic benefit. The research results indicate the most serious stage of energy consumption is the new material production stage, and the most serious stage of carbon emission is the asphalt mixture production stage of recycled asphalt pavement. Taking the HCPR technology as an example are calculated in detail. The energy consumption of the HCPR technology in the four stages of the construction stage was 17.59 MJ, 344.45 MJ, 228.51 MJ and 25.85 MJ, respectively, and the emissions in the four stages of the construction stage were 1307.89 g, 5971.28 g, 19,251.24 g and 1949.82 g, respectively. For different recycling technologies in the construction stage, the energy-saving ratios of HCPR, HIR and CCPR are 13.62%, 9.61% and 19.24% respectively when compared with the typical scheme, which have a certain energy-saving effect. However, the energy consumption of CIR reduced by 43.63%, which the energy saving effect is most significant. Moreover, the emission reduction ratios of HCPR, HIR and CCPR are 2.3%, 9.23% and 1.01% respectively when compared with the typical scheme, the emission of CIR reduced by 30.76%, so the emission reduction effect of CIR is most significant. Furthermore, the comprehensive evaluation score of the CIR technology with the most significant energy saving and emission reduction effect is 0.8021 in terms of ' ecological benefits ' and 0.8074 in terms of ' economic benefits '. In summary, it is recommended to adopt CIR technology in the engineering project, which can achieve the most significant energy-saving and emission reduction effects.

Architecture-level energy model for high-capacity STT-MRAM memory

ABSTRACT Nowadays, STT-MRAM has emerged as one of the leading contenders for next-generation memory technologies. However, STT-MRAM still exhibits high energy consumption due to its peripheral circuits, including the read/write and the sample amplifier (SA) circuits. Therefore, it is crucial to accurately evaluate the energy consumption of memory architectures during the early stages of the design process. Traditionally, energy evaluation can be conducted using the NVSim platform. However, the peripheral read/write circuitry of STT-MRAM undergoes iterative improvements, which cannot be promptly incorporated into NVSim. To address this limitation and to enable comprehensive energy consumption evaluations spanning from device-level to architecture-level for STT-MRAM, an architecture-level energy consumption model is proposed in this paper. The model offers high accuracy and flexibility for the STT-MRAM memory array structure, abstracting the influences of read/write circuits for power evaluations. Comparative analysis is performed between the proposed model and the traditional approaches. When estimating a memory array with 128 × 64, the deviation using the proposed model is less than 2%, showing improved accuracy compared to that with analytical formulas. Notably, the proposed model offers up to 97% time savings in the whole circuit simulation, thus enhancing efficiency in the design and evaluation process.

Microbial Electrolysis Cell Exergy Evaluation

Bio-electrochemical systems have increasingly become the focus of research due to their potential in environmental biotechnology, particularly in the domains of waste utilization and energy recovery. A prominent method within this domain is the transformation of organic matter into hydrogen via microbial electrolysis cells (MECs). This study offers a thorough analysis of MEC performance, employing exergy analysis and incorporating relevant data from the existing literature. The findings of this research indicate a relationship between process efficiency and effective electron transfer originating from biological oxidation to the cathode reaction, facilitating hydrogen generation. The assessment performed revealed that the exergy efficiency of the process varies by a wide range, depending on conditions such as substrate type and concentration, applied external voltage, and the presence of specific inhibitors. This interplay between substrate concentration, overall efficiency, and energy requirement underlines the complex dynamics of optimizing MEC performance. Our insights provide understanding of the challenges in bio-electrochemical systems, offering implications for their sustainable and efficient use in environmental biotechnology. The theoretical analysis involved assessing the utilization of glucose and glycerol, along with the evaluation of electrical energy consumption and hydrogen yield. Our results demonstrate that a higher applied voltage is associated with greater exergy efficiency. Furthermore, after comparing the use of glucose and glycerol as substrates, our study supports the preferential application of glucose for enhanced efficiency.

Evaluation and Modeling of Green Energy Consumption in North Sumatra, Indonesia

This paper discusses the level of green energy consumption in North Sumatra from 2020 to 2022 using the entropy method, the breakpoint method, and the integrated method. These three methods are applied to determine the feasibility of using new renewable energy. The three methods will be compared to each other to determine accuracy and options for analyzing models in the future. The level of green energy users from 2020 to 2022 generally shows a relatively stable and sustainable upward trend. During the 3 years there were fluctuations caused by the large growth rate of total energy consumption in North Sumatra, which increased by 6.35% from the previous year, and the level of urban green energy consumption grew steadily, which provided a more stable increase in user levels green energy with a sharp increase in the previous year. However, there are significant gaps in green energy consumption levels between cities. The contribution of this research is to select a model that will be applied in North Sumatra and provide input for policymakers regarding future energy and can have a positive impact on technological innovation, industry, and financial support in particular.

