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Pressure servo control plays a crucial role in the majority of industrial applications that use compressed air as their power source. How to reduce the energy consumption of the pneumatic system while ensuring the high accuracy of pressure control remains a key problem to be solved. This paper proposes a Gaussian Process (GP) 1 model predictive controller (MPC) applied to a pressure servo control system based on high-speed on-off valves. The smallest quantity of collected data is used to create the GP model. The entire model, which includes some predictive data, is produced once the generated model has been optimized. The GP model is combined with the MPC to perform comparative experiments using an industrial controller with a Field Programmable Gate Array (FPGA). The system responds quickly and with little tracking error in steady-state response studies as well as dynamic response experiments. The GP-MPC achieves the best outcomes in the dynamic comparison tests. The root mean square error (RMSE) is just 2.42 kPa, and the overshoot is less than 59.9% of the Proportional-Integral-Derivative (PID) controller and 68.5% of the sliding mode controller (SMC). Although the compressed air consumption of GP-MPC is basically the same as that of PID, it is significantly better than SMC, with a total saving of about 70.2%. All the experiments prove that the controller proposed in this paper can effectively improve the energy efficiency and tracking accuracy of the pressure servo control system. [Display omitted] • A Gaussian process model for the high-speed on-off valve is developed which is able to predict uncollected data. • A model predictive controller is established by combining the Gaussian process model with rolling optimization method. • The pressure tracking and energy-saving performance are intended to be improved by using the objective function. [ABSTRACT FROM AUTHOR]

As the path of industrial eco-efficiency (IEE) needs to be re-examined from a multi-dimensional perspective, this research opens the internal "black box" of China's industrial eco-economic system driven by sustainable development goals (SDGs) and decomposes IEE into industrial production and sustainable development stages. It further divides the industrial production stage into two parallel subsystems of water use efficiency (WUE) and energy efficiency (EE) and derives SDG6 efficiency (SDG 6 E) and SDG7 efficiency (SDG 7 E) in the sustainable development stage respectively. The paper proposes a meta two-stage parallel entropy dynamic DDF-DEA model to re-measure IEE of 30 provinces in China from 2015 to 2021, discusses the relationship between overall efficiency and stage efficiency, and by using the Tobit model explores various types of influencing factors by subregion. The results show that the modified DDF-DEA model can explore China's IEE more accurately under SDGs. China's IEE is more stable from 2015 to 2021, with the efficiency value always fluctuating between 0.59 and 0.64, the overall level is low, and there is more room for improvement. There are significant inter-provincial differences in IEE and efficiency inertia. In more than 75% of the provinces SDG 7 E constrains IEE improvement, while the dynamic evolution of IEE and its subsystem efficiency varies across regions. Environmental regulation is a common factor affecting IEE across the country and in the east, central, and west regions, whereas the level of economic development, openness to the outside world, and urbanization rate are differential factors affecting IEE across the country and in the three major regions. This study offers new perspectives for exploring the path of IEE enhancement and providing empirical references for the collaborative construction of industrial ecological civilization. [Display omitted] [ABSTRACT FROM AUTHOR]

Adoption and improvement of energy efficiency is one of the recommended pathways to tackle the problems of growing energy demand and greenhouse gas emissions. However, studies show that rebound effects from energy efficiency improvements can erode anticipated energy savings. This paper elucidates the rebound effect arising from energy efficiency initiatives in Kenya. The study uses Index Decomposition Analysis to assess the drivers of Kenya's total primary energy supply. The paper then adopts the neoclassical growth model in the empirical analysis of energy and carbon rebound effects at the macro-economic level. Cobb-Douglas production function is further applied using Solow growth model and energy as a factor of production to approximate technological progress. Results of decomposition of energy supply show that energy intensity and affluence are the drivers with the most significant effect on energy supply while population has less critical effect. Average energy and carbon rebound effects show partial rebounds of 15.64% and 31.41%, respectively. These results imply that there is need to accelerate the pace of transitioning to green energy as the ultimate solution to minimizing environmental impacts arising from energy use and tackling climate change. • Carbon and energy rebound effects of energy efficiency initiatives is studied. • Decomposition analysis is used to investigate drivers of energy supply. • Energy intensity and affluence have most significant influence on energy supply. • Average estimates of carbon and energy rebound effects are partial rebound effects. [ABSTRACT FROM AUTHOR]

