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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 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]

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]

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]

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]

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]

Abstract Railways are a rather efficient transport mean, and yet there is increasing interest in reducing their energy consumption and making them more sustainable in the current context of climate change. Many studies try to model, analyse and optimise the energy consumed by railways, and there is a wide diversity of methods, techniques and approaches regarding how to formulate and solve this problem. This paper aims to provide insight into this topic by reviewing up to 52 papers related to railways energy consumption. Two main areas are analysed: modelling techniques used to simulate train(s) movement and energy consumption, and optimisation methods used to achieve more efficient train circulations in railway networks. The most used methods in each case are briefly described and the main trends found are analysed. Furthermore, a statistical study has been carried out to recognise relationships between methods and optimisation variables. It was found that deterministic models based on the Davis equation are by far (85% of the papers reviewed) the most common in terms of modelling. As for optimisation, meta-heuristic methods are the preferred choice (57.8%), particularly Genetic Algorithms. Highlights • Modelling and optimisation methods for railways energy efficiency are reviewed. • Modelling methods provide reliable simulations of the trains' energy consumption. • Optimisation methods help obtaining the most efficient solutions for train traffic. • Most used modelling methods are deterministic, based on Davis equation. • Most used optimisation methods are meta-heuristics, mainly genetic algorithms. [ABSTRACT FROM AUTHOR]

Abstract Water pumping systems are widely used in industrial and civil applications. During their operational life, they consume energy and materials (mainly for installation and replacement of components). The aim of this paper is to optimize the pump operations in order to save energy and enlarge the operational life of the pumps and their components. This paper addresses the multi-period (e.g. 24-hours time horizon) optimization of pumping systems. To this end, we have developed a simulation-based optimization approach including novel relevant technical features of a generic but realistic pumping system, namely cavitation and overflow. The proposed multi-period optimization differs further from the classic static optimization (i.e. at the design stage), proposing a new dynamic approach in which pump activation is steered dynamically for an optimal management of the variability of water inflow. Furthermore, the problem includes constraints on the number of pump activations allowed to reduce material strain. The performances of different meta-heuristic optimization algorithms (e.g. genetic algorithm, simulated annealing and particle swarm optimization) for solving the problem are compared. The numerical results show that energy savings are possible with the dynamic approach and that particle swarm optimization and simulated annealing algorithms provide the most suitable solutions for this problem. Highlights • Three algorithms are compared to minimize energy pump consumption. • The pump model includes energy, cavitation, overow and activation frequency. • Static and dynamic optimizations are investigated. • The dynamic optimization can reduce the energy consumption by 6.5%. [ABSTRACT FROM AUTHOR]

Abstract Energy efficiency improvement is usually regarded as an effective way to decrease energy consumption and to fight climate change, but it also booms energy consumption through rebound effects. But the improvement of energy efficiency also has rebound effects, which increases energy consumption and emission. So this paper arms to capture the rebound effects of efficiency improvement by considering zero-cost breakthrough of energy efficiency and price jump of energy purchase. First, energy efficiency improvement, measured by zero-cost breakthrough of energy efficiency, stimulates energy consumption, but it may reduce the total emission. Second, both the direct and indirect rebound effects of energy efficiency improvement on energy consumption and environment are captured. Interestingly, jumping energy price decreases both the direct and indirect rebound effect. Finally, the result of the paper shows that restriction of individuals' entry or competition restriction moderates the rebound effects of energy efficiency improvement. Highlights • Effect of competition on energy efficiency rebound effects is developed in theory. • Rebound effects of energy efficiency are captured under zero-cost breakthrough. • Moderate monopoly is proofed to be helpful for reducing energy efficiency rebound effects. • Improvement of energy efficiency has both direct and indirect rebound effects. • Energy price jump has offset effects on rebound effects of efficiency promotion. [ABSTRACT FROM AUTHOR]

Since sustainable scheduling is arousing increasing attention from many manufacturing enterprises and energy consumption is a core problem regarding sustainability, the purpose of this paper is to develop an energy-efficient scheduling method to fulfill material delivery tasks in mixed-model assembly lines. In this research, the objective of minimizing the energy consumption is jointly integrated with the operational criterions when executing material delivery tasks. Owing to the NP-hard nature of the considered problem, a Taboo enhanced Particle Swarm Optimization (TEPSO) algorithm is developed to solve the multi-objective problem. Several improving strategies are applied to enhance the performance of the proposed TEPSO in order to obtain a stronger local search capability and faster search speed. The performance of the proposed TEPSO algorithm is evaluated by comparing with two other high-performing multi-objective optimization methods. Computational experiments are conducted in order to test and verify the effectiveness and efficiency of the proposed TEPSO algorithm. The achievements reported in this paper might be inspiring for further studies on energy-efficient production scheduling. [ABSTRACT FROM AUTHOR]

