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Research has revealed the existence of an energy-efficiency gap – the difference between optimal and actual energy end-use, suggesting that energy efficiency can be improved. Energy management (EnM) is a means for improving industrial energy efficiency. However, due to various barriers, the full potential of EnM is not realised. Several studies have addressed drivers and barriers to energy efficiency but few to EnM. This study aims to identify EnM practices, the most important perceived drivers and barriers for EnM, and relations among them in the energy-intensive Swedish pulp and paper industry (PPI), which has the longest experience internationally of practising EnM systems, and has worked according to the standards since 2004. Our results show that, altogether, the PPI works regularly and continuously with EnM, with a clear division of responsibilities. The highest maturity for EnM practices was for energy policy, followed by organization, investments, and performance measurement. The study also shows that communication between middle management and operations personnel has potential for improvement. The most important categories of drivers were economic, whereas for barriers they were organizational. Nevertheless, knowledge-related barriers and drivers were amongst the most important, suggesting that the absorptive capacity for energy issues could be improved. Image 1029 • Energy is managed continuously, with clear policies and responsibilities. • The main drivers are economical while main barriers are organizational. • Knowledge related barriers and drivers are amongst the next most important. • Employees' absorptive capacity for energy issues could be improved. • Link between energy policy and performance measurement could be improved. [ABSTRACT FROM AUTHOR]

Guiding industries to produce in an effective and environmentally sustainable manner has become a key issue for governments around the world. Over the past 15 years, series of regional and industrial development policies have been introduced by the Chinese government. This has influenced the geographical distribution and energy efficiency performance of China’s industries. This paper quantifies the influence of enterprises geographical distribution on energy efficiency improvement in the paper industry and aims at providing some helpful suggestions on industrial development to policy makers. The main results show that, firstly, the paper industry in eastern China shows obvious characteristic of agglomeration. The average location quotient is 1.2278. However, following the industrial and regional development policies, the characteristic of agglomeration is weakening. Secondly, only when agglomeration reaches a certain level (location quotient is above 0.5447) will industrial agglomeration positively impact on industrial energy efficiency improvement (a 1% increase in agglomeration will increase dynamic energy efficiency by at least 0.23%). Thirdly, the regional development policies carried out by the government slow the pace of energy efficiency improvement in China’s paper industry. The empirical results indicate that the government needs to consider regional characteristics and consciously guide industrial enterprises to concentrate in the dominant area. [ABSTRACT FROM AUTHOR]

China’s paper industry consumes a lot of energy and emits huge amounts of pollutions. The Chinese government over the past decades has done a lot to promote energy efficiency of the industry. This paper studies the impact of industrial polices to improve energy efficiency. The energy efficiency change is firstly studied under a framework of total factor efficiency. On this basis, different econometric models are built to discuss the detailed energy efficiency characteristics of the paper industry. The main results are as follow: (i) ownership structure did influence the energy efficiency, but the influence is different in different conditions; (ii) energy efficiency of the paper industry can be improved by economies of scale; (iii) market competition can to some extent overcome the motivation and supervision problem that often occur in state-owned companies; (iv) energy price cannot play the role of resource allocation well in China. Finally, based on our findings, some suggestions are provided. [ABSTRACT FROM AUTHOR]

The increasing use of recycled paper by the paper industry to support the Green Industry in the Indonesian Pulp and Paper Industry. But technically, there are some disadvantages of recycled fiber usage such as low drainage rate in which boosted the high energy consumption on drying process. As already known, the drying process consumes the highest energy in papermaking. To overcome this problem, the research using the concentrate of endoglucanase Egl-II has done. The steps of research included production of endoglucanase Egl-II; concentration by ultrafiltration method, modification of recycled paper fibers using endoglucanase Egl-II; characterization of paper sheet; and evaluation of energy consumption in drying the sheet of paper. The results showed that endoglucanase Egl-II had increase drainage rate of recycled fiber stock, which indicate by the freeness number. The number had increased by 80 ml CSF (Canadian Standard Freeness) from 190 ml CSF to 270 ml CSF, and fiber retention increased by 0,63% from 99,31% to 99,94%. The dissolved cellobiose test results of recycled fiber stock by the enzyme treatment at low dosage showed that no degradation of cellulose, no change into soluble sugars. Characterization of sheet of paper that has been modified with endoglucanase Egl-II based FTIR spectra showed no change in functional group, SEM results showed on the fiber surface fibrils grow more, and the results of the XRD analysis showed area reduction of amorphous regions is about 6%. The potential for energy efficiency is calculated through thermodynamic approach is about 15%. [ABSTRACT FROM AUTHOR]

The Swedish pulp and paper industry (PPI) must increase energy efficiency to remain competitive on the global market, which has experienced entries from countries with cheaper energy and raw material supplies. Interactions among variables for energy use, production, energy management, electricity price and firm characteristics (FC), in different types of mills, i.e., pulp, paper and integrated mills, in Sweden from 2006 to 2015 indicate that correlations among the studied variables were different in different types of mills. This difference between types of mills seemed to originate partly from varying accessibility to production residue that could be used for energy. For all types of mills, variation of electricity prices did not correlate significantly with energy efficiency during the study period. The studied FC were firm's age, number of employees, number of companies in company group, net sales and profit for the year. Energy efficiency was more affected by the variables characterizing energy and production compared to the variables representing FC. This study also suggested presence of possible discrepancies between FC that were perceived as barriers to energy management towards energy efficiency, according to previous studies, and what was shown by the data combining variables representing energy use, production and FC. [ABSTRACT FROM AUTHOR]

The pulp and paper industry faces several challenges linked to climate and environmental impact, resource efficiency, rising energy prices, increased competition for biomass resources, and declining demand for traditional printed paper products. However, these challenges also offer strategic opportunities for the industry to develop into a competitive, resource-efficient, and low-carbon industry in line with a biobased economy. Against this background, this paper aims to analyse current energy strategies in the pulp and paper industry in Sweden. Specifically, the paper analyses how companies combine continuous process efficiency to reduce energy costs with activities that could be developed into new energy-related products to increase revenue. Most of the analysed companies work to various degrees with both these strategies, employing methods that include improving energy efficiency, energy security, and energy conversion, as well as developing a wide range of biobased energy products. However, our study indicates that there is an untapped potential associated with energy product development, and we conclude that energy efficiency measures can free up resources, enabling the development of new energy products. Finally, several potential managerial outcomes and implications are outlined. • The paper analyses the energy strategies in the pulp and paper industry in Sweden. • Energy strategies focus both to improve energy efficiency and develop new energy-products. • The companies' energy strategies combined exploitation and exploration. • A number of managerial implications are presented. [ABSTRACT FROM AUTHOR]

Small area femtocell increases the energy efficiency of the cellular network as the distance between base station and user is very less. Mobile femtocell causes the spectrum reuse to be used at very large extent making spectral efficiency suffer. This paper discusses recently researched techniques that have been used to increase the spectral efficiency in mobile femtocell network. But these techniques also come with their own limitations. Considering this, data aggregation and compression technique can be consider as one of the best contender to increase the spectral efficiency in cellular network which is also been explained in this paper. [ABSTRACT FROM AUTHOR]

To reduce energy use and achieve a low carbon production in pulp and paper industry (PPI), it is essential to improve energy efficiency in pulp and paper production. In this study, the energy savings from the PPI were estimated based on a techno-economic analysis by EAGER tool for PPI at the factory level. The structure and implement procedure were introduced initially. Two typical pulp and paper mills from China were determined to estimate the impact of selected energy efficiency technologies (EETs) on energy savings as the cases in the base year. One Factory (A) only produced paper products (i.e. corrugated paper and Kraft linerboard) while the other Factory (B) also produced market pulp besides sack paper. In totally 22 selected EETs were applied to assess their saving potential in Factory A, and 29 measures were applied in Factory B. The results show that 2290 TJ and 1179 TJ of final energy could be saved annually in Factory A and B, corresponding to reduction of 29.4% and 13.6% total energy consumption respectively for the case factories. The CO 2 reduction potential was 32.3% for Factory A compared with that of 16.6% in Factory B. It suggests that the pulp and paper mills should encouraged to use this method estimating energy saving potential, and improve their energy efficiency with suggested measures in order to reduce energy consumption and related carbon emissions further in the coming years. • Energy savings of pulp and paper production were estimated at the factory level. • A techno-economic evaluation tool was applied to access the energy savings and carbon emission reductions. • Two typical pulp and paper factories from China were investigated to estimate their energy savings in the base year. • It is useful to assess energy savings and select feasible EETs in achieving energy saving and emission reduction targets. [ABSTRACT FROM AUTHOR]