The promotion of modern industrialization has caused heavy environmental pollution. Environmental protection is a basic national policy of China. In 2011, China began to implement the "Twelfth Five-Year Plan for National Environmental Protection" (12th FYP_NEP). Using the survey data of small and medium-sized enterprises (SMEs) in Shandong Province of China, this paper empirically explores the impact of 12th FYP_NEP on the energy utilization and operating efficiencies of SMEs. It is found that the environmental policy "12th FYP_NEP" has a significant incentive effect on both efficiency performance of Chinese SMEs, and has a greater positive impact on operating efficiency. Our heterogeneity analysis showed the following results. The incentive effect is different in different industries and enterprises of different sizes. The policy "12th FYP_NEP" has a greater positive impact on the energy utilization efficiency of SMEs in China's first and second tier cities, but it has no significant impact on their operation efficiency. This shows that SMEs in first and second tier cities are more effective in coping with the national environmental policy reform strategy. It can be seen that the promulgation of China's environmental policies can significantly improve the energy utilization awareness of these SMEs. The incentive effect of the policy on the two efficiency performances of SMEs in cities with "heavy air pollution" is greater, indicating that the implementation effect of "12th FYP_NEP" on SMEs in such cities is better. The enlightenments are as follows: the current situation of Chinese SMEs is that the energy utilization efficiency is low, while the operating efficiency is high. Most enterprises attach great importance to their own operating profits and economic development, and the awareness of energy utilization needs to be greatly strengthened. "12th FYP_NEP" has obvious positive effect on the energy utilization and operating efficiencies of SMEs, but there are slight differences among different types of enterprises. It is suggested that governments can refine their own environmental regulation standards and implement different environmental regulations for different types of enterprises, so as to enhance the performance of domestic enterprises most effectively. • This paper used the China survey data on SMEs over the period 2010–2013. • It is found that the Chinese "12th FYP_NEP" has a significant incentive effect on efficiency performance of Chinese SMEs. • The incentive effect is different in different industries and enterprises of different sizes. • The policy makes for improving the energy efficiency of SMEs in first and second-tier cities and heavy-polluted cities. • Chinese SMEs should attach great importance to energy utilization rather than operating profits only. [ABSTRACT FROM AUTHOR]

Policies targeting energy efficiency and renewable energy are sometimes viewed as more politically feasible than carbon pricing in pursuit of emission reduction goals. This paper assesses underlying drivers of energy policy development. These factors include economic, social, environmental, and institutional variables. The between estimator for panel data is an appropriate method for our focus on some exogenous variables that vary more across countries than over time. We find that larger oil reserves per capita have a negative relationship with renewable energy policy development. Education and political globalisation have strong positive relationships with both energy-efficiency and renewable-energy policy development. These results suggest that greater participation in global political groups can be an indirect approach toward energy policy development, in cases where direct and immediate policies are hard to implement. OECD countries have higher policy scores by 33 and 25 points in energy efficiency and renewable energy respectively. Blinder-Oaxaca decomposition analysis shows that these higher scores are primarily due to social and political institution predictors rather than economics and physical endowments. • Large-n cross country international sample on continuous policy score measurement. • Political globalisation is positively linked with renewables and energy efficiency policies. • Education is positively linked to energy policy development, especially for efficiency. • Higher OECD countries' policy scores are primarily due to social and political predictors. • Higher incomes are unlikely to lead to automatic improvements in energy policies. [ABSTRACT FROM AUTHOR]