As one of the most widely used power sources in the engineering field, compressed air is especially common in industrial applications. In a traditional pneumatic circuit, a three-position five-way valve is used to control the air inlet and exhaust with a single pressure, which has low efficiency. This paper proposed a novel bridge-type circuit with variable pressure control using four on-off valves to improve the energy efficiency of compressed air for pneumatic actuators. The key idea of the method was to use air expansion energy to do work. Reducing the volume of consumed air was the goal, and a numerical method was presented to calculate the optimal on-off time sequence of the four valves using nonlinear dynamic optimization. The sequence was obtained based on the combination of a finite element polynomial configuration method and a reduced space sequential quadratic programming algorithm. Then, experimental validation was conducted to illustrate the energy efficiency, including pneumatic cylinder motion test under different conditions. Compared with the traditional circuit, the experimental results show that the bridge-type circuit put forward by this paper can significantly improve the energy efficiency of pneumatic driving systems by 50–70%. Additionally, the bridge-type circuit allows the piston to move smoothly to the end of the stroke, which can take the place of the function of cushion component and speed control valve of the traditional circuit. [ABSTRACT FROM AUTHOR]

Within the urban water cycle, energy issues have been mostly studied for wastewater treatment plants, ignoring that drinking water treatment plants (DWTPs) also consume a significant quantity of energy. Knowing the real energy consumption of DWTPs is the starting point for any energy-saving initiative. This paper benchmarks the energy efficiency measures of a sample of real DWTPs using the data envelopment analysis methodology. Subsequently, whether these facilities are affected by economies of scale is investigated. This issue is essential for planning new DWTPs that minimize energy consumption. In the second stage of analysis, some structural and managerial variables affecting energy efficiency are explored. The results showed that most of the DWTPs analysed have a suitable size but can greatly improve in terms of saving energy. It was found that the age of the plants and the water company operating them significantly affects its energy efficiency. The approach applied in this paper is of great interest for water regulators and company managers since it enables them to learn from the best practices for reducing energy consumption in DWTPs and contributes to improving the sustainability and efficiency of the urban water cycle. [ABSTRACT FROM AUTHOR]

During its operation, a photovoltaic (PV) panel is exposed to various and in general, stochastic thermal and wind conditions, which have a significant influence on the PV panel operating temperature. The increased PV panel operating temperatures normally have an unfavorable effect on the PV panel performance and lifetime, thus various cooling methods were proposed in order to increase the photovoltaic energy conversion efficiency. A reasonable step before the consideration of a specific cooling strategy is to obtain a PV panel performance analysis with respect to its surroundings (specific geographical micro location) for various operating conditions. This paper presents such a study, which was conducted through an experimentally validated numerical model. Numerous CFD simulations regarding heat and fluid flow around a monocrystalline PV panel coupled with a heat flow simulation inside the PV panel elements were conducted. The aim of the paper was to investigate an effective heat transfer field and the variations in the PV panel temperatures with respect to various wind velocities and heat source conditions. A detailed study regarding pressure, viscous and body (buoyancy) forces as well as their effects on flow separation was also conducted. The study also investigated the changes in the effective heat transfer near the PV panel. The gained results in this study turned out to be useful for the consideration of a specific cooling strategy for PV panels, which can ultimately lead to an increase in PV panel efficiency and lifetime. Additionally, the conducted study could be used to improve the delivered electricity prediction from the PV system at a selected location defined by specific wind velocities and solar insolation distributions. [ABSTRACT FROM AUTHOR]

One-third of global energy demand as well as CO 2 emissions is accounted to industrial processes. In particular, over 30% of total industrial energy consumption is attributed to the iron and steel, cement and refining industry. The aim of the present paper is to review crosscutting technologies and measures adopted to improve energy efficiency in the main Italian industrial sectors regulated by the recent EU legislation on integrated pollution prevention and control (IPPC-IED). In fact, 2010/75/EU Directive on industrial emissions, a general improvement on the entire environmental performance of the industrial installations is pursued by taking into account relevant environmental issues, such as emissions into water, air, soil as well as energy efficiency, waste production, recovering and recycling, restoration of the site upon definitive cessation of activities. Moreover, according to 2010/75/EU Directive, IPPC permits should be based on Best Available Techniques (BAT) aimed to reach an adequate level of environmental protection and should establish all the necessary measures including operating conditions, emission limit values for relevant polluting substances as well as monitoring requirements. Thus, in the present paper an assessment of Best Available Techniques (BAT) related to energy efficiency in the main Italian industrial installations is carried out on the base of the analysis on the IPPC permits released by the Italian Ministry for the Environment, Land and Sea, and made available on its web site. As a result a significant improvement in energy efficiency was assessed. In fact, many process units were upgraded, by major revamping or even by replacing the process completely with one showing better performances. Finally, since energy efficiency is at its best at the beginning of the life cycle of the plant, operators, whenever necessary, periodically monitor and measure the actual energy performance of their own installations for process control and maintenance purposes. [ABSTRACT FROM AUTHOR]