Under the dual pressure of energy consumption and environmental pollution, mankind hopes to develop clean and renewable alternative energy, and the rapid development of fuel cells meets people's demand for energy-efficient power systems. The emergence of portable micro energy systems represented by microfluidic fuel cells, such as paper-based microfluidic fuel cells, has greatly enriched the means of medical detection to better cope with the threat of disease transmission. In this work, the numerical simulation method is innovatively introduced to study the paper-based microfluidic fuel cells. Both transient and steady-state modes are employed to demonstrate the whole operation process of the paper-based microfluidic fuel cell. In addition, the different structural parameters, including electrode spacing, the distance between electrode and inlet, channel thickness, and electrode length, are also investigated their influence mechanisms on cell performance. Results show that the increase of most structural parameters decreases cell output power in different degrees. Even on the premise that increasing channel thickness has a positive impact on the output power, the fuel utilization still shows a downward trend. These conclusions provide theoretical support and reference for future optimization work and accelerate the development of microfluidic fuel cells. • Numerical simulation is employed to study paper-based microfluidic fuel cell. • The effects of structure parameters on cell performance are discussed. • Through fuel concentration distribution to reveal cell performance mechanism. • Fuel utilization is used to evaluate energy efficiency. [ABSTRACT FROM AUTHOR]

Regular Ship hull maintenance is an essential for sustainability. The maintenance work of ship hulls that involve human labor suffers from many shortcomings. Maintenance robots have been introduced for drydocks to eliminate these shortcomings. An energy-efficient Complete Coverage Path Planning (CCPP) is a crucial requirement from a ship hull maintenance robot. This paper proposes a novel energy-efficient CCPP method based on Glasius Bioinspired Neural Network (GBNN) for a ship hull inspection robot. The proposed method accounts for a comprehensive energy model for path planning. This energy model reflects the energy usage of a ship hull maintenance robot due to changes in direction, distance, and vertical position. Furthermore, the proposed method is effective for dynamic workspaces since it performs online path planning. These are the major contributions made to state of the art by the work proposed in this paper. The behavior and the performance of the proposed method have been compared against state of the art through simulations considering Hornbill, a multipurpose ship hull maintenance robot. The validation confirms the ability of the proposed in realizing a complete coverage of a given dynamic workspace. According to the statistical outcomes of the comparison, the performance of the proposed method significantly surpasses that of the state-of-the-art methods in terms of energy usage. Therefore, the proposed method contributes to the development of energy-efficient CCPP methods for a ship hull maintenance robot. • A novel coverage method based on Glasius Bioinspired Neural Network is proposed. • The proposed method is intended for a multipurpose ship hull maintenance robot. • A comprehensive energy model is utilized by the proposed method for path planning. • The proposed method is significantly efficient than the state of the art methods. • The paper contributes to the development of a ship hull maintenance robot. [ABSTRACT FROM AUTHOR]

This paper examines the pervasive barriers hindering the widespread adoption of energy efficiency measures across various sectors. It categorizes these barriers into economic barriers, high upfront costs, organizational challenges, such as technical expertise and behavioral barriers, namely risk aversion and framing. To address these barriers, a comprehensive review of energy efficiency policies is conducted. These policies include incentives, coercive instruments, award systems, university industry collaboration, and technical support. To review energy efficiency barriers and policies, a methodological approach integrating non-structured snowball sampling with targeted literature review techniques was devised. Finally, the paper underlines that the success of these policies is contingent upon the active involvement, the collaboration, and the feedback of businesses, ensuring the feasibility of these policies. Their proactive engagement is indispensable in tackling energy efficiency barriers and driving the implementation of energy-efficient technologies, thus paving the way for a more sustainable and competitive businesses. [ABSTRACT FROM AUTHOR]

This paper examines the role of energy efficiency in enhancing corporate sustainability and competitiveness. Employing a systematic literature review methodology, we analyze the financial advantages, corporate sustainability alignment, and crisis resilience associated with energy efficiency measures in business operations. The results highlight the significant cost savings, improved profitability, and enhanced competitiveness resulting from energy-efficient practices. Furthermore, we elucidate how energy efficiency initiatives align with broader corporate sustainability objectives, reduce environmental impact, and promote corporate social responsibility. Additionally, the paper discusses how energy efficiency enhances organizational resilience by bolstering preparedness for crises and promoting long-term sustainability and adaptability. The main implications of our findings underscore the importance of prioritizing energy efficiency as a strategic imperative for businesses seeking to achieve sustainability goals while maintaining competitiveness in a rapidly evolving global landscape. [ABSTRACT FROM AUTHOR]

Aerogels, with their exceptional properties such as high insulation performance, lightness, and eco-friendliness, present immense potential for use in the construction industry. This paper reviews the progress in research and application of various types of aerogels in construction, highlighting notable case studies demonstrating energy efficiency gains and sustainability impacts. It delves into the lifecycle of aerogels, discussing environmental implications at each stage. Despite their potential, aerogels face certain limitations including production complexity, brittleness, and high cost which hinder their widespread adoption. The paper further discusses these challenges and highlights the need for continuous research and development efforts to overcome them, with a view to achieving more scalable production, enhanced mechanical properties, and cost reduction. Looking forward, the paper discusses the expansive horizon of aerogel research, emphasizing the potential of smart aerogels, their integration with renewable energy systems, and exploring the possibility of recycling or creating bio-based aerogels to enhance their overall sustainability. While still in early stages, aerogels promise to be a major contributor to the future of construction, leading to more sustainable and efficient built environments. [ABSTRACT FROM AUTHOR]

The adhesion of gases to the electrodes is a major reason for reductions in energy efficiency, and hinders the production of hydrogen in alkaline water electrolysis (AWE). The development of an effective solution to this problem will be crucial for the design and optimization of AWE. In this paper, we present a novel structure for an electrolyser in which baffles are inserted into the channel. The flow process of the electrolyte and the electrochemical reactions in the electrolyser with the new structure are simulated, and the effects of the added baffles on the distribution of the gas phase production and the efficiency of energy conversion are analysed. Several important structural parameters are considered, such as the angle, number and length of the baffles, and corresponding numerical calculations are performed. In order to carry out a comprehensive evaluation of the performance of each electrolyser, the energy efficiency of AWE is evaluated and the current effect, ohmic overvoltage effect and bubble overvoltage effect caused by gas adhesion are quantitatively investigated. The results show that the flow of the electrolyte can be divided into three phases when baffles are added to the channel of the electrolyser, and that the baffles play a crucial role in both the transition phase and the full development phase. The maximum reduction in gas coverage at the electrodes reaches 60% and the maximum increase in energy efficiency reaches more than 3.0% with the addition of baffles. The addition of baffles has significant effects on the current and ohmic overpotential, and the balance between the gas coverage and ohmic overpotential can allow the maximum energy efficiency of the AWE to be achieved. [Display omitted] • A novel design for an electrolyser with baffles optimises the electrolyte flow. • The mechanism of transport in an electrolyser with baffles is analysed. • The effects of the angle, number and location of baffles are studied. • The thermodynamics performance of electrolyser is evaluated. [ABSTRACT FROM AUTHOR]

