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With the surging energy price and environmental concerns, measures to improve energy efficiency have attracted increasing concerns of the manufacture sector, especially energy-intensive manufacturing industries such as tissue paper mills. Energy-efficiency scheduling, as a novel energy-efficient method, has attracted the attention of an increasing number of researchers in recent years. Drying process is the most energy-intensive production process in tissue paper mills, which has a great energy-saving potential. This paper aims to reduce the energy costs for the tissue paper mill, consisting of processing energy cost and set-up energy cost, through integrating drying process optimization with energy-efficient scheduling. First, the energy cost model and the scheduling model were built. Then, the energy cost of the drying process of every job in a given scheduling problem was optimized using particle swarm optimization (PSO). Afterwards, the energy cost was further optimized using energy-efficiency scheduling. In addition, a hybrid non-dominated sorting genetic algorithm II (NSGA-II) was utilized to solve the energy-efficiency scheduling problem. Finally, several real scheduling problems from a real tissue paper mill were addressed using the proposed approach to demonstrate its effectiveness in energy saving. The experiment result showed that there is a great energy-saving potential in the drying process, accounting for up to 12.53% of the total energy consumption. Moreover, the maximum energy saving ratio of the proposed approach could reach 9.03%. On the whole, the proposed approach can provide a new energy-saving method for tissue paper mills or other manufacturing industries. [ABSTRACT FROM AUTHOR]

The pulp and paper industry accounts for approximately 5% of total industrial energy consumption and contributes 2% of direct carbon dioxide (CO 2 ) emissions from industries. World paper and paperboard demand and production are increasing significantly, leading to an increase in this sector's energy use and CO 2 emissions. Although current studies identify a wide range of energy-efficiency technologies that have already been commercialized for the pulp and paper industry, information is limited or scattered regarding new energy-efficiency technologies that are not yet fully commercialized. Development of emerging or advanced energy-efficiency technologies and their deployment in the market will be crucial for this industry's mid- and long-term energy saving and climate change mitigation strategies. This paper compiles available information on energy savings, environmental and other benefits, costs, and commercialization status for 25 emerging technologies to reduce the energy use and CO 2 emissions. The purpose is to provide a well-structured comprehensive review on these emerging energy-efficiency technologies for engineers, researchers, investors, policy makers, pulp and/or paper companies, and other interested parties. [ABSTRACT FROM AUTHOR]

Abstract: The pulp and paper industry is one of the most energy-intensive industries worldwide. In 2007, it accounted for 5% of total global industrial energy consumption and 2% of direct industrial carbon dioxide (CO2) emissions. An energy audit is a primary step toward improving energy efficiency at the facility level. This paper describes a plant-wide energy audit aimed at identifying energy conservation and CO2 mitigation opportunities at a paper mill in Guangdong province, China. We describe the energy audit methods, relevant Chinese standards, methods of calculating energy and carbon indicators, baseline energy consumption and CO2 emissions of the audited paper mill, and nine energy-efficiency improvement opportunities identified by the audit. For each of the nine options, we evaluate the energy conservation and associated CO2 mitigation potential. The total technical energy conservation potential for these nine opportunities is 967.8terajoules (TJ), and the total CO2 mitigation potential is equal to 93,453tonnes CO2 annually, representing 14.4% and 14.7%, respectively, of the mill’s total energy consumption and CO2 emissions during the audit period. [Copyright &y& Elsevier]

Abstract: The systematic, transparent and accurate on-line energy information of the production process is quite the basis of mill energy management and conservation. An Energy Management System (EMS) was built according to the characteristics of the energy usage in a typical newsprint paper mill. The EMS first realized the process data acquisition and integration, second fulfilled the on-line energy information calculation from the integrated data. A water and steam properties query component based on IAPWS-IF97 was developed and plugged into the EMS to facilitate the energy calculation of water and steam. The practical performance in the paper mill showed that the integrated energy information of the whole mill was gained and the on-line energy supervisory was achieved. In the end a systematic, transparent and accurate energy usage profile is obtained and it would provide the valuable fundamental energy data for the further energy analysis and optimization in the EMS. [Copyright &y& Elsevier]

Electricity consumption in buildings is one of the major causes of energy usage and knowledge of this can help building owners and users increase energy efficiency and conservation efforts. For Pacific Island countries, building electricity demand data is not readily accessible or available for constructing models to predict electricity demand. This paper starts to fill this gap by studying the case of schools in Fiji. The aim of the paper is to assess the factors affecting electricity demand for grid-connected Fijian schools and use this assessment to build mathematical models (multiple linear regression (MLR) and artificial neural network (ANN)) to predict electricity consumption. The average grid-connected electricity demand in kWh/year was 1411 for early childhood education schools, 5403 for primary schools, and 23,895 for secondary schools. For predicting electricity demand (ED) for all grid-connected schools, the stepwise MLR model shows that taking logarithm transformations on both the dependent variable and independent variables (number of students, lights, and air conditioning systems) yields statistically significant independent variables with an R2 value of 73.3% and RMSE of 0.2248. To improve the predicting performance, ANN models were constructed on both the natural form of variables and transformed variables. The optimum ANN model had an R2 value of 95.3% and an RMSE of 59.4 kWh/year. The findings of this study can assist schools in putting measures in place to reduce their electricity demand, associated costs, and carbon footprint, as well as help government ministries make better-informed policies. [ABSTRACT FROM AUTHOR]

In advanced manufacturing, optimizing mixed-model synchronous assembly lines (MMALs) is crucial for enhancing productivity and adhering to sustainability principles, particularly in terms of energy consumption and energy-efficient sequencing. This paper introduces a novel approach by categorizing sequence-dependent setup times into bipartite categories: workpiece-independent and workpiece-dependent. This strategic division streamlines assembly processes, reduces idle times, and decreases energy consumption through more efficient machine usage. A new mathematical model is proposed to minimize the intervals at which workpieces are launched on an MMAL, aiming to reduce operational downtime that typically leads to excessive energy use. Given the Non-deterministic Polynomial-time hard (NP-hard) nature of this problem, a genetic algorithm (GA) is developed to efficiently find solutions, with performance compared against the traditional branch and bound technique (B&B). This method enhances the responsiveness of MMALs to variable production demands and contributes to energy conservation by optimizing the sequence of operations to align with energy-saving objectives. Computational experiments conducted on small and large-sized problems demonstrate that the proposed GA outperforms the conventional B&B method regarding solution quality, diversity level, and computational time, leading to energy reductions and enhanced cost-effectiveness in manufacturing settings. [ABSTRACT FROM AUTHOR]