Whether industrial agglomeration can promote an increase in energy efficiency is of great importance to not only China’s energy conservation and emissions reduction plans, but also China’s future sustainable development. This paper uses statistical data from 285 cities, from 2004 to 2013, to analyze the effect of industrial agglomeration on energy efficiency. The spatial autocorrelation tests show that there is significant spatial autocorrelation and spatial heterogeneity in urban energy efficiency. Although dynamic spatial econometric results show that industrial agglomeration can promote an increase in energy efficiency from a country level, there are significant differences at a regional level. In the east, the effect of industrial agglomeration on energy efficiency has a threshold effect, but in central and western areas, industrial agglomeration can promote the increase of energy efficiency, with the positive effect in western areas greater than that in central areas. Finally, based on the research, this paper puts forward concrete suggestions to enhance energy efficiency. [ABSTRACT FROM AUTHOR]

Energy consumption is a major sustainability focus in the metal cutting industry. As a result, process planning is increasingly concerned with reducing energy consumption in machine tools. The relevant literature has been categorized into two research areas. The first includes energy prediction models, which characterize the relationships between cutting parameters – the main outputs of process planning - and energy consumption. The second involves energy-consumption optimization, which uses the prediction models to find the cutting parameters that minimize energy use. However, previous energy prediction models are limited to predict energy for tool paths coded in a Numerical Control (NC) program. Previous energy optimization methods typically do not use online optimization, which enables fast optimization decision-making for supporting on-demand process planning and real-time machine control. This paper presents a component-based energy-modeling methodology to implement the online optimization needed for real-time control. Models that can predict energy up to the tool path-level at specific machining configurations are called component-models in this paper. These component-models are created using historical data that includes process plans, NC programs, and machine-monitoring data. The online optimization is implemented using a dynamic composition of component-models together with a divide-and-conquer technique. The feasibility and effectiveness of our methodology has been demonstrated in a milling-machine example. [ABSTRACT FROM AUTHOR]

A sustainable hydraulic system is proposed to cool the slurry manure and mitigate the ammonia emissions of livestock buildings, a major source of environmental pollution. In this paper, analytical and numerical methods are used to evaluate the energy efficiency and the mitigation capability of the hydraulic cooling system. Results show that annual primary energy use of only 6.08 kWh per animal can reduce 5.87 kg of ammonia per animal per year. The system is most efficient for manure with less than 12% total solids content. Results also show that the liquid region above the cooling pipes features one-dimensional transient heat transfer formed by unique flow patterns. A simplified analytical model is derived to predict the surface temperature of liquid manure. The analytical solution shows that the manure surface temperature can be reduced by 7.4 and 12 °C after 2 and 5 h, respectively. The temperature reduction results in up to 37.3% decrease in ammonia emissions with only 0.8% of the total energy use in livestock buildings. • An energy efficient cooling system is proposed to reduce emissions from buildings. • Using primary energy of only 6.08 kWh can reduce 5.87 kg NH3 per animal per year. • The cooling system uses only 0.8% of the total energy use in a livestock building. • The cooling system can reduce up to 37.3% NH3 emissions from livestock buildings. • An analytical model is derived to predict the surface temperature of liquid manure. [ABSTRACT FROM AUTHOR]

Pinch Analysis (PA) and Exergy Analysis have been used, either independently or in combination, for energy integration of process plants. This paper discusses a methodology to apply PA and Exergy Analysis during design of a new process plant to make it energy efficient, using Diesel Hydrotreating Unit (DHT) as an example. PA has been used to estimate the Minimum Energy Requirement (MER), to select utilities and to design the optimal Heat Exchanger Network (HEN). Exergy Analysis is then performed to pinpoint the sources of energy inefficiency in the whole plant and suggest improvements. The application of these two techniques has helped in energy integration of the plant during the design phase itself. Two common layouts of diesel hydrotreating unit—the 'hot separator layout' and the 'cold separator layout'—have been studied. The minimum Total Annualized Cost (TAC) is ∼7.6 M€/y and ∼10 M€/y for the hot separator layout and the cold separator layout respectively. Exergy destroyed is 27.15 MW (7.9% of exergy input) and 50.18 MW (6.7% of exergy input) respectively for the hot separator layout and the cold separator layout. Exergy Analysis reveals that the energy efficiency can be improved for air coolers, fired heaters and letdown valves. • Pinch and exergy analysis carried out on design of new DHT. • HEN with minimum TAC obtained by pinch analysis. • Sources of energy inefficiency identified by exergy analysis. • Modifications for improving energy efficiency provided. • Equipment modifications resulted in higher exergetic efficiency. [ABSTRACT FROM AUTHOR]