Black liquor (BL) is a by-product in the paper and pulp industry. Although it has good potential for providing energy as an industrial waste, BL's high moisture content limits its usability. In this study, an integrated system to effectively co-produce power and ammonia (NH 3) from BL is modeled and evaluated. The modeling and integration are conducted using the principles of exergy recovery and process integration to effectively circulate the energy/heat throughout the whole system. The developed system involves BL evaporation, gasification, syngas chemical looping (SCL), and NH 3 synthesis. During SCL process, H 2 , CO 2 , and N 2 -rich gas are produced consecutively in the oxidation, reduction, and combustion reactors, respectively. The designed system can achieve the total energy efficiency of ~50%. The result also suggests that N 2 -rich gas and pure H 2 produced during SCL can be used directly for NH 3 synthesis without any additional energy penalty. The additional step for CO 2 separation can also be avoided, affording a cleaner and more efficient system that provides complete carbon capture. • An efficient energy system of a H 2 production is proposed. • The system comprises evaporation, gasification, syngas chemical looping and NH 3 synthesis. • High energy efficiency in NH 3 production can be realized. • The designed system achieved about 50% of total energy efficiency. • The system has cleaner and more efficient system with 100% carbon capture. [ABSTRACT FROM AUTHOR]

The paper describes a new method for determining the energy efficiency of the life cycles of wind farms by the aggregated data of energy costs. The rationale for the use of aggregated data to determine energy costs during the life cycle of the wind farms is given. The classification of wind turbines and wind farms elements by the parameters and technical characteristics of the elements with subsequent division into groups for which aggregated data of energy costs are determined is given. Within the framework of the method have been developed an algorithm for determining energy costs on the production of elements of wind turbines and wind farms and formulas for their calculation during the life cycle of wind farms. In order to test the method, energy cost was calculated during the life cycle for two wind farms with wind turbines that differ parameters and technical characteristics of the elements and their energy efficiency was determined. It has been shown that the use of a hydrogen storage unit as part of a wind turbine makes it possible to efficiently use energy during down periods and increase the efficiency of the installation by 25–30%. It is noteworthy that a wind-hydrogen farm allows not only to accumulate excess energy during lean periods, but also to save the resource of wind turbines. When the energy reserve in the hydrogen battery reaches close to full, part of the wind turbines of the wind-hydrogen farm can be automatically temporarily stopped in a given order. This technology can provide an extension of the warranty service life for each wind turbine. [ABSTRACT FROM AUTHOR]

The measures needed to limit global warming pose a particular challenge to current fossil fuel exporters, who must not only decarbonise their local energy systems, but also compensate for the expected decline in fossil fuel revenues. One possibility is seen in the export of green hydrogen. Using Algeria as a case study, this paper analyses how different levels of ambition in hydrogen exports, energy efficiency and fuel switching affect the cost-optimal expansion of the power sector for a given overall emissions reduction path. Despite falling costs for photovoltaics and wind turbines, the results indicate that in countries with very low natural gas prices, such as Algeria, a fully renewable electricity system by 2050 is unlikely without appropriate policy measures. The expansion of renewable energy should therefore start early, given the high annual growth rates required, which will be reinforced by additional green hydrogen exports. In parallel, energy efficiency is a key factor as it directly mitigates CO2 emissions from fossil fuels and reduces domestic electricity demand, which could instead be used for hydrogen production. Integrating electrolysers into the power system could potentially help to reduce specific costs through load shifting. Overall, it seems advisable to analyse hydrogen exports together with local decarbonisation in order to better understand their interactions and to reduce emissions as efficiently as possible. These results and the methodology could be transferred to other countries that want to become green hydrogen exporters in the future and are therefore a useful addition for researchers and policy makers. • The required strong capacity expansion for PV and wind is challenging, but feasible. • "Energy efficiency first" benefits both the local energy transition and H2 exports. • Fully renewable power systems require a suitable political framework. • Higher hydrogen exports might help to reduce the specific power system cost. • Fossil capacity expansion must be stopped to avoid lock-ins and higher future costs. [ABSTRACT FROM AUTHOR]

In the era of Industry 4.0, achieving both energy efficiency and robust security in Cyber-Physical Systems (CPSs) presents a significant challenge because of the resource requirements and complexity of these systems. This paper presents a novel method to integrate energy efficiency and robust security measures in CPSs. We propose the integration of anomaly detection techniques into the CPSs, to facilitate self-adaptation to changing conditions and threats, thereby enhancing system flexibility and reliability while also optimizing energy consumption. Our approach enhances the flexibility and reliability of CPSs by integrating Deep Reinforcement Learning (DRL) into the MAPE-K (Monitor-Analyze-Plan-Execute with Knowledge) control loop. This integration not only streamlines anomaly detection but also optimizes energy consumption, ensuring efficient and effective management of critical system functions. The outcome is a marked improvement in the adaptive decision-making capabilities of CPSs, leading to heightened security and better energy efficiency across various sectors and applications. This study significantly advances sustainable industrial practices within the Industry 4.0 paradigm, emphasizing the development of CPSs that excel in both energy efficiency and robust security. [ABSTRACT FROM AUTHOR]

The rapid expansion of industrialization and the increase in energy demand make energy resource management necessary in various industries. Creating digital twins from available streaming data offers a practical way to enhance the efficiency of manufacturing systems. Digital twins allow for detailed analysis of key metrics, such as the energy consumption of complete manufacturing systems. Utilizing digital twins can greatly assist in improving manufacturing processes for reduced energy consumption. In this paper, we investigate the data requirements for the generation of energy-oriented digital twins of manufacturing systems. For this purpose, we developed a case study to illustrate and outline the necessary data requirements for a manufacturing system to enable the collection of data that can be used to extract energy-oriented simulation models. We, subsequently, analyze and generalize our findings that can be applied to a broader context. [ABSTRACT FROM AUTHOR]

To cope with the severe challenges related to traditional economic-centered urbanization, the Chinese government has proposed a people-oriented new-type urbanization strategy, which focuses on promoting the coordination and sustainable development of the environment, economy, and society. The existing literature has studied the impact of traditional urbanization on energy use but has not yet revealed the mechanisms and effects of the new transformation of urbanization on energy efficiency. Based on socio-economic-natural complex ecosystem theory, this paper systematically explains how new-type urbanization affects energy efficiency. By adopting a newly developed dynamic panel threshold model, the paper examines the complex impact of new-type urbanization on energy efficiency using panel data of 285 cities in China from 2003 to 2017. The results show that new-type urbanization has a significant double-threshold effect on energy efficiency. As the new-type urbanization level increases, the improvement effect of new-type urbanization on energy efficiency presents the change features of "strong-weakened-stronger." The heterogeneity analysis shows that under the constraints of multiple factors, such as new-type urbanization stages, geographic regions, economic development levels, and resource endowment, the impact of new-type urbanization on energy efficiency varies significantly. Targeted and differentiated policy recommendations for promoting new-type urbanization and energy efficiency are proposed. [ABSTRACT FROM AUTHOR]

• A bibliometric analysis of the relevant literature on tunnel lighting was conducted. • The literature is sorted by energy saving, visual comfort, and low carbon. • The relationship between energy saving and low carbon is discussed. • The relationship between energy saving and comfort is also discussed. • The optimization methods of tunnel light environment are summarized. A reasonable and applicative tunnel light environment is important to ensure driving safety. This review aims to contribute to this growing area of research by exploring the tunnel lighting, which expands from safety to visual comfort, energy saving, and low carbon This paper employs bibliometric method to a visual analysis of the relevant literature and summarizes current research efforts and development directions. Firstly, the literature is visually presented by CiteSpace to elaborate the state-of-art with the dimensions of the timeline graph, the keyword co-occurrence graph, and the institutions & countries co-occurrence graph. Afterwards the literature is reviewed from three major perspectives: energy saving, visual comfort, and low carbon. Current research is mainly on luminaire arrangement, auxiliary lighting and other measures to reduce energy consumption. Visual comfort is mainly improved by optimizing the light environment's physical quantities, e.g. luminance, color temperature, color rendering etc. Current measures to achieve low carbon targets include green energy, green photoconductivity, green luminaires and green operation. Energy saving, visual comfort and low carbon are interrelated and complementary. However, a systematic understanding of how tunnel lighting contributes to carbon emission is still lacking. There is still room for development in tunnel lighting to achieve full intelligent control and the goal of carbon neutrality. [ABSTRACT FROM AUTHOR]

