High Energy Consumption Issues Research Articles

Synergistic Catalysis of SO42-/TiO2-CNT for the CO2 Desorption Process with Low Energy Consumption.

To address the issue of high energy consumption associated with monoethanolamine (MEA) regeneration in the CO2 capture process, solid acid catalysts have been widely investigated due to their performance in accelerating carbamate decomposition. The recently discovered carbon nanotube (CNT) catalyst presents efficient catalytic activity for bicarbonate decomposition. In this paper, bifunctional catalysts SO42-/TiO2-CNT (STC) were prepared, which could simultaneously catalyze carbamate and bicarbonate decomposition, and outstanding catalytic performance has been exhibited. STC significantly increased the CO2 desorption amount by 82.3% and decreased the relative heat duty by 46% compared to the MEA-CO2 solution without catalysts. The excellent stability of STC was confirmed by 15 cyclic absorption-desorption experiments, showing good practical feasibility for decreasing energy consumption in an industrial CO2 capture process. Furthermore, associated with the results of experimental characterization and theoretical calculations, the synergistic catalysis of STC catalysts via proton and charge transfer was proposed. This work demonstrated the potential of STC catalysts in improving the efficiency of amine regeneration processes and reducing energy consumption, contributing to the design of more effective and economical catalysts for carbon capture.

A multi-objective optimization of a single-phase immersion cooling system at cabinet level

With the rapid development and urgent requirement of high computing power, the energy consumption of data center (DC) is constantly increasing. The issue of high energy consumption constrains rapid development of DCs and becomes a major challenge that urgently needs to be solved in the transformation of DCs towards large-scale, intelligent, and energy-saving. In the present study, a cabinet level single-phase immersion cooling (SPIC) system was experimentally investigated with coolant of Noah 3000D. The cooling capacity and energy consumption level of the SPIC system were investigated. The impacts of the heat load, coolant flow rate, and cooling water flow rate on the thermal performance of the SPIC unit were quantitatively analyzed. Based on experimental data fitting, the heat transfer criterion correlation and pressure difference calculation formula were obtained. The error caused by the heat transfer criterion correlation and pressure difference calculation formula is basically within ± 5 %. Based on the multi-objective optimization, both the coolant flow rate and cooling water flow rate cause obvious influences on the heat transfer coefficient and energy consumption of SPIC systems. The temperature changes on both sides of the heat exchanger can be ignored, and the error caused by the assumption does not exceed ± 1 %. With some valuable findings obtained, this work can supply some technique references for engineering design and operation management of SPIC systems.

Low energy consumption layout of exhibition buildings in Yangtze River Delta region

The issue of high energy consumption in exhibition buildings has long been a focal point in the field of architectural design. However, current energy consumption assessments for exhibition buildings mainly focus on post-construction evaluations, lacking corresponding guidance during the initial design phase. To address this issue, this study selected 48 well-known exhibition buildings both domestically and internationally as research subjects. Utilizing scatter plot curve fitting, it was discovered that there exists a nonlinear quadratic relationship between the building area of the first floor and the courtyard area. Based on this relationship, four typical layouts were established to match the climatic characteristics of Hangzhou, a representative region in the Yangtze River Delta of China. Taking into account regional architectural features, the study specifically examined the impact of different orientations and window-to-wall ratios on energy consumption levels. The influence of these factors on energy consumption was analyzed using the DesignBuilder software. The results revealed that there exists an optimal window-to-wall ratio for exhibition buildings, with parallel, L-shaped enclosed south-facing courtyards, and U-shaped enclosed east-facing courtyards showing greater energy efficiency. This research provides guidance for designing exhibition buildings that are energy-efficient and foster a harmonious indoor–outdoor relationship.