Modern manufacturing enterprises are consuming a considerable amount of energy every year. Improving energy efficiency will not only benefit the enterprises economically, but also help the world to overcome various problems such as energy crisis and air pollution. To achieve this, an accurate energy consumption model is essential. The main objective of this paper is to develop an improved cutting power-based energy consumption model for general end milling process. The proposed model consists of an idle part due to auxiliary components and spindle rotation, and an additional part due to cutting workpiece materials. The first part is modelled as a function of spindle rotation speed, and the other part is considered proportional to the cutting power. Experiments under various milling conditions have demonstrated the effectiveness and efficacy of the proposed model. Comparative studies show that the proposed model is more accurate than other models. Although calibrated from slotting experiments when cutting aluminium alloy, the proposed model is applicable for general milling process. Partial-immersion milling experiments show that the prediction error of the proposed model is as low as 1.74%. When workpiece material changes to titanium alloy, its performance remains decent, with low prediction error of 2.81%. This reveals its capability to provide reliable estimation for different workpiece materials. As such, it could help avoid tedious model calibration, thus saving time, material, and energy. Finally, the energy efficiency of general end milling process is investigated through numerical experiments with the proposed model. By revealing the relationship between energy consumption and various cutting parameters, the proposed model could serve as an excellent platform towards energy-efficient manufacturing/cleaner production. • A new energy consumption model (ECM) for general end milling is proposed. • The ECM's accuracy and reliability is validated by general milling experiments. • The ECM significantly improves the prediction accuracy than other major models. • Energy efficiency can be analyzed with the ECM via numerical experiment. • The ECM contributes to cleaner production by saving time, material, and energy. [ABSTRACT FROM AUTHOR]

The role of smart technologies can become very important and useful to solve the main population issues nowadays and provide foundations for a sustainable future. A smart approach is an opportunity for knowledge integration, necessary to solve crucial problems of contemporary societies. Today, the main challenge is to reduce the effects of global warming and ensure a balanced economic development of society. The close collaboration of all involved engineering professions is mandatory to achieve interdisciplinary synergies and can bridge challenging engineering tasks. Intense research efforts should be directed towards balanced resource utilization, efficient energy conversion technologies, integration of renewable energy systems, effective approaches to enable circular economy framework, effective process integration as well as other issues important to the population. This review editorial is primarily focused on the contributions presented at the 3rd International Conference on Smart and Sustainable Technologies held in Split, Croatia, in 2018 (SpliTech2018). The SpliTech2018 conference was a multidisciplinary event with research topics related to the main conference tracks, i.e. Smart City/Environment, Energy, Engineering Modelling and e-Health. The strategic focus of the conference was to help solve crucial issues of our times, mainly related to the sustainability and smart utilisation of limited and valuable resources. This contribution brings new ideas and discusses present issues as well as challenges that should lead towards a sustainable future based on the application of the smart technologies. The herein addressed papers bring together latest research progress into four main topic areas: (i) Green Buildings, Energy Use and Consumption, (ii) Solar Energy Utilisation, (iii) Efficiency and Waste Elimination, (iv) Smart Cities and Internet of Things. The main results of this introduction review article include a discussion of different concepts and technologies that bring further development on a broad range of topics focused on efficiency improvement, smart and sustainable resource management, cleaner production concepts and on the discussion of the various actions which would lead towards a sustainable future. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of the implementation of smart city policy (SCP) on energy efficiency (EE) in China. For this purpose, we have developed a non-convex metafrontier data envelopment analysis (DEA) approach to measure EE, and empirically examine the impacts of SCP on China's EE using Difference-in-Differences (DID) analysis, using a dataset of 251 cities between 2003 and 2016. Results show that there exists significant regional heterogeneity across cities, with the SCP exerting a significant positive effect on EE, indicating that the SCP can effectively improve EE during the study period. These findings are robust to different sub-sample, energy efficiency alternative measures, estimation strategies, and Baidu Search Index. Based on empirical results, the implications of SCP are outlined. • Energy efficiency measures of 251 Chinese prefectural-level cities are estimated. • Eastern region performs the best, followed by the central and western regions. • The effects of smart city policy on energy efficiency is investigated using DID method. • The smart city policy can effectively improve energy efficiency during the study period. • Empirical results are robust to different sub-sample, energy efficiency alternative measures, etc. [ABSTRACT FROM AUTHOR]

This paper estimates the linkages among total Sulphur dioxide (SO 2) emissions, total GDP and energy efficiency using China's provincial panel data from 2002 to 2015. We investigate total emissions rather than per capita emissions or ambient concentrations since it is total emissions that the environment cares about. Energy efficiency is estimated using stochastic frontier analysis and decomposed into both persistent and transient efficiency. We then investigate the long-run dynamics among SO 2 emissions, economic growth, and energy efficiency by employing the panel-based error correction model and taking the effects of cyclical variations into account. Our analysis shows that GDP has a positive impact on total SO 2 emissions in the short run and gains in energy efficiency have a significant negative effect on emissions in the long run. By controlling the effects of the business cycle, the effects of GDP on emissions remain positive in both the short and long run. The cross-sectional analysis provides similar insights. We argue that economic growth itself is an emission generator. Therefore, the government needs to establish a long-run strategy to curb emissions by improving energy efficiency. Image 1029 • We estimate the linkages among sulphur dioxide emissions, GDP and energy efficiency. • Energy efficiency is estimated by SFA and decomposed into persistent and transient efficiency. • We employ the panel-based error correction model with cyclical variations and structural break. • GDP has a positive impact on emissions in both the short and long run. • Gains in energy efficiency affects emissions negatively in the long run. [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]