This research paper presents a novel technique for improving load-shedding in DC microgrids by incorporating a binary number generator (BNG). Load shedding, a controlled strategy utilized to maintain equilibrium between power supply and demand within a microgrid when the aggregate demand surpasses generated power, is widely employed. Nevertheless, conventional load-shedding methods frequently encounter challenges, notably over-shedding and voltage deviations, particularly in scenarios involving numerous controllable loads. To overcome these challenges, an enhanced algorithm is proposed, which integrates the BNG technique. Simulation results conclusively demonstrate the effectiveness of the proposed algorithm in ensuring microgrid stability during periods of supply-demand imbalances. [ABSTRACT FROM AUTHOR]

Separate sensible and latent cooling (SSLC) is a promising technology for enhancing the energy efficiency of space cooling systems. In this paper, we propose an SSLC configuration consisting of an indirect evaporative cooling (IEC) device and vapor compression cycle (VCC) for handling space sensible load, and a desiccant wheel for handling space latent load. The performance of the proposed configuration is investigated using physics-based or empirical models for each component. A year-round simulation study of the proposed SSLC system is performed for 12 different cities with diverse climatic conditions. This study considers electrical, thermal, or solar energy for desiccant wheel regeneration. Parameters governing the system performance such as the air flowrate ratio in the IEC and the DW, DW regeneration air temperature, and supply temperature are studied. The proposed SSLC configuration is superior to the conventional system in all cities. The enhancement of seasonal coefficient of performance (sCOP) ranges between 50 and 261 %, 67 and 387 %, and 60 and 2072 % with yearly electrical energy savings of 33 and 72 %, 40 and 79 %, and 38 and 95 % for electrical, thermal, and solar energy for regeneration of DW, respectively. [ABSTRACT FROM AUTHOR]

Considering the escalating global warming and its severe consequences, the exploitation of hydrogen, an eco-friendly energy carrier, is gaining great interest. This paper comprehensively reviews the most common hydrogen production, storage, transportation and utilization processes, while their effectiveness is explored from energy, water, economic and environmental perspectives. Their main characteristics, advantages, shortcomings and challenges are discussed as well. The research reveals that the hydrogen's water footprint, energy consumption, carbon emissions, and cost vary significantly depending on the specific technologies used throughout its life cycle, from production to end use. For instance, fossil fuel-based hydrogen production methods, such as steam methane reforming, offer elevated energy performance and cost-effectiveness, but have a significant carbon footprint. In contrast, water electrolysis is environmentally friendly, but requires more water and has lower energy efficiency. Besides, high-pressure containers are the preferred method for hydrogen storage, while liquid and solid storages are better suited for high-energy-density applications. Regarding hydrogen transportation, pipelines are effective over long distances, whereas tankers are convenient for short distances. Furthermore, fuel cells are more energy, carbon and water efficient when using hydrogen as fuel, but they are generally more expensive than internal combustion engines. [Display omitted] • Hydrogen production, storage, transportation and utilization methods are reviewed. • Their energy efficiency, water use, cost, and environmental impact are explored. • Key recommendations to boost the utilization of hydrogen systems are outlined. • Fossil fuel-based technologies are more energy-efficient and cost-effective. • Renewable-based processes are more environmentally friendly but water-intensive. [ABSTRACT FROM AUTHOR]

This paper provides a method for predicting the energy efficiency of buildings using artificial intelligence tools. The scopes is twofold: prediction of the levels of the heating load and cooling load of buildings. A feature of this research is the performance of intellectual analysis in conditions of a limited amount of data when solving the stated tasks. An improved method of augmentation and prediction (input-doubling method) is proposed by processing data within each cluster of the studied dataset. The selection of the latter occurs due to the use of the fast and easy-to-implement k-means method. Next, a prediction is made using the input-doubling method within each separate cluster. The simulation of the method was performed on a real-world dataset of 768 observations. The proposed approach was found to have a high prediction accuracy in the absence of overfitting and high generalization properties of the improved method. Comparison with existing methods showed an increase in accuracy by 40-46% (MSE) compared to SVR with rbf kernel, which is the basis for the improved method, and by 5-12% (MSE) compared to the closest existing hierarchical predictor. [ABSTRACT FROM AUTHOR]

[Display omitted] • Classification • Clustering • Energy efficiency • Group leader election • Intelligent System • Meta-heuristic • Wireless sensor networks Strategies to streamline energy resources in wireless sensor networks (WSN) are still a hot topic. Many researchers have proposed various models of the WSN protocol so that the base station (BS)/sink can receive data collected from each sensor node. The energy in the WSN, which has a long life span, will convey a lot of data to the sink until the sensor nodes die. This paper has proposed modeling the WSN protocol by utilizing the classification and clustering of sensor nodes using the chimpanzee leader election optimization (CLEO) method. The CLEO algorithm is a meta-heuristic algorithm inspired by a social model that applies the pattern of leader selection to the chimpanzee community. The optimization method has the advantage of getting a fast fitness value which is one of the critical factors in utilizing meta-heuristic models in the WSN field. The closest sensor nodes at a certain distance to the sink are marked as classification, while other sensor nodes are marked as clusters. The clustering of sensor nodes utilizes a cluster function using the CLEO algorithm. This paper also carried out the selection of group leaders to obtain an energy efficiency model from WSN-CLEO. The results of the proposed method, WSN-CLEO, have been compared to other protocol models. [ABSTRACT FROM AUTHOR]

Energy efficiency can make energy access more affordable by reducing the electricity cost burden on households and businesses. Improving products' energy efficiency helps reduce monthly energy bills— freeing up funds that can feed back into the economy, thus stimulating economic growth. To demonstrate these benefits, this paper conducts a cost-benefit analysis (CBA) and a national impact analysis (NIA) for implementing an energy-efficiency standards and labeling (EESL) program for refrigeration products in Uganda. The CBA compares the costs versus the benefits of investing in energy-efficient products for consumers: It shows that the most cost-effective products have an efficiency level 35 % higher than baseline products sold on the market. By choosing these products, consumers save, on average, US$76 over the lifetime of the product. The NIA assesses the impact of an energy-efficiency standard set at that level and shows potential cumulative savings of US$595 million (2023–2040) for households and small businesses. These savings translate into additional purchasing power for households and investments for small businesses, leading to increased living standards and economic development. This paper describes the importance of implementing energy efficiency policies and programs in emerging economies where affordability of electricity hinders electricity access. This paper provides a rigorous approach of using CBA and NIA assessments to demonstrate the economic savings for the consumers and the nation to implement EESL programs for major electric equipment. • Energy efficiency increases consumer's welfare. • In Uganda, it can save consumers US$76 over the lifetime of the product. • This represents cumulative savings of US$595 million (2023–40) at the national level. • Energy efficiency policies is critical for electricity access affordability • The paper provides a Regulatory Impact Assessment replicable in other countries. [ABSTRACT FROM AUTHOR]