Energy, exergy, economic, and environmental analysis of natural gas sweetening process using lean vapor compression: a comparison study

Abstract Gas sweetening with an aqueous solution of diethanolamine is a crucial and common process in natural gas processing. However, the process, particularly in the solvent regeneration section, consumes a substantial amount of energy, significantly escalating the cost of gas. This paper presents a simulation and optimization of an existing natural gas refinery plant using a lean vapor compression method. The simulation results indicate that the current process requires 2.73 GJ/tacid gas for solvent regeneration, with exergy destruction of 14,120.59 kW in the solvent regeneration section. The total annualized cost for the current process is 11.68 M$. A modified scheme is proposed to address the issue of high energy consumption and the associated costs. The proposed scheme demonstrates significant improvements in the aforementioned parameters. Specifically, energy for solvent regeneration, exergy destruction in the solvent regeneration section, total annualized cost, and cost of gas are reduced by 16.12 %, 25.04 %, 20.97 %, and 20 % compared to the current process, respectively. These improvements enhance the thermoeconomic indexes, making the proposed scheme a viable and cost-effective alternative to the current process.

CuInP2S6‐Based Electronic/Optoelectronic Synapse for Artificial Visual System Application

AbstractWith the development of information processing, various neuromorphic synaptic devices have been proposed, including novel devices mimicking multiple sensory systems in the biosome, in which vision is a vital source of information. Due to the pressing issue of high energy consumption and the ever‐increasing complexity of practical application scenarios, there is an urgent need to investigate optoelectronic synapses with simple structure but multifunctional capabilities, thereby broadening their application scope. Here, remarkable performances in both electrical and optical operation modes are achieved in multilayer graphene/CuInP2S6/Au electronic/optoelectronic device. By modulating the electrical and optical pulses, both short‐term and long‐term memory can be emulated in the same device, while visual perception, processing, and memorizing functions are demonstrated in this single cell with relatively low energy consumption. In addition, light adaptive behavior can also be simulated through optical–electrical cooperative modulation in the device, further providing a novel and promising strategy for future applications in artificial visual systems.

Study on the Influence Mechanism of Energy Consumption of Sugarcane Harvester Extractor by Fluid Simulation and Experiment

Previous studies on sugarcane harvester extractors have mainly focused on improving harvest quality and reducing the impurity rate and loss rate, which often ignored the issue of high energy consumption. To reduce the energy consumption of the extractor while maintaining the original impurity rate and loss rate stable, firstly, a blade element analysis method with aerodynamic theory was put forward to analyze the stress of the extractor blade, and the energy consumption equation and influencing factors of extraction were obtained. Subsequently, the computational fluid dynamics model of the exhaust extractor was established. Computational fluid dynamics (CFD) and the SST k-ω model were used to analyze the mechanism of various influencing factors on the energy consumption and internal flow characteristics of the extractor. The changes in various parameters were analyzed and discussed with respect to the resulting variations in internal pressure, velocity, vortex structure, and lift–drag coefficient of the extractor. A test bench of the extractor was built, and orthogonal tests were carried out with energy consumption, impurity rate, and loss rate as test indicators. Considering the results of the simulation and bench test comprehensively, the combination of a rotational speed of 1450 RPM, a blade number of 3, an installation angle of 25°, and a blade chord length of 200 mm was optimal for the extractor. Finally, a comparative test was carried out between the optimized extractor and the original extractor. The results demonstrated that the energy consumption of the optimized extractor was reduced by 15.49%. The impurity rate decreased by 3.51%, and the loss rate decreased by 12.39% compared to the original extractor. The study can provide a theoretical and experimental basis for designing and optimizing extractor performance.