Amid a war in Southeast Asia, fomenting campus radicalism, and a looming energy crisis, a number of physicists shifted from the big science endeavors of post-war physics toward a new and little science of energy efficiency. These moves were actively supported by the American Physical Society, which took various ongoing crises as an opportunity to create employment opportunities and harness enthusiasm for more socially engaged physics. The Society's 1974 Summer School on efficient energy use was illustrative. Participants came from universities, national laboratories, industry organizations, and utility companies. Together, they estimated efficiency savings believed achievable at certain points in the US energy system. The summer school attendees argued energy efficiency should be redefined according to the second law of thermodynamics rather than the first. This approach allowed energy-using appliances to be reconceived of as sources of energy supply as well as demand. Rigorous estimates of potential savings were made. However, to the ire of more radical physicists, the school placed the onus to conserve on the consumer, ignored industrial energy use, and had avoided drastic measures. In revisiting these events, their lead-up and afterlife, this paper historicizes a now-central tenet of energy policy. [ABSTRACT FROM AUTHOR]

In view of the prominent and intractable problems of frequent high temperature alarms of the communication equipment and high energy consumption of air conditioners in Zhengzhou communication outdoor cabinets, a temperature control system with heat pipe as the main part and air conditioner as the auxiliary part is proposed in this paper. A prototype is developed and its applications are discussed. The annual field test shows the system works well, and it has a remarkable energy saving efficiency. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, the implementation of clustering and routing protocols has been crucial in prolonging the network's operational duration by conserving energy. However, the challenge persists in efficiently optimizing energy usage to maximize the network's longevity. This paper presents CHHFO, a new protocol that combines a fuzzy logic system with the collaborative Harris Hawks optimization algorithm to enhance the lifetime of networks. The fuzzy logic system utilizes descriptors like remaining energy, distance from the base station, and the number of neighboring nodes to designate each cluster head and establish optimal clusters, thereby alleviating potential hot spots. Moreover, the Collaborative Harris Hawks Optimization algorithm employs an inventive coding mechanism to choose the optimal relay cluster head for data transmission. According to the results, the network throughput, HHOCFR is 8.76%, 11.73%, 8.64% higher than HHO-UCRA, IHHO-F, and EFCR. In addition, he energy consumption of HHOCFR is lower than HHO-UCRA, IHHO-F, and EFCR by 0.88%, 39.79%, 34.25%, respectively. [ABSTRACT FROM AUTHOR]

This paper presents the findings of fifteen energy audits conducted on industrial sites in Canada's Greater Toronto Area (GTA). The audits covered a range of industries including food processing, packaged goods, and finishing processes (powder-coating). The primary focus of the audits was to analyze the natural gas consumption and the performance of major-gas-consuming equipment. The audits identified natural-gas-consuming equipment that could be optimized to yield energy and operational cost savings and greenhouse gas (GHG) reduction opportunities. Food production plants' energy intensity ranges from 5.59 m3/ft2 to 17.73 m3/ft2. Therefore, there is a significant opportunity to improve energy consumption through better technology integration. The results of the audits indicate a trend of an increase in the percentage of non-productive consumption with non-productive time. The proposed energy-saving measures include reducing non-productive natural gas consumption, gas-fired equipment tune-up, optimizing boiler loads, and reducing oven exhaust by using variable frequency drives (VFDs). The findings of this study could be used to develop a demand-side management program specifically for small- and medium-sized industrial facilities in the Greater Toronto Area and other parts of Canada. [ABSTRACT FROM AUTHOR]

Aiming at the problems of poor scheduling flexibility and insufficient carbon emission reduction capacity of the current integrated energy system, this paper proposes an optimization scheduling model of integrated energy demand response that combines source-load synergy with reward and punishment stepped carbon trading mechanism. Firstly, the integrated energy system operation architecture including electricity-heat-cooling energy was constructed to harmonize the energy generation side and consumption side and effectively improve the multi-energy complementary capability of the system. Secondly, the reward and punishment stepped carbon trading mechanism is established by combining the initial carbon quota allocation method and the actual carbon emission calculation theory, so that environmental friendliness and economic sustainability are effectively improved. Finally, to minimize the system operating cost, an integrated demand response optimal dispatch model that considers the characteristics of electric, thermal and cooling loads is constructed to determine the optimal dispatch scheme for the integrated energy system. The results of the calculation example indicate that the proposed integrated demand response model has the function of peak reduction and valley correction, energy conservation and carbon reduction, and provides a feasible solution for the integrated energy system optimal scheduling. [ABSTRACT FROM AUTHOR]

Industry 4.0 is a term used to refer to the fourth industrial revolution, characterized by the introduction of new technologies, such as the Internet of Things, Big Data, and artificial intelligence (AI). As the number of connected devices in industrial settings grows, energy optimization of such sensors becomes increasingly essential. This paper proposes an energy optimization framework for sensor nodes in Industry 4.0. The framework is based on energy efficiency, energy conservation, and energy harvesting principles. It is designed to optimize the energy consumption of sensor nodes while maintaining their performance. The framework includes dynamic power management, scheduling, and harvesting techniques to reduce energy consumption while maintaining performance. In addition, the framework provides a comprehensive approach to energy optimization, including advanced analytics and AI to predict energy consumption and optimize energy use. The proposed model reached 96.93% sensitivity, 91.36% false discovery rate, 11.28% false omission rate, 90.12% prevalence threshold, and 91.24% threat score. The proposed framework is expected to improve the performance of sensor nodes in Industry 4.0, enabling increased efficiency and cost savings. [ABSTRACT FROM AUTHOR]