• Combining hydrodynamic and acoustic cavitation significantly enhances the energy-efficient processing of cellulose fibers. • Achieving maximum efficiency requires extensive optimization through multiphysical simulations and experimental investigations to understand the interaction of physical phenomena. • Effective sonicator design requires tuning of sonotrodes, signals, structural geometry, fluid volumes, flow conditions, and nozzle design to achieve synchronized resonance amplification at high power. • Cavitation treatment gives a notably improved fiber properties at specific concentrations, temperatures when combined with proper acoustic and hydrodynamic cavitation intensities. The cellulose pulp refining process is crucial for achieving high-quality paper characteristics. This research aims to enhance energy efficiency while maintaining good fiber quality using hydrodynamic and acoustic cavitation (HAC). Experiments were conducted with an in-house developed flow-through sonicator combined with a novel Venturi nozzle for hydrodynamic cavitation. The Venturi design was determined by analytical modeling and verified by CFD simulation with multi-phase turbulence models to balance cavitation intensity and turbulence against the acoustic cavitation effect. Experimental evaluation of two batches of CTMP fibers, pre-processed in different ways, showed significant improvements in paper strength and fiber properties. The best results for Batch 1 (HC and LC) were obtained with 386 kWh/bdt for AC and 350 kWh/bdt for HC (60 °C, 2 % concentration). The tensile strength index increased by 26 %, and the TEA-index, related to freeness, increased by 55 %. HAC treatment (750 kWh/bdt, 70 °C, 1.5 % concentration) of the less refined Batch2 (HC) yielded results better than the Batch 1 reference. These findings confirm the energy-efficient potential of the sonicator concept compared to traditional industrial processes. The conclusion is that HAC-refining of softwood pulp requires a proper balance between hydrodynamic and acoustic cavitation intensities. Both fiber concentration by weight and temperature are critical for an energy-efficient process. [Display omitted] [ABSTRACT FROM AUTHOR]

The contemporary world faces several energy problems and struggles to balance sustainable energy and steady industrial development. In this context, the existing energy efficiency studies have not unfolded the mysteries surrounding the industrial units' energy-saving potential and the key determinants and impacts of the manufacturing units' energy efficiency levels. Therefore, there is a need to comprehensively study the existing energy efficiency studies and clarify the above. Considering two databases, Scopus and Web of Science, the study uses bibliometric analysis and a systematic literature review to analyze the current energy efficiency literature. The bibliometric analysis is based on 619 published papers and assesses the existing energy efficiency literature to ascertain the evolution of energy efficiency studies from 2001 to 2022. This investigation adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-2020) framework for a systematic review of ninety-three relevant papers from the existing energy efficiency literature. The systematic literature review (SLR) highlights twenty-seven theories discussed in several dimensions of the environmental and industrial linkages in the manufacturing sector. Subsequently, the study identifies energy efficiency measures and the associated methodological issues. Next, the study addresses the available set of determinants and the impacts of energy efficiency performance on manufacturing industries across the globe. It explores the potential research gap in the existing studies. Finally, the concluding remarks, discusses several policy implications, and suggests avenues for future research in the direction of theory, context, and methodology in energy efficiency domain. [Display omitted] • Bibliometric analysis and systematic literature review are performed to synthesize the current energy efficiency studies. • The study considers 619 energy efficiency papers from Scopus and Web of Science databases over the past 22 years. • The study uses the PRISMA-2020 framework and uses Bibliometrix in R (RStudio) and VOSViewer software for the analysis. • SLR considers 93 papers and identifies 27 existing theories, addresses determinants and impacts of energy efficiency. • The study identifies the research gap, presents several policy implications and provides the scope for future research. [ABSTRACT FROM AUTHOR]

This paper presents an energy efficiency improvement scheme for offshore wind farms. This scheme uses learning-based nonlinear model predictive control (NMPC) and does not require wake modeling. The main feature is that each wind turbine can independently complete all optimal control, without the need for wind farm wake model calculation and iterative optimization. Specifically, this paper studies the critical factors for increasing the active power of wind farms and reducing the structural load of wind turbines, and reconstructs the optimal control objectives of wind turbines. Furthermore, combined with the nonlinear model of wind turbines containing uncertainty, a nonlinear model predictive control algorithm based on deep neural networks was designed, which can achieve multi-objective optimal control at the wind turbine level. The simulation results show that the uncertainty estimation method can effectively improve the nonlinear control performance, achieve an increase in the active power of the wind farm without wake iterative optimization, and at the same time suppress the structural loads of all wind turbines. • Propose a solution to improve wind farm energy efficiency without requiring wake modeling. • A nonlinear model of wind turbines considering uncertainty was established. • A deep neural network was used for uncertainty estimation. • Nonlinear model predictive control is used to achieve optimal control of wind turbines. [ABSTRACT FROM AUTHOR]

The motivation of this paper is to investigate the resistance of countries' energy research and development (RD&D) expenditures to random shocks. The analysis includes the five countries (France, Germany, Japan, the United States, and the United Kingdom) that are the biggest investors in RD&D in fossil fuels, renewables, energy efficiency, and nuclear energy. Thus, economies will be able to take precautions against global shocks in producing sustainable energy policies. To achieve this aim, this paper uses the artificial neural network approach, which uses a distributed computing model that can store and generalize data after a learning period. Empirical results widely depend on countries and distinct energy technology policy fields. The key findings provide evidence that RD&D expenditures, except for renewables, do not tend to mean revert. The economies of Japan, Germany, and the United States should make more renewable investments to reduce the resistance of renewable energy sources to shocks and thus produce policies for both environmental sustainability and energy security. The economies of France and the United Kingdom can ensure energy security by continuing their sustainable energy policies. • Applied SDG policies focused on energy technology RD&D are presented. • The stochastic characteristics of energy technology investments are examined. • Carbon-reducing policies are recommended for the top five economies. • Energy technologies are perused through artificial intelligence approach. [ABSTRACT FROM AUTHOR]

Urban energy consumption is a critical aspect of sustainable urban development, with technological innovations playing a pivotal role in shaping energy usage patterns. This paper presents a comprehensive analysis of urban energy consumption dynamics in relation to the adoption of technology across various sectors, including transportation, residential, industrial, and commercial domains. Through extensive data collection and advanced statistical analyses, we investigate the correlation between technology adoption rates and energy consumption behaviors in urban areas. Our findings reveal a strong positive correlation between technology adoption rates and reduced energy consumption across sectors. We employ spatial analyses to identify localized successes, shedding light on regions where technology-driven initiatives have significantly lowered energy demands. These insights offer valuable guidance for urban planners and policymakers aiming to implement targeted interventions and replicate effective strategies. Furthermore, the paper emphasizes the transformative potential of innovative solutions, ranging from smart infrastructure to industrial automation, in promoting energy efficiency and environmental sustainability. By fostering the integration of such technologies, cities can mitigate their carbon footprint, enhance energy resilience, and create more livable environments for residents. This research contributes to the discourse on urban energy transitions and provides actionable insights for urban policymakers and stakeholders striving for a greener, more sustainable urban future. • Urban energy study integrates tech for sustainable transitions. • Optimized urban planning with technology-driven energy solutions. • Innovative model promotes green, resilient cities through tech adoption. [ABSTRACT FROM AUTHOR]

The evolution of wireless body area network (WBAN) has changed the human life for its applications in the field of healthcare, fitness, entertainment and sports etc. However, two of the major challenges in the design of WBAN are energy efficiency and guaranteeing QoS. The load balance of different packet queues in a WBAN plays important role in design of energy efficient and reliable system. In this paper, we propose a Traffic Prioritized Load Balanced Scheduling (TPLBS) algorithm for load balancing in different priority queues in wireless body area networks based on IEEE 802.15.6 model. The main objective of this paper is to minimize packet drop in the queues so that throughput of WBAN can be improved. In this case we consider both priority and location from which the packet received, so that no packet should wait for a long time in the assigned queue to be transmitted to Access Point. The proposed method is simulated using Castalia to study and compare its performance with its counterparts. The simulation results reveal that the proposed protocol works better than the existing methods in terms of delay, throughput and energy efficiency. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of import competition on energy efficiency among firms in China. Using a difference-in-differences approach that exploits industry- and firm-level tariff reductions following China's accession to the WTO, we examine the effects of reduced output tariffs on coal intensity, measured as coal use per output, of Chinese manufacturing firms. Our findings indicate that higher levels of import competition lead to significant reductions in coal intensity, without negatively affecting firm production levels. We also find evidence that these effects are primarily driven by multi-product firms adjusting their product mix to prioritize energy-saving options. [ABSTRACT FROM AUTHOR]