Data center server workload and infrastructure control based on a joint RSM and CFD approach

The rapid expansion of data centers and cloud computing has exacerbated the issue of high energy consumption and localized overheating in servers. Consequently, the identification of effective cooling methods and resource allocation strategies for server rooms has become pivotal in enhancing overall airflow distribution and optimizing thermal performance within data centers. Time-efficient Computational Fluid Dynamics (CFD) tools offer an alternative to resource-intensive experimental measurements. However, it is difficult to monitor the information in real time and optimize the design of DC. In this study, an innovative application of Response Surface Methodology (RSM) is introduced to prediction thermal environment information and optimization performance of data center. In contrast to traditional single-factor optimization methods, this approach incorporates multiple factors, such as server workloads and air supply conditions, as optimization parameters. Furthermore, maximum server temperatures, temperature differences, and other metrics are defined as key performance indicators (KPIs). A predictive model was developed with the aim of offering comprehensive information about the thermal environment of the data center. Moreover, the study qualitatively analyzes the influence of each parameter on various indicators. Fitting equations are solved based on actual conditions to determine optimized configuration schemes in real time for the entire data center or specific scenarios. This approach effectively reduces cooling energy consumption and optimizes data center thermal management. The optimized configuration resulted in a significant reduction of approximately 30% in the maximum server temperature and approximately 20% in the temperature difference. Additionally, the optimization methodology established in this study facilitates the implementation of a real-time control mechanism for data center cooling systems, enabling energy demand and management optimization. The findings of this study offer valuable insights and generalized methods for enhancing the performance of air-cooled servers.

Can water conservation and energy conservation be promoted simultaneously in China?

Understanding the water-energy (WE) nexus is crucial for addressing water scarcity and high energy consumption issues in China. However, few studies have analyzed the WE nexus and the drivers of the spatiotemporal changes. To fill in this gap, we quantified the provincial energy, water-related energy, water, and energy-related water footprints (EF, EFwat, WF, and WFene, respectively) in China during 2002–2017 based on a multiregional input-output model, and analyzed the drivers underlying their changes. Results showed that Agriculture, Manufacturing, and Energy supply were dominant sectors in the WE nexus, showing 371.9 billion m3 (bm3) of WF, 16.3 trillion kWh (TkWh) of EF, and 0.2 TkWh of EFwat on average, respectively. Structural adjustment and key technological advances reduced WF by 272.6 and 265.4 bm3, and EF by 4.3 and 2.8 TkWh, respectively, but they resulted in −0.1 and −0.023 TkWh of WFene, and −2.3 and 10.2 bm3 of EFwat, respectively. Final demand and resource consumption intensity effects were respectively the main accelerator and suppressor of resource footprints during 2002–2017. Upgrading industrial chains and phasing out backward production capacity could promote water and energy conservation simultaneously. This study provides a scientific basis for comprehensive policymaking toward sustainable water and energy management.

A Review of Artificial Intelligence in Embedded Systems.

Advancements in artificial intelligence algorithms and models, along with embedded device support, have resulted in the issue of high energy consumption and poor compatibility when deploying artificial intelligence models and networks on embedded devices becoming solvable. In response to these problems, this paper introduces three aspects of methods and applications for deploying artificial intelligence technologies on embedded devices, including artificial intelligence algorithms and models on resource-constrained hardware, acceleration methods for embedded devices, neural network compression, and current application models of embedded AI. This paper compares relevant literature, highlights the strengths and weaknesses, and concludes with future directions for embedded AI and a summary of the article.

Algae Pyrolysis in Molten NaOH-Na2CO3 for Hydrogen Production.

Biomass pyrolysis within the alkaline molten salt is attractive due to its ability to achieve high hydrogen yield under relatively mild conditions. However, poor contact between biomass, especially the biomass pellet, and hydroxide during the slow heating process, as well as low reaction temperatures, become key factors limiting the hydrogen production. To address these challenges, fast pyrolysis of the algae pellet in molten NaOH-Na2CO3 was conducted at 550, 650, and 750 °C. Algae were chosen as feedstock for their high photosynthetic efficiency and growth rate, and the concept of coupling molten salt with concentrated solar energy was proposed to address the issue of high energy consumption at high temperatures. At 750 °C, the pollutant gases containing Cl and S were completely removed, and the HCN removal rate reached 44.92%. During the continuous pyrolysis process, after a slight increase, the hydrogen yield remained stable at 71.48 mmol/g-algae and constituted 86.10% of the gas products, and a minimum theoretical hydrogen production efficiency of algae can reach 84.86%. Most importantly, the evolution of physicochemical properties of molten NaOH-Na2CO3 was revealed for the first time. Combined with the conversion characteristics of feedstock and gas products, this study provides practical guidance for large-scale application of molten salt including feedstock, operation parameters, and post-treatment process.