In recent times, software-defined networking (SDN) has garnered significant attention due to its approach of separating the control plane from the data plane. This abstraction allows managers to have a centralized perspective on the network, which in turn enables them to control traffic flow and routing policies dynamically without configuring individual devices. The increased adoption of SDN has resulted in the need to optimize energy consumption without compromising network performance. Creating an energy-efficient solution presents a challenge due to the intricate process of finding the right equilibrium between network performance and energy conservation. This article examines various techniques for achieving energy efficiency in SDN and classifies them into three categories - software-based, hardware-based, and hybrid approach. These categories are further divided into their subcategory. Furthermore, a comprehensive exploration will be conducted to delve into the benefits and drawbacks of each energy efficiency approach, followed by an in-depth comparative analysis. The article also discusses the research issues and challenges associated with each technique. Finally, the paper provides future prospects for investigating energy efficiency approaches in SDN, which are expected to yield substantial benefits for upcoming researchers in this domain. [ABSTRACT FROM AUTHOR]

The paper aims to present the need and the importance of using efficiently the energy and finding new ways to improve the transport based on renewable energy. The paper is based on a large number of official information sources which are structured and presented in the author's opinion. The main results emphasize that the Danube region is a large river basin and ecological corridor requiring a regional approach to nature conservation, spatial planning and water management. The environmental impact of transport links, tourist constructions or new energy production facilities must also be considered. Transport policy has been given a new direction: achieving a 'sustainable through flexibility' system, which means organizing transport in such a way as to optimize energy consumption. The development of the national transmission system shall be carried out in accordance with the requirements of conservation and environmental protection and the rational use of energy. The protection of human life and the environment is a priority in all transport-related relations. [ABSTRACT FROM AUTHOR]

The global aluminium industry faces a serious challenge in reducing greenhouse gas emissions as the demand for aluminium continues to increase. The aluminium industry has a responsibility to streamline its energy consumption, especially in the production process. There have been many studies discussing energy consumption performance in the industry. However, most of them only discuss energy saving partially, without involving energy consumption with various items produced. This paper proposes an energy savings measurement in the manufacturing industry. An energy baseline consumed per unit volume has been developed using the equivalent volume method with an energy management control system (EMCS). The study takes a case example from the automotive--aluminium component industry. The steps taken in the study are: examining the production process, converting the production volume to equivalent, calculating the energy consumption ratio, developing an energy baseline, simulating the savings performance, and then proposing an EMCS with key performance indicators (KPI) for sustainability. The results show that the development of a baseline using the ratio of energy and an equivalent volume of production gives a better data correlation with an R² value close to one. From the baseline, the bestdemonstrated performance (BDP) can be used as a reference to set energy goals. Furthermore, the data and the deviant deleted have the same baseline value. They differ in energy reduction goal percentages. The practical application of this study is not only in the manufacturing industry but in other industries as well, such as building management. This study contributes to energy savings achieved with EMCS. [ABSTRACT FROM AUTHOR]

Hybrid tractors (HT) are regarded as the efficient agricultural machine due to their energy conservation performance and faster torque response to deal with load fluctuations. However, the strategy to allocate the battery and fuel energy for demand power should be discussed. In this paper, an on-line management strategy of the HT is proposed to optimize the energy consumption of engine and motor and to reduce torque ripple for power units. A new architecture for replacing power shift and continuously variable transmission technology is proposed. Then, the modified equivalent consumption minimization strategy (ECMS) is used to optimize the torque distribution in which the equivalent factor is further calculated for the real-time process. Besides, the modification of ECMS in variable working conditions can effectively analyse the torque distribution between the motor and engine. The numerical test is implemented that the effectiveness of the proposed energy strategy is validated in plowing conditions. The consequences indicated that the proposed power distribution strategy can adaptively allocate the torque demand according to the fluctuation load. Comparing with the traditional rule-based strategy, the proposed strategy can reduce 6.2% of the energy, and decrease torque ripple with the proposed tractor architecture. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs), constrained by limited resources, demand routing strategies that prioritize energy efficiency. The tactic of cooperative routing, which leverages the broadcast nature of wireless channels, has garnered attention for its capability to amplify routing efficacy. This manuscript introduces a power-conscious routing approach, tailored for resource-restricted WSNs. By exploiting cooperative communications, we introduce an innovative relay node selection technique within clustered networks, aiming to curtail energy usage while safeguarding data dependability. This inventive methodology has been amalgamated into the Routing Protocol for Low-Power and Lossy Networks (RPL), giving rise to the cooperative and efficient routing protocol (CERP). The devised CERP protocol pinpoints and selects the most efficacious relay node, ensuring that packet transmission is both energy-minimal and reliable. Performance evaluations were executed to substantiate the proposed strategy, and its practicality was examined using an Arduino-based sensor node and the Contiki operating system in real-world scenarios. The outcomes affirm the efficacy of the proposed strategy, outshining the standard RPL concerning reliability and energy conservation, enhancing RPL reliability by 10% and energy savings by 18%. This paper is posited to contribute to the evolution of power-conscious routing strategies for WSNs, crucial for prolonging sensor node battery longevity while sustaining dependable communication. [ABSTRACT FROM AUTHOR]

Computational methods play a significant role in reducing energy consumption in cities. Many different sensor networks (e.g., traffic intensity sensors, intelligent cameras, air quality monitoring systems) generate data that can be useful for both efficient management (including planning) and reducing energy usage. Street lighting is one of the most significant contributors to urban power consumption. This paper presents a summary of recent attempts to use computational methods to reduce energy usage by lighting systems, with special focus on graph-based methods. Such algorithms require all the necessary data to be integrated, in order to function properly: this task is not trivial, and is very time-consuming; therefore, the second part of the paper proposes a novel approach to integrating urban datasets and automating the optimisation process. In two practical examples, we show how spatially triggered graph transformations (STGT) can be used to build a model based on the road network map, sensor locations and street lighting data, and to introduce semantic relations between the objects, including utilisation of existing infrastructure, and planning of development to maximise efficiency. [ABSTRACT FROM AUTHOR]