Hot embossing is an efficient technology for the fabrication of glass micro- and nanostructures. However, the long cycle time, high energy consumption, and high nitrogen emissions in traditional hot embossing approach hinders sustainable production of glass micro-optics. Therefore, this paper proposes a novel two-stage gravity-assisted hot embossing process that enables the fabrication of high-quality glass micro-pillar arrays in a rapid, green manner. In this approach, the two-stage gravity loading unit provides accurate force on glass preform through a simple control system, and the tailor-made heating module based on Si 3 N 4 ceramic heaters requires an energy consumption of just 700 kJ per molding cycle. As a result, the proposed approach is featured by low energy consumption and high manufacturing efficiency. In this study, the effects of the embossing temperature, force, and time on the replication accuracy of a K9 glass micro-pillar array were investigated through a series of hot embossing experiments. Afterward, the form accuracy, uniformity of microstructures, and warpage of glass replicas under the optimal process parameters were evaluated separately. Finally, repeated hot embossing experiments were conducted to demonstrate the reproducibility of the hot embossing process. The experimental results show that embossing temperature had the most significant effect on the replication accuracy of glass micro-pillars. By optimizing the process parameters, the embossed glass micro-pillars could achieve transfer ratios of 99.00% and 95.14% in height and diameter, respectively. Moreover, the surface roughness of glass micro-pillars was less than 5 nm, and the warpage amplitude of glass replicas in a 3.9 × 3.9 mm area was smaller than 1 μm. The small discrepancy in geometric features of glass replica in the repeated trails reflects the satisfactory reproducibility of this hot embossing process on the micro and nano scales. The results indicate the strong industrialization potential of the proposed two-stage gravity-assisted hot embossing machine and hot embossing process for fabricating high-quality glass microstructures more cleanly and sustainably. • A novel gravity-assisted rapid high-temperature hot embossing apparatus is developed. • A novel hot embossing process is designed for fabricating high-quality glass micro-pillar arrays in a cleaner manner. • Effects of process parameters on the replication accuracy of glass micro-pillar arrays are evaluated. • Form deviation, uniformity of microstructures as well as warpage of glass replica are analyzed. • The reproducibility in replicating geometric features in the novel hot embossing process is demonstrated. [ABSTRACT FROM AUTHOR]

The improvement of energy efficiency of products is a key pillar of climate and energy strategy in the European Union (EU). The first EU product policies were adopted in the late 1970s, and they have evolved to become a coherent set of implementing measures under framework directives that harmonise and refine the regulatory process. After years of weak implementation, considerable progress in terms of scale and ambition has been achieved in the last decade. In 2020, product mandatory measures covered 50% of the EU total final energy consumption, leading to 46 Mtoe energy savings. This paper describes the available policy instruments to promote energy efficiency and remove the market barriers hindering the penetration of the best performing technologies. It offers a review of the progress made over these last 40 years of EU product policies, describing the Energy Labelling, the Minimum Energy Performance Standards (MEPS), the Ecodesign Directive and the voluntary agreements (EU Ecolabel and Green Public Procurement). Moreover, it highlights the remaining challenges and provides policy recommendations to further exploit the EU potential to save energy from products. • Energy efficiency in products is a key pillar of EU climate and energy strategy. • Despite 40 years of EU product policies, their scale has only improved since 2010. • In 2020, mandatory measures covered 50% of the EU final energy consumption. • By 2030, savings expect to reduce the final consumption by 17%. • Policy orientation to further exploit the energy savings of products is provided. [ABSTRACT FROM AUTHOR]