In this paper, the energy efficiency of the widespread application of backstepping control to a class of nonlinear motion systems is investigated. A Switched Step Integral Backstepping Control (SSIBC) scheme is introduced to improve immunity to measurement noise and to increase the energy efficiency of conventional backstepping in practice. The SSIBC is realized by switching between two candidate controllers obtained at different steps of the iterative backstepping design process. A bi-state dependent hysteresis rule is developed to supervise stable switching between the different regimes in the presence of noise. The proposed method is experimentally verified on a MIMO twin rotor laboratory helicopter involving coupled nonlinear dynamics, inaccessible states and uncertainties. Experimental results show that in addition to a reduction in power consumption, the SSIBC reduces saturation of the control signal and visible motor jerking in contrast with conventional backstepping. Additional comparisons with a previously proposed optimized decoupling PID controller also show significant improvement in precision achieved with higher energy efficiency. Experimental results obtained with the introduction of an external disturbance into the system also show the robustness of the proposed SSIBC. • We propose a switched step integral backstepping control for nonlinear motion systems. • Experiments on a laboratory helicopter with time varying references show good system performance and energy efficiency. • The controller is robust to an external disturbance and reduces visible motor jerking. [ABSTRACT FROM AUTHOR]

To identify the influence of digital transformation on energy consumption, this paper introduces digitalization and energy elements into the multi-sector energy efficiency analysis model. Furthermore, this paper empirically tests the influence of digital transformation on energy efficiency from the micro level. The results show that the digital transformation indeed improves the enterprises energy efficiency, in which enterprises with higher energy efficiency are more affected. The improvement effect of digital transformation on enterprise energy efficiency continues to increase over time. In comparison, digital transformation shows more effective improvement effect on energy efficiency in enterprises that substantive transformation priority, with same group and maturity stage. Mechanism analysis shows that digital transformation can improve the energy efficiency of enterprises by reducing costs, increasing income, improving production efficiency and promoting technological innovation. In addition, the digital inclusive finance, government subsidies, intellectual property protection and service industry opening show positive regulatory effects. This paper proposes that, with the goal of peak carbon dioxide emissions and carbon neutrality, enterprises should actively increase digital investment and strengthen digital management of energy utilization. [Display omitted] • Digital transformation indeed improves the enterprises energy efficiency. • The promotion effect of digital transformation increases over time. • Digital transformation drives efficiency improvement and technological innovation. • Digital transformation contributes to cost reduction and benefit increase. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative decision support system for improving ship energy efficiency. It combines an engine optimization model and an artificial neural network (ANN). Real-time data regarding the ship and engine performance is obtained along a specific ship navigation, and an engine optimization model is built using Ricardo Wave software. This model is validated with high accuracy. Ship-specific parameters are derived, and fuel consumption is estimated using ANN models with different structures. The study identifies the most suitable ANN model with 1 hidden layer and 5 neurons based on error metric evaluation where the 0.99697 R2, 0.00035 RMSE, and 0.06470 MAPE scores are calculated. This approach offers a cost-effective solution for shipping companies to monitor critical engine parameters in real-time without investing in sensors or data collection systems. Thus, it contributes to dealing with the problem of the scarcity of analyzable data in the maritime literature, which is one of the significant issues in the papers related to energy efficiency, machine learning, and deep learning. It is an innovative approach since the parameters that are related to real-time operations rather than considering only instruction book information are aggregated, and the produced data is analyzed by an intelligent tool. • A system is proposed to control ship energy efficiency level by combining an optimization model and a neural network • A simulation model is created in the Ricardo Wave tool and the engine model is validated by actual data. • The ship fuel consumption is estimated by an artificial neural network based on the derived input parameters. • The prediction process is evaluated by error metrics to determine its success. [ABSTRACT FROM AUTHOR]

Abstract The annual market demand for disposable baby diapers exceeds 20 billion units (690 kt) in the European Union (EU). Almost 40,000 disposable diapers are used every minute, producing 1.3 t/min (dry weight) of waste. Based on the estimates in this work, this requires 90.3 PJ of primary energy and emits 2.7 Mt CO 2 eq. annually. In an attempt to reduce resource, waste and environmental impacts associated with diapers, this paper focuses on novel design and manufacture of disposable baby diapers. This involves using optimised absorbent core and novel bonding technologies to replace conventional gluing of diaper materials. Life cycle assessment has been performed to compare the environmental performance of these new diapers, here termed "glueless", with standard designs. The annual resource consumption and environmental impacts of glueless diapers have been estimated at different production levels: a single production platform, an industrial plant, a country (Italy) and the EU, taking into account different production volumes, electricity mixes and waste management options. Different market penetration scenarios have been considered to determine potential environmental implications at the EU level by 2020. The results reveal that glueless diapers reduce the consumption of raw materials by 23% (9.2 g/diaper), primary energy demand by 25% (752 kJ/diaper) and global warming potential by 10% (10.4 g CO 2 eq./diaper) compared to the standard diapers. They also have more than 50% lower eutrophication, ozone depletion and human and eco-toxicity. Up to 16 PJ primary energy and 191,000 t CO 2 eq. would be saved annually in the EU by using glueless diapers. The cumulative savings would amount to 47 PJ and 566,000 t CO 2 eq. by 2020. The annual consumption of raw materials at the EU level would be reduced by 196,000 t with cumulative savings of up to 584,000 t by 2020, also reducing the equivalent amount of waste from the disposal of diapers. Consequently, glueless diapers can contribute to meeting the energy, climate and resource efficiency goals specified in the EU 2020 strategy. Graphical abstract Image 1 Highlights • Novel design and manufacture of "glueless" disposable baby diapers is considered. • Glueless diapers save 23% of materials and 25% of energy relative to standard type. • Most life cycle impacts are reduced by >50% and global warming potential by 10%. • Up to 584,000 t of waste and 566,000 t of CO 2 eq. can be saved by 2020. • Glueless diapers can help meet the EU energy, resource and climate change targets. [ABSTRACT FROM AUTHOR]

This paper investigates the sustainability of Tabriz City focusing on its decarbonization. Statistical, quantitative, and comparative research methods are used to analyze the total energy consumed, conversion of primary energy, final exergy, and losses analysis according to the renewable and carbon-based energies. Then, the renewable resource potentials of the city are simulated using Grasshopper plug-in-Rhino simulator, THERM, PVSyst photovoltaic software, and ArcMap. In terms of the socio-economic assessment, non-oil Per Capita GDP, emissions, and energy intensities are analyzed concerning the B2DS scenario by 2050. The per capita GDP of the city is 71% of the country's average value. Tabriz's real GDP growth averaged −1.11% per year, primary energy demand increased by an average of 6.1%, CO 2 emissions from energy use grew by an average of 6% annually and the emission intensity of the economy increased by a total of 52.02%, in the period from 2011 to 2019. Finally, it is shown that the city consumes 58050 GWh/year of different carbon-based resources that only produced 20110 GWh/year of useful work with 5.63 MT CO 2 emissions, while the same work could locally be supplied by 30000 GWh/year RE with a minimum rate of 0.18 MT CO 2 emissions. The city Landfill receives 1000 tons/day of MSW, but two-thirds of this amount can be recycled. Regarding different sectors, buildings produce half of the CO 2. The cement industry with dual pollutants (17%) is the most polluting factory. Carbon-based electricity (66%) is the most polluting form of energy. In terms of carbon sequestration requirements with trees, shifting from fossil fuels toward green energies, EE, and recycling MSW can plunge required trees from 81.9 to 1.16 million trees. This paper highlights the importance of electrification of transportation based on RE, energy performance of buildings, and all sectors. • Large city decarbonization strategies • Application of RE according to geographic and climatic factors. • Electrification of sectors based on RE locally. • MSW recycling and sequestration by trees for decarbonization regarding the LULC and NDVI analysis. • Conversion and storage efficiencies of carbon-based fuels vs RE. [ABSTRACT FROM AUTHOR]