In this paper, the window-opening behavior in a three-star green building with an operation mark in Ningbo was investigated. Four single offices facing south were selected, and the measurement lasted 20–40 days in the cooling season. An analysis of the relationship between window use and environmental factors was assessed by monitoring the occupancy state, the window action and window state, the time, and the temperature and humidity. A statistical analysis method was conducted to reveal the similarities and differences in window use among different occupants. The main findings were as follows: The window adjustment behaviors of different people vary significantly. In terms of adjustment time, there are two modes of behaviors. In addition, the occupancy state had a great impact on window action. Moreover, some people prefer to open the windows in the morning and close the windows at departure time, However, some of them prefer to open the windows at departure time and close the windows at the arrival time. Some irrational window opening behaviors were found in this research. Through correlation analysis, it was shown that the longer time the occupants were in the office, the higher window-opening duration and window-opening frequency would be. If the window was closed at arrival time, the total opening duration of window was significantly reduced. Also, window opening duration and closing duration are proportional to each other. With the help of principal component analysis (PCA) of the 12 features that affected window adjustment, the correlation between the window opening behaviors and the features could be clearly illustrated. A stochastic model of window-opening behavior based on logistics regression and uncertainty analysis was used in this paper. The cooling energy consumption of the stochastic model is 99.9% higher than the energy consumption generated by a fixed number of air changes, and the average energy consumption exceeds the fixed value by more than 21%. The findings of this study have certain guiding significance for promoting energy conservation by occupants' behaviors in green buildings in this region. [ABSTRACT FROM AUTHOR]

Quadrotor unmanned aerial vehicles (UAVs) have emerged as ubiquitous and agile robots and data carriers within the framework of the future Internet of Things (IoT) and mobile wireless networks. Yet, the insufficient onboard battery necessitates the optimization of energy consumption for both the UAV and IoT devices while ensuring that communication requirements are met. This paper therefore proposes a more accurate and mathematically tractable model for characterizing a UAV's energy consumption concerning desired trajectories. This nonlinear model takes into account the UAV's dynamics, brushless direct current (BLDC) motor dynamics, and aerodynamics. To optimize the communication time between IoT devices and the UAV, IoT devices are clustered using a modified GAK-means algorithm, with dynamically optimized communication coverage radii. Subsequently, a fly–circle–communicate (FCC) trajectory design algorithm is introduced and derived to conserve energy and save mission time. Under the FCC approach, the UAV sequentially visits the cluster centers and performs circular flight and communication. Transitions between cluster centers are smoothed via 3D Dubins curves, which provide physically achievable trajectories. Comprehensive numerical studies indicate that the proposed trajectory planning method reduces overall communication time and preserves UAV battery energy compared to other benchmark schemes. [ABSTRACT FROM AUTHOR]

The electrification of isolated or rural areas brings with it technical, economic, and social challenges that differentiate the operation of these networks compared to the traditional operation of large electrical power systems, such as the dependence of air or river transport on fuel for the supply of generation plants, the absence of individual measurement and the obsolete infrastructure of the distribution networks. Therefore, this paper proposes a hybrid methodology for studying a Colombian case, analyzing the development of programs for rational electricity use and energy efficiency in isolated areas. These first steps are related to the diagnosis of the current conditions of the power network, the identification of actors that can influence the regulation of the electricity service in the area, and the proposal of mechanisms that allow promoting the rational and efficient use of the electricity. [ABSTRACT FROM AUTHOR]

A wet electrostatic precipitator (WESP) is typically installed downstream of wet flue gas desulfurization (WFGD) to remove fine particles and sulfuric acid mists from flue gases in coal-fired power plants. The emission reduction characteristics of multiple pollutants and the energy consumption data of 214 sets of WESPs (94 sets of metal plate WESPs, 111 sets of conductive Fiber Reinforced Plastic WESPs, and 9 sets of flexible plate WESPs) were tested and analyzed, and the results showed that: WESPs had a high removal efficiency on PM, PM2.5, SO3, droplets and Hg, and mostly concentrated in ≥75%, ≥70%, ≥60%, ≥70% and ≥40%, respectively. The outlet pollutant concentrations were mostly concentrated in ≤5 mg/m3, ≤3 mg/m3, ≤5 mg/m3, ≤15 mg/m3 and ≤5 μg/m3, respectively. Specific power consumption and specific water consumption were concentrated in the range of 0.5~2.5 × 10−4 kWh/m3 and ≤10 × 10−6 t/m3. The correlation analysis of multiple pollutant's removal performance was studied and the quantitative evaluation index requirements of high efficiency WESPs were determined in this paper. The high efficiency indexes of WESPs, such as PM emission concentration, SO3 emission concentration, PM removal efficiency, SO3 removal efficiency, pressure drop, air leakage rate and specific power consumption, were ≤2.50 mg/m3, ≤2.50 mg/m3, ≥90%, ≥85%, ≤200 Pa, ≤0.5% and ≤1.3 × 10−4 kWh/m3, respectively. The high efficiency indexes of specific water consumption for metal plate WESPs and FRP WESPs were ≤2.50 and ≤0.66 × 10−6 t/m3, respectively. This study can provide valuable reference for the following energy conservation and efficiency improvement of ultra-low emission units. [ABSTRACT FROM AUTHOR]

The escalating issue of global climate change necessitates urgent measures to reduce carbon emissions globally. Within this context, the construction industry emerges as a critical sector to address given its high energy consumption, substantial CO2 emissions, and low utilization rate. Therefore, it is pivotal to foster energy conservation and reduce emissions in this sector. To this end, this paper delineates two primary objectives: (1) identifying optimal research methodologies and index parameters for evaluating carbon emission efficiency in the construction industry, and (2) assessing the variance in carbon emission efficiency at disparate stages and regions. Leveraging the Malmquist index, we scrutinize the carbon emission data from 30 Chinese provinces spanning from 2010 to 2019. Our findings indicate a geographical dichotomy in China's construction industry's carbon emission efficiency—lower in the west and higher in the east. Additionally, this study delves into the distinguishing features of emission efficiency alterations across regions, the main influencing factors, and avenues for enhancement. Subsequently, it proposes policy recommendations tailored to the unique attributes of various regions and the overarching framework. [ABSTRACT FROM AUTHOR]