With the advent of the era of big data, large-dimensional spatial panel data is gradually used to do empirical research in the macroeconomic field. This paper adopts a Data Envelopment Analysis(DEA) approach to calculate regional energy efficiency based on the perspective of total-factor energy efficiency using statistical data of 30 administrative regions in China. On basis of spatial effects, the paper assesses the convergence of regional energy efficiency in China using large-dimensional spatial panel data model. Our results indicate that (1) There is significant spatial autocorrelation and clear spatial effects in China's regional energy efficiency. Thus, spatial effects should not be ignored when assessing the convergence of regional energy efficiency in China; (2) During the period from 2000 to 2014 China's regional energy efficiency not only exhibits absolute β -convergence but also exhibits conditional β -convergence, the convergence rate is higher than the rate of absolute convergence after controlling for the initial conditions of the level of economic development, foreign direct investment and government influence; (3) The convergence rate of China's regional energy efficiency from 2004 to 2014 is higher than the convergence rate for the period of 2000–2004, which indicates that industry transfer has contributed to improvement in the convergence of regional energy efficiency in China since 2004. [ABSTRACT FROM AUTHOR]

In a multi-pass face milling process, cutting parameters for each pass and the total number of passes dramatically affect the electrical energy consumption and production cost of the final product. In this paper, the electrical energy consumption characteristics of multi-pass face milling are firstly analyzed. Then a multi-objective parameter optimization model for maximizing energy efficiency and minimizing production cost is proposed and solved by the Adaptive Multi-objective Particle Swarm Optimization algorithm. Finally, a case study is carried out to validate the proposed model and search for the trade-off solutions between maximum energy efficiency and minimum production cost. From the results of the case study, significant interaction effects between cutting parameters and number of passes are revealed. Moreover, it also can be found that the traditional multi-pass parameter optimization for minimizing production cost does not necessarily satisfy the maximum energy efficiency criterion. Simultaneously optimizing the cutting parameters of each pass and the total number of passes achieves a trade-off between maximum energy efficiency and minimum production cost. Based on the work presented in this paper, manufacturers can easily improve energy efficiency and reduce production cost in the multi-pass face milling process. [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]

Excessive energy consumption and carbon dioxide emissions are long lasting issues and need continuous research to improve efficiency evaluation and performance monitoring of economies. The static and dynamic aspects of efficiency need to be dealt with simultaneously to thoroughly analyze the performance of economies. This paper aims at conducting a static and dynamic analysis of energy and CO 2 emissions efficiency of major economies. In this paper, we applied slacks based model of Tone (2001) with the treatment of undesirable output in objective function and constraint assuming free disposability of undesirable output and built a dashboard. The results can be summarized by saying that the larger economies with intensive production strategy, larger secondary industry, and weaker carbon tax laws are more likely to be inefficient. China, India, and Russia have the greatest potential for improvement in both energy efficiency and carbon dioxide emissions efficiency. The suggested dashboard has the ability to dig out the potential for efficiency improvement of countries like the USA, which mostly appear at the efficient frontier with other techniques. Concluding it can be suggested that economies in lower ranks of dashboard need stricter policy measures to cut energy consumption, carbon dioxide emissions and encourage a shift from fossil fuels to other renewable resources of energy. [ABSTRACT FROM AUTHOR]

This paper presents the application of the Discrete Event Simulation (DES) in an industrial plant to analyze the behavior of the consumption and generation of electrical energy in conjunction with other variables of the process. In other words, the process modeling was conducted considering the energy consumption in equipment as well as the local photovoltaic (PV) energy generation. A medium-sized plant was the reference base used herein, and the main variables considered were the time of supply of tanks and processing of raw material, active power of equipment and energy tariffs. A simulation model with resolution in seconds was designed, enabling the simulation of consumption curves of each equipment of a given part of the production process. The equipment of variable active demand was modeled by a mathematical regression method, and the others were assumed with constant power. The same model was altered to unit in minutes for simulating the monthly electricity consumption, so as to obtain financial results. The contractual rules for electricity supply were included, and the use of a diesel-powered generator was taken into account. The application of a freeware was employed as a low cost alternative for small and medium-sized companies, even though the lack of graphic resources has increased the complexity of the system modeling process. The model with resolution in seconds proved to be efficient to simulate the consumption profile of a specific equipment that alters the power in a short-time period, such as the pumps. The model, on the other hand, in minutes allowed a more effective analysis in terms of finance, enabling the verification of alternative scenarios throughout a month. The monthly cost reduction perceived by considering self-generation in this model was about 36%. Detailed diagram of the main elements of modeling of a manufacturing process of an industry concentrating on the consumption and generation of electric energy. Image 1 • The electricity consumption in an industrial process can be approached in a simulation model. • PV energy can be simulated together with variables of industrial processes. • The discrete event simulation can be used in industrial processes to optimize the electricity management. [ABSTRACT FROM AUTHOR]