Energy-Efficient DNN Inference on Approximate Accelerators Through Formal Property Exploration

Deep neural networks (DNNs) are being heavily utilized in modern applications, putting energy-constraint devices to the test. To bypass high energy consumption issues, approximate computing has been employed in DNN accelerators to balance out the accuracy-energy reduction trade-off. However, the approximation-induced accuracy loss can be very high and drastically degrade the performance of the DNN. Therefore, there is a need for a fine-grain mechanism that would assign specific DNN operations to approximation to maintain acceptable DNN accuracy, while achieving low energy consumption. We present an automated framework for weight-to-approximation mapping through formal property exploration for approximate DNN accelerators. At the MAC unit level, our experimental evaluation surpassed already energy-efficient mappings by more than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times 2$ </tex-math></inline-formula> in terms of energy gains, while supporting a fine-grain control over the introduced approximation.

Forward-and-reverse multidirectional turning: A novel material removal approach for improving energy efficiency, processing efficiency and quality

To address the issue of high energy consumption and low utilization rate in conventional turning, a concept of forward-and-reverse multidirectional turning (MDT) and the MDT approach are proposed to reduce energy consumption in idling and to improve processing efficiency and surface quality. The material removal performance of the MDT from aspects of energy consumption, processing efficiency, chip morphology and surface quality is discussed to understand its features and advantages compared with unidirectional turning (UDT). In three application scenarios, the processing efficiency is increased by 6.40%, 8.45%, and 7.76%, and energy consumption is reduced by 10.88%, 7.25%, and 9.52%, using the MDT, respectively. Additionally, the MDT has better control ability of the chip removal, benefitting for improving the processing stability. The surface quality of the workpiece processed by the MDT is generally better than that by UDT. This study provides a novel high performance processing approach for the machining,which contributes to promoting the efficient and high-quality development of mechanical manufacturing industry.

Environmental aspects of the production and use of autoclaved aerated concrete with low density

The purpose of the article is to investigate the state of carbon dioxide emissions generated as a result of wall materials production and the construction industry as a whole. The paper provides a comparative analysis of housing construction in Ukraine and in some CIS countries. Against the background of the indicators of low housing availability and low relative volumes of housing construction, the issue of high energy consumption remains valid. The absolute and relative volumes of greenhouse gas emissions from economic activity of the population of Ukraine are given. The projected consequences for Ukraine from continued CO2 emissions on the same level and temperature rise are estimated. It is deemed that the most suitable wall material for countries with emerging economies is autoclaved aerated concrete (AAC); since it is a structural and thermal insulating material, it can solve the problem of housing construction.&#x0D; The paper shows the key priority of low energy consumption and makes emphasis on lowering the density of the produced aerated concrete, reducing mineral additives and cement production expenses.

Scenario-Based Comparative Analysis for Coupling Electricity and Hydrogen Storage in Clean Oilfield Energy Supply System

In response to the objective of fully attaining carbon neutrality by 2060, people from all walks of life are pursuing low-carbon transformation. Due to the high water cut in the middle and late phases of development, the oilfield’s energy consumption will be quite high, and the rise in energy consumption will lead to an increase in carbon emission at the same time. As a result, the traditional energy model is incapable of meeting the energy consumption requirement of high water cut oilfields in their middle and later phases of development. The present wind hydrogen coupling energy system was researched and coupled with the classic dispersed oilfield energy system to produce energy for the oilfields in this study. This study compares four future energy system models to existing ones, computes the energy cost and net present value of an oilfield in Northwest China, and proposes a set of economic evaluation tools for oilfield energy systems. The study’s findings indicate that scenario four provides the most economic and environmental benefits. This scenario effectively addresses the issue of high energy consumption associated with aging oilfields at this point, significantly reduces carbon emissions, absorbs renewable energy locally, and reduces the burden on the power grid system. Finally, sensitivity analysis is utilized to determine the effect of wind speed, electricity cost, and oilfield gas output on the system’s economic performance. The results indicate that the system developed in this study can be applied to other oilfields.