With the advancement of carbon peaking and carbon neutrality goals, microgrid clusters have attracted widespread attention due to their high stability and energy efficiency. This article proposes a scheduling architecture for microgrid clusters that integrates blockchain smart contracts, consensus mechanisms, and encryption technologies to address the issues of data trust, privacy protection, and security reliability in microgrid clusters. An economic adjustment model for microgrid clusters is constructed that combines economic and environmental objectives. Finally, based on the RPBFT (Rotating Proof of Believability) algorithm and group architecture of FISCO BCOS blockchain technology, an economic scheduling method for microgrid clusters is designed. The authors built a microgrid cluster model on the FISCO BCOS blockchain platform and conducted experiments on the effectiveness, economy, fault tolerance, and scalability of economic scheduling methods. The experimental results showed that the economic scheduling method proposed in this paper can effectively reduce the risk of nodes tampering with data in a microgrid cluster system, ensure the privacy of submicrogrids, and support the deployment of large‐scale microgrid clusters, the realization of multiparty collaborative autonomy and the stable, low‐carbon, economic operation of microgrid clusters. [ABSTRACT FROM AUTHOR]

In this paper, we have investigated the implications of the threshold effect of changes in FDI inflows for the nexus between energy consumption and economic growth in eight under-researched sub-Saharan African countries for the period 1971--2016. The countries are Benin, Congo, Kenya, Nigeria, Senegal, South Africa, Sudan, and Zambia. Using the lag-augmented VAR (LAVAR) model (corrected for cross-sectional dependence), we develop an empirical framework tightly linked to the endogenous growth model that allows for a threshold effect of changes (strength and weakness) in FDI inflows on the nexus. Our findings show that the FDI inflows matter for the causal link between energy consumption and economic growth in some countries, although, for the cross-section as a whole, our bootstrap simulation supports the neutrality hypothesis. The overall results suggest that an energy demand policy, such as an energy conservation policy, should not cause any significant adverse side-effects to economic growth in those sub-Saharan African countries. Policy implications of the threshold effect for the nexus for individual sub-Saharan African countries are also provided. [ABSTRACT FROM AUTHOR]

Improving agricultural energy efficiency is essential in reducing energy consumption and achieving agricultural sustainable development. This paper aims to measure the agricultural total-factor energy efficiency in China rather than the partial-factor energy efficiency while taking full account of regional heterogeneity and to investigate the driving factors of agricultural total-factor energy efficiency. The empirical results showed that the average value of agricultural total-factor energy efficiency is 0.814 in China, and the technological gap ratio is 0.853. The regional difference in agricultural total-factor energy efficiency was quite obvious. Higher agricultural energy inputs are associated with higher agricultural total-factor productivity. The total value of potential agricultural energy savings in 30 provinces of China reached 1704.41 billion tons of standard coal. In terms of the absolute amount of agricultural energy saving, the amount was largest in the low-energy-input area, which was 113.87 million tons of standard coal, accounting for 66.81% of the total potential saving amount. Furthermore, we used the Tobit model to analyze the influencing factors of agricultural total-factor energy efficiency. We found that the proportion of agriculture to GDP has a positive impact on agricultural total-factor energy efficiency, while the per capita income of farmers, fiscal support for agriculture, the illiteracy rate of farmers, agricultural labor input, and agricultural capital stock have a negative impact on agricultural total-factor energy efficiency. Finally, we proposed policy implications in terms of agricultural technological progress, agricultural infrastructure, technical training, etc. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) enable communication among sensor nodes and require efficient energy management for optimal operation under various conditions. Key challenges include maximizing network lifetime, coverage area, and effective data aggregation and planning. A longer network lifetime contributes to improved data transfer durability, sensor conservation, and scalability. In this paper, an enhanced dual-selection krill herd (KH) optimization clustering scheme for resource-efficient WSNs with minimal overhead is introduced. The proposed approach increases overall energy utilization and reduces inter-node communication, addressing energy conservation challenges in node deployment and clustering for WSNs as optimization problems. A dynamic layering mechanism is employed to prevent repetitive selection of the same cluster head nodes, ensuring effective dual selection. Our algorithm is designed to identify the optimal solution through enhanced exploitation and exploration processes, leveraging a modified krill-based clustering method. Comparative analysis with benchmark approaches demonstrates that the proposed model enhances network lifetime by 23.21%, increases stable energy by 19.84%, and reduces network latency by 22.88%, offering a more efficient and reliable solution for WSN energy management. [ABSTRACT FROM AUTHOR]

In this paper, the potential for conserving energy has been used inside the collaborative network. The purpose of this work is to examine a model of a collaborative mobile cloud with the objective of lowering the total energy consumption of network nodes. This model is made up of many different network nodes, all of which collaborate with one another to build the network. We performed a theoretical examination into the quantity of energy that is used by the nodes when they are functioning as part of the network. In addition, a user grouping and scheduling-based system was established in order to establish when and how users should participate in the creation of the network. This was done so that the system could identify when and how users should contribute to the construction of the network. The proposed methodology took into consideration both the user and the base station components, and it made an effort to strike a balance between reducing the amount of energy that was consumed and ensuring that everyone was treated in an equitable manner. Even with higher delay values, the collaborative method may minimise energy use. The suggested approach uses slower but more energy-efficient nodes by increasing the allowable latency, which reduces energy usage and benefits from the diversity of nodes. The results of the simulation are presented by our proposed method from the perspective of user fairness as well as presenting the advantages of conserving energy that are associated with employing the collaborative strategy. [ABSTRACT FROM AUTHOR]

This paper uses SketchUp and OpenStudio to design and optimize the multiperformance parameters of the near-zero energy consumption residential building scheme stage. By establishing a basic model, the performance parameters such as insulation thickness, typical outer window, window-to-wall ratio, and their contribution rates within the threshold range are optimized for energy conservation; simulate the energy consumption of the determined multiperformance parameter combination scheme, select the most energy-saving scheme, and calculate its energy-saving contribution rate; calculate the life cycle cost of the above schemes, select the scheme with the lowest cost, and analyze its economic benefits; select energy-saving cost and economic benefit, and calculate energy-saving contribution rate and economic benefit. Finally, through the comparative analysis of the design and test data, this paper concludes that EnergyPlus will optimize the multiperformance parameters of the near-zero energy consumption residential building scheme stage. At the same time, the multiobjective optimization method and process of the passive energy-saving technology of the near-zero energy consumption building proposed in this paper, as well as the technology combination template under different needs, provide a reference for the selection of the technology path. [ABSTRACT FROM AUTHOR]