A large part of the energy for heating and cooling is consumed due to human needs for thermal comfort in the living environment. It is important to use a suitable method to design an energy-efficient building to satisfy the thermal comfort of residents throughout the year. This paper focuses on the implementation of the sensitivity analysis in the area of energy analysis of a prefabricated timber building on box models. The sensitivity analysis plays an important role in early planning, partially also presenting the energy analysis. A combination of the building energy simulation and the sensitivity analysis technique identifies key variables by order, which can either have a strong or insignificant impact on the further design of the energy efficiency of a building. Moreover, this paper presents a sensitivity analysis method performed on the case study of six different timber building models where design parameters, such as geometry, insulation features, glazing ratio and distribution, shading control and interior set-point temperatures, are varied in environments with different climatic conditions: moderate (Ljubljana), warm (Athens), and cold (Helsinki). The sensitivity analysis for a range of variable input parameters is conducted by using the global sensitivity analysis technique, i.e. the Morris method, which is based on the elementary effect. The main objective of the article is to provide guidance for researchers, professionals and building planners about the parameters they should focus on in the early planning of an energy-efficient timber building to reduce the energy required for heating and cooling, thereby ensuring constant thermal comfort in the living environment. The results of the sensitivity analysis, which serve as guidelines, show that the overall U-factor of a window, the solar heat gain coefficient, and a set-point temperature for heating are design variables that most affect the heating energy demand for the considered one- and two-storey box models in the three locations. The dominant parameters have on average 30% more influence on heating energy demand in cold climates than parameters in moderate climates and 88% more than in warm climates. While shading control and solar heat gain coefficient are the most influential parameters for cooling energy demand, with the dominant parameters in warm climates having on average 39% more influence than parameters in moderate climates and 49% more influence than parameters in cold climates. In the total energy demand for the operation of all box models under all climatic conditions, special attention should be paid to shading control. In addition, in moderate and cold climates, the overall U-value of the window and the internal set- point temperature in winter must be considered, and in hot climates, the solar heat gain coefficient is important. In the case of the two-storey box model, designers need to be careful about the glazing-to-wall ratio which depends on the orientation of the glazing (south-north or east-west). In this case, the dominant parameters have on average 47% more influence in warm climates than in cold climates and 56% more than in temperate climates. • Prefabricated timber-framed box models located in cold, moderate and warm locations were introduced. • Architectural parameters that minimize the total energy demand are searched. • The Morris method was used to identify the most influential parameters. • A guideline for early design of energy efficient timber buildings under different climatic conditions was developed. • Window characteristics, AGAW, shading and set-point temperature in winter have the strongest influence on energy demand. [ABSTRACT FROM AUTHOR]

Recently, there has been a substantial interest in on-device Machine Learning (ML) models to provide intelligence for the Internet of Things (IoT) applications such as image classification, human activity recognition, and anomaly detection. Traditionally, ML models are deployed in the cloud or centralized servers to take advantage of their abundant computational resources. However, sharing data with the cloud and third parties degrades privacy and may cause propagation delay in the network due to a large amount of transmitted data impacting the performance of real-time applications. To this end, deploying ML models on-device (i.e., on IoT devices), in which data does not need to be transmitted, becomes imperative. However, deploying and running ML models on already resource-constrained IoT devices is challenging and requires intense energy consumption. Numerous works have been proposed in the literature to address this issue. Although there are considerable works that discuss energy-aware ML approaches for on-device implementation, there remains a gap in the literature on a comprehensive review of this subject. In this paper, we provide a review of existing studies focusing on-device ML models for IoT applications in terms of energy consumption. One of the key contributions of this study is to introduce a taxonomy to define approaches for employing energy-aware on-device ML models on IoT devices in the literature. Based on our review in this paper, our key findings are provided and the open issues that can be investigated further by other researchers are discussed. We believe that this study will be a reference for practitioners and researchers who want to employ energy-aware on-device ML models for IoT applications. [ABSTRACT FROM AUTHOR]

In recent years, the severe environmental degradation and high levels of fossil fuel consumption linked to conventional ship energy systems have drawn attention to the advancement of alternative ship energy systems. Consequently, ship energy systems based on the use of an electrical microgrid are coming to the fore as an increasingly popular alternative solution. However, managing the energy flows within a shipboard microgrid can be highly challenging due to the multiple energy sources (including renewable energy sources) and types of loads involved. Additionally, the integration of an energy storage system has been identified as an effective solution for improving the reliability of shipboard power systems, pointing out the important role of energy storage systems in maritime microgrids and their potential to enhance the energy management process. As such, effective energy management strategies are necessary to optimize performance and ensure that the vessel's energy demands are met while minimizing fuel consumption and reducing cost and environmental impacts. This paper presents a comprehensive review of such strategies and methods recently presented in the literature associated with energy management in shipboard microgrids integrating energy storage systems and examine the different techniques that can be utilized to achieve optimal system performance. Moreover, the paper also sheds light on the future challenges and perspectives imposed by the modern shipboard microgrids operation on the energy/power management of these systems. The aim of this paper is to provide a helpful guideline for researchers and engineers conducting research in the field of electrically powered ships. [Display omitted] • A comprehensive review of EMS for electrical and hybrid ship is presented. • A comprehensive review of ESS which can be used in such ships is presented. • Technologies of ESS and their suitability to ships are discussed and commented. • Future challenges and perspectives imposed by modern SMG operation are presented. [ABSTRACT FROM AUTHOR]

Buildings' energy consumption and greenhouse gas emissions are a major global concern. Healthcare buildings, being crucial to society, pose particular challenges due to their round-the-clock operation and stringent hygiene standards. This paper comprehensively reviews existing literature to promote energy-efficient and comfortable healthcare buildings. The research explores both passive measures, such as orientation, materials, and daylight, and active measures, including Heating, Ventilation, and Air Conditioning systems, energy management, and renewable resources. The paper emphasizes the critical role of user behavior in conserving energy and outlines how factors like building size, operation hours, and climate can impact resource consumption. It highlights the importance of solar power as a prominent renewable energy source. It offers design and retrofitting options to enhance healthcare buildings and addresses the lack of research on small-scale healthcare buildings. The paper emphasizes maintaining a balance between user comfort and energy reduction, involving diverse stakeholders, and exploring benchmarks, automated shading, geothermal sources, local materials, and their impact on carbon emissions. This review aims to contribute to environmentally responsible and socially resilient healthcare infrastructure and provide insights for future challenges in creating energy-efficient healthcare buildings. • Literature review of "sustainable", "green", and "smart" healthcare building strategy. • A comprehensive examination of passive and active measures for energy-efficiency. • Findings highlight user behavior's critical role in energy conservation. [ABSTRACT FROM AUTHOR]

This paper investigates conversion of a Nordic oil-heated townhouse into carbon-neutral by different energy efficiency (EE) improvements and an off-grid system including solar photovoltaics (PV), wind power, and battery and hydrogen energy storage systems (BESS and HESS). A heat-pump-based heating system including waste heat recovery (WHR) from the HESS and an off-grid electrical system are dimensioned for the building by applying models developed in MATLAB and Microsoft Excel to study the life cycle costs (LCC). The work uses a measured electrical load profile, and the heat generation of the new heating system and the power generation are simulated by commercial software. It is shown that the EE improvements and WHR from the HESS have a positive effect on the dimensioning of the off-grid system, and the LCC can be reduced by up to €2 million. With the EE improvements and WHR, the component dimensioning can be reduced by 22%–41% and 13%–51% on average, respectively. WHR can cover up to 57% of the building's annual heat demand, and full-power dimensioning of the heat pump is not reasonable when WHR is applied. Wind power was found to be very relevant in the Nordic conditions, reducing the LCC by 32%. [Display omitted] • Energy efficiency improvements notably reduce dimensioning of system components. • Waste heat from FC and electrolyzer covers up to 57% of the annual heat demand. • A full-power-dimensioned GSHP does not reduce the fuel cell dimensioning. • Seasonal storage on a small scale makes the system not economically viable. • Small-scale wind power is expensive, but it significantly reduces the system LCC. [ABSTRACT FROM AUTHOR]