The increasing energy demand in harbour areas, coupled with the need to reduce pollutant emissions, has led to the development of renewable energy-based polygeneration systems to face the carbon footprint of ports and ships at berth. In this way, in the coming years, ports can be converted into modern energy hubs. From this point of view, this paper presents a new dynamic simulation model for assessing and optimizing the energy and economic impact of ports. Here, energy systems and renewable sources can be designed to be connected to national electricity and natural gas grids and can include also alternative fuels (hydrogen, biomethane, etc.) and thermal energy networks, as well as different biomass fluxes (to be exploited for energy aims). Energy availability/demands of near towns and port buildings/infrastructures, as well as on-shore power supply are also included in the dynamic assessments. Hourly weather data and different prices for all the considered energy carriers are taken into account hour by hour. A multi-objective optimization approach is also implemented in the model considering energy and economic indexes to be optimized. The whole model is implemented in a computer tool written in MATLAB. For showing the capability of the developed model, a novel case study referred to the port of Naples (South-Italy) is presented. Here, several renewable energy sources are considered, including an anaerobic biodigester for producing biogas from the organic waste of docked cruise ships. A combined heat and power system (fed by biogas) is implemented in the port energy hub also for supplying absorption chillers. PV panels, and marine power generators are also included. In the conducted analysis, optimization targets are the maximization of system self-consumption and self-sufficiency as well as the minimum simple payback period. The proposed system can effectively contribute to the decarbonization of the port energy demand and reduce harmful pollutant emissions. Results showed that very high rate of renewable energy produced on-site can be exploited (up to 84%) by the considered port facilities, ensuring increasing independency from utility power grid (self-sufficiency index up to 40%). By the obtained results and through the developed simulation/optimization tool, novel design and operating criteria can be achieved for future port energy hubs featured by renewables and bi-directional energy exchange between ships and port. [ABSTRACT FROM AUTHOR]

This paper aims to develop an optimal real-life energy-efficient design for a production plant within the concept of the circular economy. The problem is to install a Heat Recovery System (HRS) that utilizes the hot oil used by the compressors to heat the water for the central heating system. To achieve the desired level of energy efficiency this design problem must be formulated from both the optimization and sustainability points of view. Additionally, this design problem must also consider the investment cost. In line with this purpose, this paper formulates this design problem as an optimization problem employing a mathematical programming approach as a single objective, and as a multi-objective optimization problem through a goal programming approach. Besides, this paper uses the return on investment as a key performance indicator, since it deals with a real-life design problem with an investment cost. The related design problem is solved with the single objective and multi-objective versions of the developed mathematical programming model via a commercial solver to identify different design alternatives and hence giving the decision-maker to make a selection option. Finally, the capability of the developed mathematical programming model is tested on a set of randomly generated problems. The obtained results indicate that the developed mathematical programming model is a successful decision support system since its single and multi-objective versions are capable of identifying energy-efficient production designs within the context of the real-life problem on hand and the circular economy. • A real-life energy-efficient design problem for a production plant is undertaken. • A heat recovery system is proposed within the concept of a circular economy. • The problem is modelled from both the optimization and sustainability aspects. • The problem is formulated as multi-objective models using goal programming. • The models are solved to minimize investment costs and maximize energy efficiency. [ABSTRACT FROM AUTHOR]

Transformations in the agri-food system since the early 19th century have led to an unprecedented increase in food production. However, the structure of this system has generated many negative environmental and social impacts that threaten the sustainability at the local, regional and global scale. This situation entails the need for an agroecological transition that leads to an agri-food model that is aware of the planetary boundaries and guarantees the reproduction of human and all other forms of life. Agroecology is crucial for the Mediterranean, where the negative environmental and social impacts of industrial agriculture are particularly evident. The aim of this paper is to present a best practice viticulture farming that is in an advanced level of agroecological transition in the region. The results show that the energy efficiency of this agroecosystem is greater to conventional farms in the region, while generating similar financial returns but more equally distributed than the big agro-industrial companies in the sector. Based on this best practice case study, we provide several methodological and practical insights on the energy balance of the farm system, supplemented by data on the value-added distribution from wholesaler selling back to the industrial winemaking and vine-growing incomes, and the final financial returns of the company. The results highlight the need of multifactorial analyses that contribute to a systemic perspective on the synergic elements and leverage points for scaling-up the agroecological transition of Mediterranean viticulture. • Mediterranean best practice viticulture farming towards agroecological transition. • Circular economy of this farm system is greater to conventional farms in the region. • Practical insights contribute to the global debate on the agroecological transition. • These insights refer to both the energy and the cash balances of the farm system. [ABSTRACT FROM AUTHOR]