The Non‐Volatile Random Access Memory (NVRAM) is recently identified as the most upcoming main memory technology in Embedded and Internet of Things (IoT) systems due to its appealing qualities like zero static power consumption and great memory cell density. On the other hand, most NVRAMs have low write endurance due to workload‐induced write variance, leading to more write activity at a few blocks of memory than the other blocks. Improving the endurance of NVRAM on embedded architectures is very critical due to the limited constraints of Embedded architectures. The main goal of this paper is to address the complexity of NVRAM designs, with a focus on embedded boards, and to create a prototype that enhances NVRAM endurance using a compression technique. Furthermore, this framework is not particular to a single NVRAM device. An Instruction Per Cycle based Dynamic Pattern Compression (IPC_DPC) model is developed to address NVRAM's high write latency and low endurance. The primary goal of the proposed IPC_DPC model is to minimize the energy utilization and latency of heavy workloads during the execution by pre‐determining the workload's instruction cycles. The IPC_DPC model initially divides the Low IPC and High IPC workloads and then compresses the workloads dynamically based on their IPC values compared to the threshold factor. As a result, IPC_DPC improves the compression ratio and reduces the write latencies associated with traditional compressors, significantly reducing the write activity and improving the lifetime of NVRAM. We implemented the proposed IPC_DPC model using GEM5 with a Raspberry Pi board and took IoMT, MiBench, and EEMBC benchmarks for evaluation. Compared to FPC, BDI, FNW, and DFPC models, the proposed IPC_DPC model is shown to be more efficient in terms of compression ratio (56.05%) and energy reduction (17%). [ABSTRACT FROM AUTHOR]

Benefiting from advanced satellite payload technologies, edge computing servers can be deployed on satellites to achieve orbital computing and reduce the mission processing delay. However, geostationary Earth orbit (GEO) satellites are hindered by long-distance communication, whereas low Earth orbit (LEO) satellites are restricted by time windows. Relying solely on GEO or LEO satellites cannot meet the strict quality of service (QoS) requirements of on-board missions while conserving energy consumption. In this paper, we propose a computation offloading strategy for GEO/LEO hybrid satellite networks that minimizes total energy consumption while guaranteeing the QoS requirements of multiple missions. We first innovatively transform the on-board partial computation offloading problem, which is a mixed-integer nonlinear programming (MINLP) problem, into a minimum cost maximum flow (MCMF) problem. Then, the successive shortest path-based computation offloading (SSPCO) method is introduced to obtain the offloading decision in polynomial time. To evaluate the effectiveness and performance of SSPCO, we conduct a series of numerical experiments and compare SSPCO with other offloading methods. The experimental results demonstrate that our proposed SSPCO outperforms the reference methods in terms of total energy consumption, QoS violation degree, and algorithm running time. [ABSTRACT FROM AUTHOR]

The increasing price of and demand for energy have prompted several organizations to develop intelligent strategies for energy tracking, control, and conservation. Demand side management is a critical strategy for averting substantial supply disruptions and improving energy efficiency. A vital part of demand side management is a smart energy management system that can aid in cutting expenditures while still satisfying energy needs; produce customers' energy consumption patterns; and react to energy-saving algorithms and directives. The Internet of Things is an emerging technology that can be employed to effectively manage energy usage in industrial, commercial, and residential sectors in the smart environment. This paper presents a smart energy management system for smart environments that integrates the Energy Controller and IoT middleware module for efficient demand side management. Each device is connected to an energy controller, which is the inculcation of numerous sensors and actuators with an IoT object, collects the data of energy consumption from each smart device through various time-slots that are designed to optimize the energy consumption of air conditioning systems based on ambient temperature conditions and operational dynamics of buildings and then communicate it to a centralized middleware module (cloud server) for management, processing, and further analysis. Since air conditioning systems contribute more than 50% of the electricity consumption in Pakistan, for validation of the proposed system, the air conditioning units have been taken as a proof of concept. The presented approach offers several advantages over traditional controllers by leveraging real-time monitoring, advanced algorithms, and user-friendly interfaces. The evaluation process involves comparing electricity consumption before and after the installation of the SEMS. The proposed system is tested and implemented in four buildings. The results demonstrate significant energy savings ranging from 15% to 49% and highlight the significant benefits of the system. The smart energy management system offers real-time monitoring, better control over the air conditioning systems, cost savings, environmental benefits, and longer equipment life. The ultimate goal is to provide a practical solution for reducing energy consumption in buildings, which can contribute to sustainable and efficient use of energy resources and goes beyond simpler controllers to address the specific needs of energy management in buildings. [ABSTRACT FROM AUTHOR]

This study provides a viable path to save energy by means of e-commerce development. Taking the national e-commerce demonstration cities (NEDC) pilots policy implemented in China as a quasi-natural experiment, based on the city panel data from 2006 to 2019, this study applies the multi-period difference-in-difference (DID) method to evaluate the effect of NEDC on energy saving in pilot cities. The empirical results suggest that the NEDC policy obviously contributes to energy conservation. The treated cities reduced energy consumption by 14.2% as a result of the implementation of NEDC, relative to the untreated cities. The conclusions remain valid after conducting robustness tests such as placebo test, instrumental variables regression, propensity score matching-difference-in-difference (PSM-DID), and synthetic difference-in-difference (SDID). The NEDC achieves energy-saving effects through technological innovation, industrial restructuring, and economic agglomeration. Furthermore, the heterogeneity analysis indicates that, in cities with high levels of human capital, well-developed information infrastructure, non-resource-based cities, and favorable business environments, the impact of NEDC on energy saving is more significant. Analysis of spatial effects shows that the implementation of NEDC has negative externalities, increasing energy consumption in the surrounding area. In the context of the digital economy, this paper presents new insights on the relationship between e-commerce and energy consumption and provides policy direction for countries looking for energy-saving solutions. [ABSTRACT FROM AUTHOR]