Abstract Electrical discharge machining is a significant non-traditional technique, widely used in the precise manufacturing field. However, the electrical discharge machining process possesses plenty of energy consumption and hazardous exhaust emissions. Since a sustainable machining technique, external magnetic field assisted, could dramatically develop sustainable machining performance of electrical discharge machining process, this paper presents a comparative study energy efficiency and environmental impact in magnetic field assisted electrical discharge machining and conventional electrical discharge machining. A novel thermo-physical model was proposed to calculate energy distribution under the single/continuous discharge, which was verified by a series of corresponding experiments. Then, based on simulation and experimental methods, a comparative study on the magnetic field assisted electrical discharge machining and conventional electrical discharge machining was conducted to analyze the discharge energy flowing and temperature distribution of workpiece, electrode tool and debris. Moreover, the effects of external magnetic field on the machining performance, environmental impacts and energy efficiency were presented. Eventually, it can be found out that the effect of magnetic field contributes to increasing energy utilization efficiency by 15.2%, material erosion efficiency by 22.6%, and material removal rate by 21.9%. To balance energy efficiency and surface roughness (Ra), the optimal parameter combination is obtained as below: magnetic field intensity: 0.2T, discharge current: 7–9A, and pulse duration: 300s. Highlights • Magnetic field assisted EDM improve energy efficiency and environmental impact. • A thermo-physical model is proposed to calculate energy distribution of MF-EDM process. • Sustainable machining performance of EDM and MF-EDM are comparatively investigated. • The optimal parameter is: magnetic field intensity: 0.2T, current: 7∼9A, and pulse duration: 300μs. [ABSTRACT FROM AUTHOR]

Abstract There is increasing interest in the idea that energy efficiency has economic, environmental and social impacts beyond energy and cost saving - a 'multiple benefits' perspective. However, present EU-decision making on energy efficiency is based on assessment of a very narrow range of costs and benefits. This paper investigates whether and how advocates of energy efficiency have used multiple benefits to frame their interactions with policy-makers at EU and UK level, and to broaden the appeal of energy efficiency. Nine semi-structured interviews were conducted with key practitioners from industry-backed or trade organisations and environment-focussed NGOs. All respondents regularly made use of multiple benefits arguments. Their experience is that these arguments are most persuasive when linked to the values and priorities of decision-makers and politicians, most of whom do not value energy efficiency as a benefit in itself. Different contexts and different benefits are more or less salient for different stakeholders. This framing sets energy efficiency decisions in a broad economic, environmental and social context. As such it requires more evidence than a simple focus on energy savings, and different sorts of evidence which can connect with a variety of decision makers. The importance of recognising differing contexts, actors, values, priorities has led to the development of an alternative visualisation of multiple benefits, which de-centres energy efficiency. Highlights • 'Multiple benefits' identifies economic, social and environmental impacts of energy efficiency. • Leading NGOs and trade associations use this framing to influence EU policy makers. • Multiple benefits arguments work best linked to values and priorities of policy makers. • Persuasive case studies as well as quantitative evidence are required. • A new visualisation of multiple benefits has been developed, which 'de-centres' energy efficiency. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of urbanization on provincial energy efficiency in China. Using panel data of 30 Chinese provinces between 2003 and 2014, we adopt a stochastic frontier model to estimate energy efficiency in China, and apply a series of spatial panel data models to tackle spatial dependence of energy efficiency between provinces. Our results show that the overall impact of urbanization on energy efficiency is negative in China. These results are established after controlling for spatial correlation and other confounding factors, and are also robust to various model specifications. We also document that the impact of urbanization on provincial energy efficiency manifests through both a direct negative impact induced by the focal province's urbanization process, and an indirect positive spillover effect caused by urbanization in adjacent areas. [ABSTRACT FROM AUTHOR]

Machining workshop is a widely distributed manufacturing system that consumes massive energy in a low efficiency. In recent years, the increasing pressure from energy price and environmental directive have forced machinery manufacturers to address energy efficiency monitoring and management to improve economic benefits and environmental performance. However, due to the complicated energy flow and dynamic energy changes of the machining workshop, machinery manufacturers still lack an effective method to monitor and manage the energy efficiency in a practical manner. To this end, this paper proposes an energy efficiency monitoring and management system with the support of the newly emerging Internet of Things (IoT) technology. Firstly, the energy characteristics and energy efficiency indicators of the machining workshop are analyzed and defined. Then the framework of the IoT based energy efficiency monitoring and management system is proposed. The key approaches for energy efficiency monitoring and management are then illustrated. Finally, an industrial application is demonstrated to validate the effectiveness and benefits of the proposed system. With the application of the proposed system, potential opportunities for energy consumption decrement and energy efficiency improvement can be identified. Machinery manufacturers can easily reduce energy consumption and energy cost by managing the machining process. [ABSTRACT FROM AUTHOR]