Transformations in the agri-food system since the early 19th century have led to an unprecedented increase in food production. However, the structure of this system has generated many negative environmental and social impacts that threaten the sustainability at the local, regional and global scale. This situation entails the need for an agroecological transition that leads to an agri-food model that is aware of the planetary boundaries and guarantees the reproduction of human and all other forms of life. Agroecology is crucial for the Mediterranean, where the negative environmental and social impacts of industrial agriculture are particularly evident. The aim of this paper is to present a best practice viticulture farming that is in an advanced level of agroecological transition in the region. The results show that the energy efficiency of this agroecosystem is greater to conventional farms in the region, while generating similar financial returns but more equally distributed than the big agro-industrial companies in the sector. Based on this best practice case study, we provide several methodological and practical insights on the energy balance of the farm system, supplemented by data on the value-added distribution from wholesaler selling back to the industrial winemaking and vine-growing incomes, and the final financial returns of the company. The results highlight the need of multifactorial analyses that contribute to a systemic perspective on the synergic elements and leverage points for scaling-up the agroecological transition of Mediterranean viticulture. • Mediterranean best practice viticulture farming towards agroecological transition. • Circular economy of this farm system is greater to conventional farms in the region. • Practical insights contribute to the global debate on the agroecological transition. • These insights refer to both the energy and the cash balances of the farm system. [ABSTRACT FROM AUTHOR]

Nowadays, China's economy and energy structure are deeply adjusting to the direction of low-carbonization and non-carbonization with unprecedented efforts. This paper considered carbon emissions and energy endowments, adopted SBM-Undesirable model and spatial Durbin model to calculate the energy efficiency of 30 provinces and municipalities in China from 2015 to 2019 and analyze the direct effect, indirect effect and total effect on energy efficiency of 7 variables. Empirical results show that: Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. The valuable conclusions obtained in this study deepens the insights about the influencing factors of China's energy efficiency under the constraints of carbon emission and energy endowment. Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. [Display omitted] • Energy efficiency has spatial positive correlation and agglomeration characteristics. • Energy consumption structure mainly affects energy efficiency. • Environment Kuznets Curve exists in China. • "Pollution paradise hypothesis" exists in foreign direct investment. • Environmental pollution is transferred to surrounding provinces through resource trades. [ABSTRACT FROM AUTHOR]

Compressed air systems have a high energy transfer capacity. They are widely used in the manufacturing industry due to being clean, dependable, and simple-to-use. On the other hand, these systems are among the most significant energy consumers in the manufacturing sector because they are inefficient with high electricity usage and high CO 2 emissions. As a result, all kinds of the energy efficiency enhancements in these systems promote cleaner production by lowering total energy consumption and CO 2 emissions in factories. In this paper, the energy-saving potential and carbon emissions of Compressed Air Systems are investigated using data from in-situ energy audits. A simple set of equations is proposed to calculate the mass flow rate of air leakage. The sound intensity (dB) obtained from ultrasonic flow measurements were used as the input of the equation set. Furthermore, two new Energy Performance Indicators have been proposed to guide energy audit evaluation and continuous monitoring of the energy efficiency of Compressed Air Systems in industrial facilities. The new evaluation criteria "Specific Compressed Air Savings" and "Specific Leakage Savings" provide a comparison tool to help decision-makers with their compressed air system investment decisions. Using the "Specific Compressed Air Savings" and "Specific Leak Savings" parameters, the analysis method is demonstrated for an example industrial plant. The facility's specific compressed air and leakage savings are calculated as 0.0067 TOE/ton and 0.0035 TOE/ton, respectively. [ABSTRACT FROM AUTHOR]