With the emergence of various Internet of Things (IoT) technologies, energy-saving schemes for IoT devices have been rapidly developed. To enhance the energy efficiency of IoT devices in crowded environments with multiple overlapping cells, the selection of access points (APs) for IoT devices should consider energy conservation by reducing unnecessary packet transmission activities caused by collisions. Therefore, in this paper, we present a novel energy-efficient AP selection scheme using reinforcement learning to address the problem of unbalanced load that arises from biased AP connections. Our proposed method utilizes the Energy and Latency Reinforcement Learning (EL-RL) model for energy-efficient AP selection that takes into account the average energy consumption and the average latency of IoT devices. In the EL-RL model, we analyze the collision probability in Wi-Fi networks to reduce the number of retransmissions that induces more energy consumption and higher latency. According to the simulation, the proposed method achieves a maximum improvement of 53 % in energy efficiency, 50 % in uplink latency, and a 2.1 -times longer expected lifespan of IoT devices compared to the conventional AP selection scheme. [ABSTRACT FROM AUTHOR]

Future power systems will face more extreme operating condition scenarios, and system emergency dispatch will face more severe challenges. The use of distributed control is a well-designed way to handle this. It enables multi-energy complementation by means of autonomous communication, which greatly improves the flexibility of the grid. First, in the context of global energy conservation and emission reduction, this paper adopts the energy usage method of "renewable energy is the main source of energy, supplemented by thermal power and energy storage" to reduce the system abandoned wind (light) rate while supplementing the energy storage capacity. Second, a consensus algorithm is added to the system while considering the coordination between thermal units and energy storage. An "interface" for autonomous communication between thermal units and energy storage is created using the incremental cost of each agent. To address the recurring issue of power imbalance during emergency dispatch of the system, the consensus algorithm is enhanced so that the communication interval varies with the unit rate. This is based on the climbing characteristics of each thermal power unit. Finally, the effectiveness of the proposed method is verified in an IEEE-30 bus system. [ABSTRACT FROM AUTHOR]

As commercial transportation complexes, expressway service buildings have large passenger flow and a poor energy-saving effect, and have become the focus of energy conservation and emissions reduction efforts in the transportation field. At the same time, the particularity of the function determines that it is within the scope of no municipal supporting facilities, which renders them typical energy island-type buildings. This paper takes the expressway service buildings in a cold area as the research object, and carries out the correlation and partial correlation analysis of the factors influencing the operating energy consumption of the air-conditioning system. For the analysis of factors affecting the energy consumption of expressway service buildings during the operation period, considering that most of the service buildings are in the form of heating and cooling air conditioners, this paper chooses to represent the "refrigeration period" with a more obvious degree of influence. At the same time, during the operation period, because the ontological characteristics have been determined according to the analysis results, the outdoor meteorological characteristics are the main factors affecting the energy consumption of expressway service buildings. These include the dry bulb temperature and horizontal plane solar irradiance index, as well as the indoor comprehensive environment parameters: temperature, CO2 concentration index, indoor personnel density index. Based on the above analysis, a low energy consumption operation strategy for the air-conditioning system is proposed. The results of this article are of great significance for the construction of energy consumption models for expressway service buildings and the adoption of low energy consumption strategies. [ABSTRACT FROM AUTHOR]

In recent decades, significant changes have occurred in the consumer lifestyle and energy consumption structure. In order to foster a more holistic understanding of how residential consumers use energy in their everyday life and how it affects energy efficiency, individual data about energy-related behaviour in six primary areas, namely, housing, mobility, diet, consumption, leisure activities, and information, were studied. Specifically, the objective of this study is to investigate energy efficiency behaviour based on residential consumers' lifestyles. An exploratory pilot study with a total of 50 respondents was carried out in month of July. Data were collected from residential consumers from six states in Peninsular Malaysia and were analysed using the Partial Least Square Structural Equation Modelling approach. The result showed that consumption, housing, and information are the dominant direct contributors to energy efficiency. By understanding these lifestyles, researchers and policymakers can better understand consumer energy consumption behaviour and design targeted interventions to encourage energy efficiency and conservation. The paper highlights the need for further research on consumer lifestyles and their contribution to energy efficiency. It also provides findings from this study that was used to refine the research tools for future research. [ABSTRACT FROM AUTHOR]

Due to the viscoelasticity of rubber materials, hysteresis loss due to deformation is the main reason for the rolling resistance of high-speed rubber tracks. Since the structure and material of high-speed rubber track assemblies are different from traditional tires and metal tracks, the rolling resistance theory of traditional wheeled and tracked vehicles is not applicable. Therefore, in order to determine the rolling resistance scientifically and accurately, the mechanism research of the rolling resistance of high-speed rubber track assembly is the key to the design of high-speed rubber crawler vehicles. In this paper, the stress–strain characteristics of rubber track under the action of compression, tension, bending, and driving were studied. The strain load spectrum of rubber tracks was established, and the strain cyclic load was extracted by the rainflow method. The temperature model of the rubber track was developed based on its dynamic characteristics. On the basis of energy conservation, the hysteresis loss of rubber is equivalent to the energy consumption of rolling resistance, and the theoretical model of rolling resistance of high-speed rubber track assembly is established. In accordance with the model above, the key influencing factors and changing trends of rolling resistance are analyzed, which provides a theoretical basis for the performance optimization of high-speed rubber track assembly. [ABSTRACT FROM AUTHOR]

Axion clumps in an external magnetic field can emit electromagnetic radiation which causes them to decay. In the presence of a plasma, such radiation can become resonant if the clump frequency matches the plasma frequency. Typically, the decay or back-reaction of the clump is ignored in the literature when analyzing such radiation. In this paper we present a self consistent, semi-analytic approach which captures axion backreaction using energy conservation. We find that inclusion of back-reaction changes the clump frequency over time enabling clumps with a range of different initial frequencies to become resonant at some point in their time evolution. [ABSTRACT FROM AUTHOR]