Abstract The more efficient use of energy is a policy issue worldwide. Smart use of technology and management of information is becoming crucial for increasing energy efficiency. The 7th Framework Program of the European Union supported international research to fulfill the potential of Information and Communications Technologies for Energy Efficiency. Using Social Network Analysis, this paper analyzes this research network and explores the links and influences in the cross-country knowledge flows generated. The analysis identifies some important differences in the position that countries hold on the network. Results highlight the importance of countries acting as hubs and gatekeepers in the promotion of research and the improvement of energy efficiency. Highlights • The network of the 7th Framework Programme on Information and Communication Technologies for energy efficiency is studied. • Countries with a central position in the research network benefit from energy efficiency gains. • A fast access to knowledge does not guarantee efficiency improvements. • Climate-resilient countries tend to have more adaptation in terms of efficiency. [ABSTRACT FROM AUTHOR]

This paper reviews the incentives for pursuing a low-carbon electricity sector that are embedded in China's regulatory and policy framework. To do so, we first describe the industry structure and the regulatory framework. Second, we explicitly review the policies that were developed to promote energy efficiency and renewable energy. These policies range from the introduction of legal requirements to undertake particular actions to pricing mechanism and financial incentives. Based on this, we tease out the challenges faced by a sector governed by a myriad of complex arrangements, different institutions and agents who face different and often conflicting incentives for pursuing environmental and energy efficiency objectives. Finally, we provide suggestions to scientifically set up low-carbon policies and to achieve the expected goals with minimum social cost. [ABSTRACT FROM AUTHOR]

Energy efficiency state identification of milling process plays an important role in energy saving efforts for manufacturing systems. However, it is very difficult to track energy efficiency state in machining processes based on traditional signal processing strategies due to the fact that energy state is usually coupled with a lot of factors like machine tool states, tool conditions, and cutting conditions. An identification method of information reasoning and Hidden Markov model for energy efficiency state is proposed in this paper. Utilizing cutting conditions, empirical models of the energy efficiency, experimental data and signal features, an expert system is established for initial probability optimization and the state is further identified by Hidden Markov model. The experiments show that energy efficiency state can be identified with this method. [ABSTRACT FROM AUTHOR]

A fundamental problem in the management of energy usage is the inability to clearly predict any possible energy saving opportunities. The cost of both under or overestimating potential returns on investment can be prohibitive to a decision maker. In recent years the simulation of energy usage using existing manufacturing simulation tools has increased in popularity among researchers, but it is decision makers who need to see the benefits of this discipline. This paper proposes an interactive manufacturing energy management toolkit which makes use of existing productivity simulation models for the prediction of energy usage. An interactive Microsoft ® Excel ® based toolkit is developed to control Lanner's WITNESS ® discrete-event simulation software using Microsoft ® Visual Basic ® for Applications. The toolkit has the ability to predict potential areas where energy saving opportunities can be made within a complex manufacturing line, and is accessible from management presentations and proposals. The interactivity of the toolkit provides an environment which facilitates efficient hypothesis testing. The paper includes an industrial case study where the approach was used to quantify theoretical savings from certain energy usage reduction scenarios within a complex automotive engine manufacturing line. [ABSTRACT FROM AUTHOR]

Significant increases in industry energy efficiency are crucial for the transformation of the world's energy systems. Many production sites offer high energy savings capabilities, and if these are accompanied by short periods of economic amortization, companies should be willing to act. This case study provides a novel and extended energy assessment for plastics processing plants including primary energy, greenhouse gas emissions, and energy costs. The research distinguishes between the standard form of separate individual energy assessments and provides a more innovative holistic approach taking all relevant energy flows within the production system into account. Dynamic simulation offers a quick and effective way to predict the results of the possible energy saving measures highlighted in this analysis. The paper presents validated energy consumption simulations based on realistic processing conditions for two injection molding factories in different climatic zones. The results show that combining a number of separate energy saving measures can reduce the primary energy demand by around 26% for a German plant under temperate climate conditions and 20% for a Western Australian plant under Mediterranean conditions. However, when the separate energy saving measures are holistically combined the reduction in energy use significantly increases to 41% and 43% respectively. This holistic energy strategy involves incorporating better cogeneration and waste heat recovery options. For small and medium sized companies in particular major energy infrastructure investments may often be considered too expensive without examining the extended benefits from a holistic energy assessment perspective. In contrast, a holistic framework, like the one suggested in this paper could provide a number of new options for increasing energy efficiency that individually might normally not be accepted under conventional economic rate of return analysis. [ABSTRACT FROM AUTHOR]

This paper presents a review of the literature on energy efficiency in mining with a specific emphasis on the role of operators in energy efficiency of loading and hauling operations. The objectives are to: (i) establish the current knowledge on energy efficiency in mining, in general; (ii) establish current knowledge on the role of the operator in energy efficiency of loading and hauling operations, specifically; and (iii) make recommendations for industrial best practice and future research directions to enhance energy efficiency in mining. The papers included in the review were selected through searches in major abstract databases using relevant keywords, with emphasis on recent peer-reviewed work. The review identified gaps in the literature and made recommendations for future research and industry best practice. [ABSTRACT FROM AUTHOR]