In the natural stone sector, rock blocks are cut as a plate using block-cutting machines (BCM), and the plates are polished in the polishing machines. Energy consumption is the primary operating cost in both the cutting and polishing processes. The energy consumption of BCMs is affected by many factors, with the most influential being traverse speed. The energy efficiency of BCMs can be improved by regulating the traverse speed throughout the cutting process, and the roughness of the cut surface can be reduced by keeping the ratio between the traverse speed and peripheral speed constant as an additional benefit. This also reduces energy consumption and waste production in the polishing process. In this paper, two controllers used for the regulation of traverse and peripheral speeds are applied to a laboratory-scale BCM, one of which regulates only the traverse speed, while the other regulates both the traverse and peripheral speeds. A limped hierarchical fuzzy logic controller (LHFLC) approach is used in the design of the controllers for the first time on the BCM. In the proposed LHFLC method, the design procedure of the controller is simplified, and its memory usage, computational load, and response time are decreased. The performance of the controllers (a three-input/one-output (3I1O) FLC, 3I1O LHFLC, and a three-input/two-output (3I2O) LHFLC) was tested with cutting experiments performed on three rock samples (Bilecik Beige limestone, Uşak Green marble, and Afyon travertine), and the acquired results reveal that the proposed controllers (3I1O LHFLC and 3I2O LHFLC) are more efficient than the previous controller (3I1O FLC), with over 21%. A statistical analysis shows that to improve the energy efficiency of the BCM, the 3I1O LHFLC could be used rather than the 3I1O FLC. It is further noted that statistically, the cutting rate can be kept more constant with the 3I2O LHFLC than with the 3I1O LHFLC, meaning that the surface roughness of the plates produced by the BCM can be reduced using the 3I2O LHFLC. [Display omitted] • The energy efficiency of the block-cutting machine (BCM) was improved by regulating traverse speed throughout the process. • A limped hierarchical fuzzy logic controller (LHFLC) was used to regulate the traverse speed for the first time on a BCM. • With the LHFLC, the energy consumption of the BCM was reduced by at least 20%. • The cutting rate of the BCM was kept constant through the regulation of both the traverse and saw blade speeds. • Energy consumption and waste production can be reduced in the polishing process keeping the constant cutting rate of the BCM. [ABSTRACT FROM AUTHOR]

In the German industry Heating, Ventilation and Air Conditioning (HVAC) systems account for 11 %–20 % of the final energy consumption. Usually HVAC systems are dimensioned based on static extreme values and thus during most of the operation time, HVAC systems tend to be overdimensioned. In addition, the extensive literature review of 40 papers shows that often topics on model-based energy efficiency improvement are commonly performed for office or residential buildings, but rather rarely for production environments. Furthermore, the performance of control schemes for energy efficiency improvement are rarely compared with each other or incompletely compared with each other. In this publication, we use the framework of a Cyber–Physical Production System (CPPS) to compare the performance of four main control schemes, ranging from simple time-based control to model-predictive control, which has not been done in the context of battery production before. Over a fixed observation period, the four control schemes are transparently compared with each other in a case study using the example of the Battery LabFactory Braunschweig (BLB). Compared to the initial state, a significant reduction in final energy demand can be achieved with all examined control approaches, which is even up to 37.29% in case of the model-predictive control. Surprisingly, even simple control approaches, without any predictions, have a good energetic saving potential of up to 20.22% compared to the initial state, which is why they are initially recommended for practical implementation. Moreover, we publish all source code of the control schemes, in order to encourage the implementation of energy efficiency measures in further applications not restricted to battery production. • Comparison of control schemes for energy efficiency improvement of HVAC systems. • Considering scheduled to model-predictive control applied to battery production. • Best control scheme achieves energetic reduction of up to 37.29% in case study. • Control scheme approaches transferable to other cases outside of battery production. • Publication of source code to encourage implementation of efficiency measures. [ABSTRACT FROM AUTHOR]