Energy Aware Metaheuristic Optimization with Location Aided Routing Protocol for MANET

A mobile ad hoc network (MANET) involves a group of wireless mobile nodes which create an impermanent network with no central authority and infrastructure. The nodes in the MANET are highly mobile and it results in adequate network topology, link loss, and increase the re-initialization of the route discovery process. Route planning in MANET is a multi-hop communication process due to the restricted transmission range of the nodes. Location aided routing (LAR) is one of the effective routing protocols in MANET which suffers from the issue of high energy consumption. Though few research works have focused on resolving energy consumption problem in LAR, energy efficiency still remains a major design issue. In this aspect, this study introduces an energy aware metaheuristic optimization with LAR (EAMO-LAR) protocol for MANETs. The EAMO-LAR protocol makes use of manta ray foraging optimization algorithm (MRFO) to help the searching process for the individual solution to be passed to the LAR protocol. The fitness value of the created solutions is determined next to pass the solutions to the objective function. The MRFO algorithm is incorporated into the LAR protocol in the EAMO-LAR protocol to reduce the desired energy utilization. To ensure the improved routing efficiency of the proposed EAMO-LAR protocol, a series of simulations take place. The resultant experimental values pointed out the supreme outcome of the EAMO-LAR protocol over the recently compared methods. The resultant values demonstrated that the EAMO-LAR protocol has accomplished effectual results over the other existing techniques.

Novel heat pump reactive distillation and dividing-wall column reactive distillation processes for synthesizing isopropyl acetate to save TAC and reduce CO2 emissions

Focusing primarily on the issue of high energy consumption in isopropyl acetate (IPAC) production, a heat pump reactive distillation (RD-HP) process and a dividing-wall column reactive distillation (RD-DWC) process were proposed. Chemical software Aspen Plus (version 10) was used to investigate the steady state simulations. In this work, RD-HP and RD-DWC processes were compared with conventional reactive distillation (CRD) in energy saving, economic, and environmental performance. In addition, TAC was used as the objective function, and the sequential iterative procedure was proposed for the design of three processes, and the optimal parameters were obtained. The results manifested that the IPAC product of three processes all reached the purity index (mole fraction 98.20%). Compared with CRD, the TAC of RD-HP and RD-DWC were reduced by 13.46% and 21.31%, CO2 emissions were reduced by 13.25% and 20.17%, respectively. The thermodynamic efficiency of three processes are 7.69%, 9.02%, and 10.57%, respectively.

Machine Learning based Energy Management at Internet of Things Network Nodes

The Internet of Things networks comprising wireless sensors and controllers or IoT gateways offers extremely high functionalities. However, not much attention is paid towards energy optimization of these nodes and enabling lossless networks. The wireless sensor networks and its applications has industrialized and scaled up gradually with the development of artificial intelligence and popularization of machine learning. The uneven network node energy consumption and local optimum is reached by the algorithm protocol due to the high energy consumption issues relating to the routing strategy. The smart ant colony optimization algorithm is used for obtaining an energy balanced routing at required regions. A neighbor selection strategy is proposed by combining the wireless sensor network nodes and the energy factors based on the smart ant colony optimization algorithm. The termination conditions for the algorithm as well as adaptive perturbation strategy are established for improving the convergence speed as well as ant searchability. This enables obtaining the find the global optimal solution. The performance, network life cycle, energy distribution, node equilibrium, network delay and network energy consumption are improved using the proposed routing planning methodology. There has been around 10% energy saving compared to the existing state-of-the-art algorithms.