Energy efficiency has emerged as one of the most essential design parameters in contemporary computing system design. Approximate computing is a new computing paradigm to achieve energy efficiency by trading-off energy/area/latency improvements with accuracy for error-resilient applications. This paper proposes R econfigurable E nergy-efficient A pproximate D ivider (READ) that achieves several energy–quality configurable modes using fixed restoring array divider architecture. Conventional approximate binary dividers require various divider hardware configurations to achieve distinct energy–quality trade-off points, which decreases the hardware flexibility, especially for modern embedded systems. READ accomplishes energy efficiency while meeting the dynamically varying accuracy requirements of the targeted application. READ uses reconfigurable subtractor cells that can work in either accurate or approximate mode using a subtractor cell controller logic. The paper also introduces the design of overflow detector using minimal hardware resources. A comprehensive accuracy and hardware evaluation on CMOS 45-nm technology node are performed for the proposed dividers as well as other state-of-the- art divider designs. Compared to the accurate 16 ∕ 8 divider design, the proposed divider shows an improvement of 49% in terms of energy efficiency and is 1.26x faster, while introducing minimal errors. The proposed divider design is demonstrated for its efficacy in image processing tasks and shows nominal effect on the output quality. • A fixed restoring array based approximate divider is proposed and presented with detailed error and circuit analysis for CMOS-45 nm technology node. • The approximate divider presented is reconfigurable in runtime which enables accuracy configurability by varying the design parameter. • Reconfigurable half and full subtractor cells are designed and proposed which achieves dual mode of operation — accurate and exact with energy savings. • Overflow detector circuit for divider design is proposed and presented which is scalable and hardware efficient. • The approximate divider designs are evaluated for image processing applications and found to be satisfactory in terms of Quality of Services (QoS). [ABSTRACT FROM AUTHOR]

Energy efficiency represents a financial threat to energy companies. This paper examines how investor-owned electricity companies in North Carolina have turned the threat of energy efficiency – or "negawatts" – into a new arena of accumulation. They have done this by exploiting features of the North Carolina Renewable Energy and Energy Efficiency Portfolio Standard (REPS), a law passed in 2007 that encourages energy efficiency. I argue that under REPS, electricity companies have positioned themselves, counter-intuitively, as the primary producers of less of their main product. As such, these companies have been awarded high rates of return for creating energy efficiency projects. This paper builds on previous research into how environmental crises like climate change have been turned into new opportunities for accumulation in the neoliberal era. It focuses on neoliberal accumulation in an understudied system (electricity), socio-nature (energy efficiency), and political economic context (the regulated monopoly). Through reregulation, REPS creates negawatts as a new monopoly product for IOUs, contrary to what might be expected from previous research on green neoliberalism which often emphasizes the processes of commodification. This case study offers insights into the kinds of accumulation tactics that may occur in other regulated monopoly political economic contexts. Illuminating these tactics can inform more equitable and sustainable energy efficiency policies and programs by focusing attention on the need for transparency, alternative energy efficiency producers, and diverse energy efficiency programs aimed at reducing energy poverty. [ABSTRACT FROM AUTHOR]

The Kraft process is an intensive user of capital, energy, water, and chemicals, and is particularly vulnerable in the present precarious economic situation. Therefore, Canadian Kraft pulp mills offer good potential for improvement, especially if the equipment and unit operations are diagnosed in details by means of specific key performance indicators (KPI). The characterization and performance analysis of equipment is a prerequisite to optimization. A thorough evaluation of the equipment performance must be done to assess the actual vs. the expected performance before proceeding to any kind of energy improvement project. A systematic methodology for equipment performance evaluation through key performance indicators (KPIs) is presented in Part I. New key performance indicators (KPIs) based on dimensional analysis as well as other conventional key performance indicators are used to efficiently analyze and diagnose the causes of inefficiencies of the equipment, and propose adequate remedial actions. The methodology has been applied to an Eastern Canadian Kraft mill and several improvement projects leading to 30% of energy savings are proposed, entailing a low investment cost and a payback of 1.1 a. [ABSTRACT FROM AUTHOR]

This study analyzes the impact of green finance and renewable energy on energy efficiency in E−7 economies. We analyzed the nonlinear and asymmetric effects of green finance and renewable energy on energy efficiency. We collected data from 1985 to 2017 and applied the NARDL and 2SLS methods. The results reveal that the differences in green finance development in the E−7 region are as follows: China (0.61), Brazil (0.55), India (0.53), Indonesia (0.49), Mexico (0.37), and Russia (0.39). In 2019, the Gini coefficient was the largest in Russia (0.57), followed by Turkey. Based on empirical findings, the largest barrier to green energy efficiency is insufficient private and governmental investment in the energy sector to improve access to power, to increase energy security and promote economic growth in an environmentally sustainable manner. The findings point to a promising but vulnerable future for renewable energy and energy efficiency deployment in E−7 countries. This paper emphasizes that green financing and renewable energy policy limitations must be addressed to realize the funding potential of energy efficiency in E−7 countries. • We have analyzed the barrieres for renewable energy and energy efficiency. • Non-linear and asymmetric effects is observed on energy efficiency. • We have applied NARDL model to examine the relationship among variables. [ABSTRACT FROM AUTHOR]

• A multi-parametric analysis study has been conducted for 96 building scenarios. • The impact of building construction on the energy and temperature performance is studied. • The effect of different phase change materials on temperature regulation is investigated. • Several configurations have been recommended for both building constructions. This paper presents a comparative study that will evaluate and optimize 96 building cases in a multi-parametric manner. This study is conducted by using the EnergyPlus simulation software with the integrated PCM hysteresis model. The studied building designs were carefully selected to have equivalent air volume, while taking into consideration the outer wall shape of the building to increase or decrease the outside sun and wind exposed surface as well as increasing the PCM area inside the buildings. Three different building forms were evaluated, the square form, the octagonal form which is considered as the building design with a reduced surface, and finally the innovative zigzag form which has a higher wall surface compared to the square form. Additionally, these three building forms, were evaluated at two different constructions (light-weight and heavy-weight), four different PCM types and four different HVAC scenarios. The main purpose of this study is to assess indoor air temperature fluctuation reduction, energy efficiency, and PCM activation. The results reveal an energy saving up to 13.1 % and a maximum total yearly temperature fluctuation reduction of 653 °C. The recommended building configuration was able to reach a maximum PCM activation of 26.63 %. [ABSTRACT FROM AUTHOR]

Cabinet and in-store layout design impose high demands on supermarket refrigeration systems, due to temperature requirements and interactions between the ambient environment and the display. It is clear that views diverge on how different barriers should be investigated, and there are reasons to believe that energy efficiency measurements, with regards to both energy efficiency in buildings and energy efficiency in the operations, have weak points. The energy efficiency situation is a paradox that needs to be elaborated on. The paper presents a systematic literature review of research on open (no doors) or closed refrigerated cabinets (with doors) energy efficiency, chilled groceries and the consumer behavior, followed by an analysis of the contemporary research. The paper draws on findings and collects peer-reviewed articles from databases in order to examine how research has reported on this issue. As a result, 31 articles were framed, with different variables, to form a body of this article. Empirical research is needed that uses actual data, such as perceptions, behavioral research with lab experiments, and field measurements. Consumers shopping situation, for chilled groceries, is an extensive and complex topic, and a single study cannot provide a complete overview of all its related aspects. The results focus on two objectives. Firstly to present the review and secondly to analyze and identify knowledge gaps within the energy efficiency and store installations in the grocery context. [ABSTRACT FROM AUTHOR]