Room air conditioners (RACs) are one of the high energy-consuming home appliances. Developing a smart solution to evaluate and track the efficiency of RACs is essentially useful for residents to make necessary maintenance or replacement decisions. While smart meters are increasingly installed to monitor electricity use, the application of smart meter data to evaluate the RAC efficiency remains inadequate. In this paper, we present a data-driven framework to identify non-inverter window RACs with low energy efficiency by analyzing smart meter data from the university student hall rooms. In this framework, we first applied the extreme gradient boosting (XGBoost) method to predict a RAC's hourly electricity consumption. Then we measured the effect of outdoor temperature on the XGBoost prediction of hourly RAC electricity consumption using the Shapley Additive Explanation method to interpret the RAC's efficiency. We conjectured that the RAC efficiency is normal if the predicted hourly electricity consumption is significantly correlated with the outdoor temperature. In contrast, the RAC efficiency is low if the outdoor temperature changes have little impact on the predicted electricity consumption. Finally, we applied the K-Means clustering algorithm to separate the RACs into the "low efficiency" and "normal efficiency" categories based on each's pattern of outdoor temperature's impact on electricity consumption. Our cross-validation result showed that the XGBoost model can achieve an average R2 score of 0.50 and an average root mean squared error of 0.20 kWh. We used RAC replacement records to validate our framework of interpreting the RAC's efficiency. On average, RACs having low efficiency consumed 25.69% more electricity per hour. Overall, our data-driven framework can contribute to extending the value of smart meters for RAC efficiency evaluation. Meanwhile, the smart meter data-driven framework can be improved, and more validation is needed in the future. • We created a data-driven framework to assess the room air conditioner's efficiency. • An XGBoost model was developed for hourly electricity consumed by air conditioners. • We clustered air conditioners based on Shapley value of outdoor temperature. • Air conditioners with low efficiency were identified and validated from clustering. • Identifying air conditioners with low efficiency can save electricity. [ABSTRACT FROM AUTHOR]

Energy efficiency based on behavioral change has attracted increasing interest in recent years, although, solutions in this area lack much needed techno-economic analysis. That is due to the absence of both prospective studies and consumer awareness. To close such gap, this paper proposes the first techno-economic assessment of a behavioral change-based building energy efficiency solution, to the best of the authors' knowledge. From the one hand, the technical assessment is conducted through (i) introducing a novel edge-based energy efficiency solution; (ii) analyzing energy data using machine learning tools and micro-moments, and producing intelligent, personalized, and explainable action recommendations; and (iii) proceeding with a technical evaluation of four application scenarios, i.e., data collection, data analysis and anomaly detection, recommendation generation, and data visualization. On the other hand, economic assessment is performed by examining the marketability potential of the proposed solution via a market and research analysis of behavioral change-based systems for energy efficiency applications. Also, various factors impacting the commercialization of the final product are investigated before providing recommended actions to ensure its potential marketability via conducting a Go/No-Go evaluation. In conclusion, the proposed solution is designed at a low cost and can save up to 28%–68% of the consumed energy, which results in a Go decision to commercialize the technology. • Techno-economic assessment of behavioral based energy saving systems. • Edge-based energy saving using artificial intelligence and micro-moments. • Anomaly detection and explainable recommender systems for energy monitoring. • Market assessment and commercialization strategy considerations. • Market barriers and market drives of buildings energy efficiency solutions. [ABSTRACT FROM AUTHOR]