The paper investigates the association between foreign direct investment (fdi) and energy consumption within the purview of trade liberalization and economic growth from 1971 to 2014 in Bangladesh, employing the Auto Regressive Distributive Lag (ardl) bounds testing approach. The study result depicts a negative impact of fdi on energy consumption in both the long and short run. Moreover, the study results persist robust to alternative measurements and estimators. Furthermore, a unidirectional causal relationship moving from energy consumption to foreign direct investment supports the institutional strength of the energy sector. Therefore, policymakers should undertake a pragmatic policy for the best utilization of fdi in the energy sector and reinforce local firms’ absorptive capability to internalize fdi-centric information spillover in energy conservation. [ABSTRACT FROM AUTHOR]

The idea of designing a controller for electrical energy management is due to the need for energy saving and intelligent management of the consumed energy. The article presents the designed and studied device designed to limit the consumption of electrical energy within one day and the magnitude of the load current in single-phase circuits. Thus, the consumer (household consumer) of electrical energy can use the energy at time and in amount at will, but within pre-set limits. The paper discusses the principle of operation of the device for power consumption management, its main characteristics, and applications. [ABSTRACT FROM AUTHOR]

Design priorities for tall and supertall buildings have for some time shifted to achieving more energy efficiency to address the energy needs of the increasing global population. Engineers and architects aim to achieve energy conservation through active and passive approaches, pursuing technological innovations and adopting climate-responsive design. Because of the green movement currently dominating the building industry, tall buildings that need a massive amount of energy to build and operate, and the practical desire to switch from non-renewable to clean renewable energy resources, intense attention has been given to the energy efficiency of tall buildings in the recent past. Due to the vast array of energy-efficient design features, equipment, and applications available now, it is timely to examine the pros and cons of these issues. This review paper is an attempt to comprehensively present and deliberate these issues. It illustrates and discusses the concepts and applications through a few case studies from several continents worldwide. The review shows that the design of tall buildings focusing on energy conservation is an evolutionary process and there is a need for further research about how to face the associated challenges to improve energy efficiency by developing creative solutions and strategies, as well as applying additional innovative technologies. [ABSTRACT FROM AUTHOR]

This editorial paper tackles the issue of the consumer attitudes toward energy reduction and changing energy consumption behaviors. This topic is of special relevance today as Europe faces an unprecedented energy crisis as a result of diverting from Russian supplies of oil and gas due to the war in Ukraine. For many years now, Europe has relied upon cheap and affordable Russian oil and gas (in fact, the European Green Deal and the strategy for the decarbonization of the economy by 2030 were indirectly based on it), but the transition to the renewable future now appears to be jeopardized. As energy prices are soaring globally, it is not yet clear whether this would have an effect on significantly changing consumer behavior and increasing energy efficiency and security as many consumers are reluctant to change their old habits and are used to having their energy on demand and for any possible occasion. However, changing energy consumption behaviors would be beneficial not only for handling the current energy crisis but also for setting the long-term trends with respect to energy saving, which is crucial for fighting global warming and climate change while sustaining economic growth. [ABSTRACT FROM AUTHOR]

Electricity is used in educational buildings, and there are now numerous attempts to reduce consumption, achieve sustainability, and protect the environment. This paper aims to study energy consumption, identify opportunities to rationalize energy consumption, and propose solutions at Sulaiman Al-Rajhi University in the Kingdom of Saudi Arabia in order for the university campus to become sustainable. The results showed that total annual electrical consumption totaled 13,859 MWh in 2021. The air conditioning system, other devices, and lighting have the percentage of consumption 79, 14, and 7% of the total, respectively. Electricity consumption intensity was approximately 145–155 kWh/m2, and the per capita intensity was approximately 12,987–16,351 kWh, in the period 2017–2021. The price of the electrical energy generated on the university campus ranged between 0.3 and 0.53 SR/kWh in 2021, while the electricity tariff from the grid for educational buildings was 0.18 SR/kWh. This means that the public grid was 50% cheaper than campus-generated electricity. At the price of energy generated by generators, the total simple payback time (SPBT) for the suggested energy conservation measures (ECMs) is 4.13 years, whereas the SPBT is 8.96 in the case of the consumption of the electricity supplied by the national grid. The environmental benefits of the proposed ECMs were also identified. [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

The complex energy conversion and the volatility of renewable energy/load bring great challenges to the operation of the park‐level integrated energy system (PIES). To overcome this challenge, this paper proposes a multi‐timescale flexible dispatching method to fully exploit the flexibility of PIES in the energy cascade utilization mode. The cascade utilization model for energy flow is firstly established to analyse the coupling and complementary of heterogeneous energy. On this basis, the supply‐demand general equations of multi‐energy flexibility are proposed, which accurately quantify the ability to cope with uncertainty through mutual flexibility. Through coordinated complementation and mutual exchange of multi‐grade flexibility, the system realizes the suppression of random power fluctuations. The scheduling model includes day‐ahead dispatch and intraday multi‐time scale dispatch, which can satisfy the adjustment speed requirements of different energy. Numerical results demonstrate that the proposed method effectively enhances the flexibility and economy of system operation. The flexible demand for energy of all grades can be satisfied. Compared with the flexible dispatch in the triple energy supply structure, the operating cost is reduced by 9.07%. [ABSTRACT FROM AUTHOR]

Emissions from road traffic contribute to climate change. One approach to reducing the carbon footprint is providing eco-driving feedback so that drivers adapt their driving style. Research about the impact of eco-feedback on energy consumption is the basis for designing a mobile eco-driving feedback information system that supports drivers in reducing fuel consumption. This work develops design knowledge from existing knowledge. Subsequently, we implement a prototypical instantiation based on the derived knowledge. Insights from a field study suggest that our design artifact allows most drivers to decrease fuel consumption by 4% on average. The paper's theoretical contribution is a set of design principles and an architecture of the proposed mobile eco-driving feedback information system. One recommendation is to provide normative feedback that compares drivers with each other. This feedback appears to encourage drivers to decrease their fuel consumption additionally. The design knowledge may support researchers and practitioners in implementing efficient eco-driving feedback information systems. [ABSTRACT FROM AUTHOR]