Research on Energy Consumption Monitoring and Evaluation Technology for Asphalt Mixing Plants Based on the Internet of Things

The construction process of asphalt pavement in highway construction projects is a key link in energy consumption and emissions, and the production of asphalt mixing stations is the main energy consumption link of asphalt pavement. Currently, targeted energy consumption evaluation and monitoring of asphalt mixing stations still lack systematic research. This article first determines the evaluation indicators for energy conservation and emission reduction of asphalt pavement. By decomposing the energy consumption composition of the asphalt mixing station, a energy consumption evaluation system for the asphalt mixing station consisting of three parts: heating drum, asphalt heating and insulation system, and power system is established. After calculation, the predicted natural gas conversion rates for each ton of SMA-13 asphalt mixture in the upper layer, AC-20 asphalt mixture in the middle layer, and AC-25 asphalt mixture in the lower layer are 8.07, 7.41, and 6.87 m3, respectively. The predicted results fit well with the measured data. Finally, through the development of hardware and software, the energy consumption evaluation and monitoring of asphalt mixing stations based on the Internet of Things were achieved, which played a promoting role in the environmental protection evaluation of highway pavement construction.

Energy consumption assessment and economic analysis of a novel sustainable electro-machining auxiliary system

In contrast to traditional machining methods, electro-machining presents a new opportunity for treating materials that are problematic for conventional approaches. While gaining increasing prominence in the manufacturing industry, electro-machining is marked by heightened energy consumption and reduced operational efficiency. A comprehensive survey of electro-machining manufacturing facilities has identified two pivotal factors influencing energy consumption and efficiency enhancements: 1) determining optimal electrical parameters for electro-machining during the production planning stage, and 2) timely adjustment of electro-machining parameters throughout the production stage. To address these two challenges, an innovative model-based electro-machining auxiliary system has been introduced for the surveillance and optimization of the machining process. The system aims to curtail energy consumption, enhance machining efficiency, and fortify economic viability, all while maintaining machining quality. Notably, the system demonstrates adaptability in deriving optimized electrical parameters tailored to diverse processing conditions. Energy consumption evaluation and techno-economic analysis, employing primary industry data, were conducted to compare the energy efficiency and economic performance of the machining process with the new auxiliary system against the conventional approach. The foremost outcome of adopting the new auxiliary system is a substantial reduction in energy usage; from an economic standpoint, the analysis shows that the cost of machining a single workpiece is reduced by 27.75%; the energy efficiency analysis reveals a 27.75% decrease in energy consumption per unit area, accompanied by an approximately 30% increase in machining efficiency. The proposed approach has demonstrated significant practical value for the sustainable development of the electro-machining process.

Simulation optimization and energy consumption evaluation on the wood solar drying kiln with heat storage and dehumidification system

The conventional wood drying process has high energy consumption and detrimental environmental impact. While solar energy has found widespread application in material drying, simulation software has been instrumental in optimizing drying processes and curbing energy consumption. Nevertheless, there remains a dearth of simulation and optimization studies specifically focusing on wood drying systems, particularly those incorporating phase-change heat storage devices.This study delves into the wood drying process in one year within a solar drying kiln equipped with a phase-change heat storage and dehumidification system. The investigation scrutinizes the impact of different operating parameters and heat storage devices on the temperature distribution across the entire system. Results indicate that through a new programming method, the simulation of the temperature change of the phase change thermal storage material is realized, and the visualization degree of the system is improved. The average relative error of simulated temperature and measured temperature is 2.29 %, which has a strong consistency. When dehumidifier air flow rate is 1500 m3/h, solar panel angle is 36°, the dehumidifier is turned off when the drying room temperature reaches 55 °C, and the dehumidifier is turned on when the drying room temperature drops below 55 °C, the highest energy efficiency can be achieved. Moreover, through simulation and optimization, the average indoor temperature increased by 24.05 %, and the system energy consumption reduced by about 56.23 %. This is equivalent to a reduction of 3,312.22 kg of CO2 emissions.In essence, this study provides a pathway for enterprises to realize tangible energy savings and emission reductions in the wood drying process, showcasing the potential of integrating solar energy, phase-change heat storage, and dehumidification for enhanced efficiency.