Basic Passive Side-Day lighting Considerations for High Rise office Building

High rise office building design is one of the essential buildings in construction industry due to the limited space especially in the urban area. After home, a high rise office building is an important space for human in modern era. Due to the issue of high energy consumption especially inefficient artificial light strategy, side-day lighting becomes the best solution for a high rise office building design. Despite providing efficient energy consumption, side-day lighting creates a positive impact to the worker as well as the office's indoor environment. Hence, this paper aims to explore the basic passive side-day lighting considerations that educate people especially for those who are involved in the building construction industry. Beside, this paper focuses on the passive design considerations due to the various advantages that not involved especially with complex electrical and mechanical system. A systematic literature review is the main methodology for this paper to identify the basic passive side-day lighting considerations for a high rise office building design. Base on this research, it revealed that eight elements for building design considerations should be applied to provide a better day lighting impact for a high rise office building design. Considerations for non-building design aspects should also need to be applied since those aspects contribute to produce a better day lighting impact for a high rise office building design.

QoS provisioning and energy saving scheme for distributed cognitive radio networks using deep learning

One of the major challenges facing the realization of cognitive radios (CRs) in future mobile and wireless communications is the issue of high energy consumption. Since future network infrastructure will host real-time services requiring immediate satisfaction, the issue of high energy consumption will hinder the full realization of CRs. This means that to offer the required quality of service (QoS) in an energy-efficient manner, resource management strategies need to allow for effective trade-offs between QoS provisioning and energy saving. To address this issue, this paper focuses on single base station (BS) management, where resource consumption efficiency is obtained by solving a dynamic resource allocation (RA) problem using bipartite matching. A deep learning (DL) predictive control scheme is used to predict the traffic load for better energy saving using a stacked auto-encoder (SAE). Considered here was a base station (BS) processor with both processor sharing (PS) and first-come-first-served (FCFS) sharing disciplines under quite general assumptions about the arrival and service processes. The workload arrivals are defined by a Markovian arrival process while the service is general. The possible impatience of customers is taken into account in terms of the required delays. In this way, the BS processor is treated as a hybrid switching system that chooses a better packet scheduling scheme between mean slowdown (MS) FCFS and MS PS. The simulation results presented in this paper indicate that the proposed predictive control scheme achieves better energy saving as the traffic load increases, and that the processing of workload using MS PS achieves substantially superior energy saving compared to MS FCFS.

Intelligent fuzzy rule-based approach with outlier detection for secured routing in WSN

In wireless sensor networks (WSNs), energy optimization and the provision of security are the major design challenges. Since the wireless sensor devices are energy constrained, the issue of high energy consumption by the malicious nodes must be addressed well in order to enhance the network performance by making increased network lifetime, reduced energy consumption and delay. In the past, many researchers worked in the provision of new techniques for providing improved security to WSN in order to enhance the reliability in the routing process. However, most of the existing routing techniques are not able to achieve the required security through the use of intelligent techniques for safeguarding the sensor nodes from malicious attacks. In order to address these problems, a new fuzzy temporal clustering-based secured communication model with trust analysis and outlier detection has been developed in this research work. For this purpose, a new fuzzy temporal rule-based cluster-based routing algorithm with trust modelling and outlier detection for monitoring the nodes participating in the communication has been proposed. In addition, a fuzzy temporal rule- and distance-based outlier detection algorithm is also proposed in this paper for distinguishing the malicious nodes from other nodes within each cluster of the network and has been used in the secured routing algorithm. The proposed secure routing algorithm uses the temporal reasoning tasks of explanation-based learning and prediction as well as spatial constraints for making efficient routing decisions through the application of trust and key management techniques for performing effective authentication of nodes and thereby isolating the malicious nodes from communication through outlier detection. By applying these two proposed algorithms for communication in the proposed work, it is proved through experiments that the proposed secure routing algorithm and the outlier detection algorithm are able to perform secured and reliable routing through genuine cluster head nodes more effectively. Moreover, these two algorithms provide improved quality of service with respect to the reliability of communication, packet delivery ratio, reduction in end-to-end delay and reduced energy consumption.