The increasing global consumption of energy and its negative impacts on the environment has been an issue discussed both by academics and practitioners, including in the health sector. Hospitals are major consumers of energy, which leads to increased operating costs, decreased competitiveness, and negative environmental impacts. Energy management in hospitals must be understood as a way to contribute to environmental sustainability and as a way to improve competitiveness. Therefore, the objective of this paper is to propose guidelines for efficient and sustainable energy management in hospitals, developed based on the literature review, the challenges faced and the good practices of sustainable energy management in the hospitals studied, the cross analysis of the case studies, and the authors' expertise. As a result, the eight proposed guidelines are related to culture change, energy consumption management, energy management standard, purchase of renewable energy, green technologies, sustainable hospital buildings, social responsibility programs focused on energy use, and sustainable energy public policies. These guidelines contribute in an applied/managerial way to help managers of public and private hospitals overcome the challenges of energy management and contribute to UN's SDG7 due to its potential to improve energy efficiency and environmental performance, therefore, being a movement towards clean energy. This study also theoretically/scientifically contributes to the academic debate since the empirical findings found in the hospitals studied and the proposition of guidelines deepen and expand the key elements identified in the literature on efficient energy management in hospitals, providing the basis for developing new research on the subject. Energy management in hospitals is discussed from the perspective of sustainability. Challenges need to be overcome for sustainability benefits to be achieved. This work can assist public and private hospitals in developing sustainability. Guidelines for sustainable energy management in hospitals are proposed. [ABSTRACT FROM AUTHOR]

The super efficiency slack-based measure (SBM) with undesirable outputs was used in this paper to determine the energy efficiency of the service industry in various provinces from 2007 to 2017. The different characteristics of the energy efficiency of service industry in different provinces were obtained from the perspective of heterogeneous resource endowment. The findings show that: ⅰ) China's service industry's overall energy efficiency fluctuates in a 'W' shape. Provinces with varying resource endowments demonstrated significant variation in energy efficiency. Provinces with a high concentration of technology and energy had the highest and lowest levels, respectively, indicating an upward and downward trend. ⅱ) Energy efficiency improvements in China's service sector were primarily a result of technological advancements. Technological advancement and technical efficiency were the primary causes in technology- and labor-intensive provinces, respectively, whereas the combined effect of both factors was the primary cause in energy-intensive provinces. ⅲ) Foreign investment and environmental regulation may both contribute to the improvement of energy efficiency in the service industry, while energy structure and government intervention may work against it. Additionally, a U-shaped relationship was observed between the service industry's development level and energy efficiency. As a result, policymakers should develop targeted promotion strategies based on the resource endowment and development stage of the service industry in various provinces. • Undesirable super efficiency SBM model and Malmquist–Luenberger index are used. • China's service industry's overall energy efficiency fluctuates in a 'W' shape. • Static and dynamic analysis of the service industry's energy efficiency is provided. • The service industry's energy efficiency in provinces with different resource endowment is heterogeneous. [ABSTRACT FROM AUTHOR]

Given their increasing number and the implementation of more energy-intensive treatment methods, wastewater treatment plants (WWTPs) expect to increase energy consumption. In addition, climate change presents new challenges to the operation of these facilities, thus being critical to understand how to improve their energy performance and environmental sustainability while ensuring the quality of service provided. This paper reviews the latest publications on the energy performance of municipal WWTPs, particularly on the different phases of the treatment process and the impacting factors. The contextual and underlying factors that influence energy performance were identified, categorized, and analyzed through a broad survey. The most significant factors are the plant size, load factor (plant capacity utilization), and dilution factor. The implementation of anaerobic-anoxic-oxic systems is considered suitable in sensitive areas requiring high pollutant and nutrient removal rates, presenting, in some cases, moderate energy consumption (0.267 kWh/m3), being similar to the conventional activated sludge (0.269 kWh/m3). In more stringent effluent quality requirements, such as wastewater reuse, membrane bioreactors are advised, despite higher consumption (0.33 kWh/m3). Energy improvements can also be achieved by implementing automatization, inverters, and strategies that increase flexibility and adaptability in the operational process. Lastly, given the multidimensional characteristics of the WWTPs assessment, further improvements may be identified if the energy performance of these plants is compared using holistic and multi-criteria approaches, integrating multiple inputs and outputs simultaneously. • Long-term operation of low installed power equipment deserves more attention. • Energy intensity is mainly influenced by plant's size, load, and influent dilution. • Anaerobic-anoxic-oxic systems are a good option for impoverished areas. • Energy performance must be assessed in a holistic and multi-criteria approach. [ABSTRACT FROM AUTHOR]