Environmental efficiency improvement has played a crucial role in the theory and practice of stimulating clean production. This paper analyzes the interaction between environmental efficiency and output efficiency, particularly whether they reinforce each other or compete with each other, on the basis of a data set of 137 firms in the textile industry in China's Jiangsu Province. In the first stage, generalized data envelopment analysis is applied to calculate efficiency measures of energy, waste water, waste gas, soot, and output efficiency taking capital, labor, water, and energy as inputs, industrial output value as desirable output, and waste water discharges, waste gas and soot emissions as undesirable outputs. In the second stage analysis, a structural equation model with latent variables is applied to analyze the interaction between the latent variable environmental efficiency, measured by the four observed environmental indicators, and output efficiency, taking also into account the endogenous variable profit. The main outcomes of the structural equation model are the following. Firstly, environmental efficiency negatively impacts on profit while profit positively impacts on environmental efficiency. In a similar vein, output efficiency is found to depress profit while profit increases output efficiency. Thirdly, environmental efficiency has a positive impact on output efficiency while there is no effect of output efficiency on environmental efficiency. Fourthly, taxes impair a firm's output efficiency. From the findings it follows that a swap of general taxes for an energy tax is likely to improve both output efficiency and energy efficiency. The latter outcome implies a win–win situation which will facilitate the further implementation and adoption of environmental policy. Finally, the paper illustrates the applicability of structural equation modeling in efficiency analysis. [ABSTRACT FROM AUTHOR]

Legislation targeting business carbon emissions typically excludes the significant portion of the economy comprised of small- and medium-sized enterprises (SMEs). As an alternative many governments have developed voluntary programs to assist SMEs to reduce emissions and increase their energy efficiency. To maximise benefits associated with such programs, this paper seeks to provide insights into key factors contributing to the design of successful voluntary energy efficiency programs for SMEs. This is achieved by comprehensively analysing the factors that impacted the uptake of energy savings measures by 202 SMEs which participated in the ClimateSmart Business Cluster Program (commencing in 2009). Expanding on previous research that has mostly focus on identifying inhibiting factors (barriers) to the uptake of energy savings measures, this paper offers a comprehensive assessment of barriers and motivating factors (motivators). A unique finding of this research is that SMEs experienced many different barriers and motivators while participating in the program, inferring great complexity to achieving the critical aim of reducing carbon emissions. Based on these findings, this paper argues that voluntary government energy efficiency programs should be flexibly designed and implemented to accommodate the many and various barriers. Motivating factors should be emphasised and barriers identified upfront so that the program can be tailored to the often idiosyncratic needs of SMEs. [ABSTRACT FROM AUTHOR]

The building sector is considered as the biggest single contributor to world energy consumption and greenhouse gas emissions. Therefore, a good understanding of the nature and structure of energy use in buildings is crucial for establishing the adequate future energy and climate change policies. Availability of the updated data is becoming increasingly important in order to allow a rigorous analysis. In this paper, recent data on the world energy consumption in both residential and commercial buildings are reported. Past situation, current status and future trends are discussed and analyzed for selected countries. A breakdown of buildings energy consumption is realized in order to determine the influencing key parameters. A whole section of this paper is dedicated to give an overview of measures and policies adopted by different countries, allowing the monitoring, management and reduction of the energy consumption in buildings. Critical aspects of these policies are discussed based on the feedback of the early adopters. [ABSTRACT FROM AUTHOR]

Energy efficiency is a complex topic to integrate into higher education curricula, with limited success internationally or in Australia. This paper discusses one of the successful initiatives within the Energy Efficiency Training Program , which was jointly managed and implemented by the New South Wales Office of Environment and Heritage and Department of Education and Communities. The state government initiative aimed to increase the knowledge and skills of the New South Wales workforce, help business to identify and implement energy efficiency projects, and provide professional development for the training providers. Key sectors targeted included property, construction, manufacturing and services. The Program was externally evaluated over the three years 2011–2013 and a range of insights were gained through these facilitated reflective opportunities, confirming and building upon literature on the topic to date. This paper presents lessons learned from the engineering part of the program (‘the project’), spanning government agencies, academic institutions, and academia. The paper begins with a contextual summary, followed by a synthesis of key learnings and implications for future training initiatives. It is intended that sharing these lessons will contribute to literature in the field, and assist other organisations in Australia and overseas planning similar initiatives. [ABSTRACT FROM AUTHOR]

The textile industry uses large amounts of electricity, fuel, and water, with corresponding greenhouse gas emissions (GHGs) and contaminated effluent. Emerging energy-efficiency, greenhouse gas (GHG), and pollution mitigation technologies will be crucial for the textile industry as it responds to population and economic growth that is expected to spur a rapid increase in textile consumption over the coming decades and a corresponding increase in the industry's absolute energy use and GHG and other pollutant emissions. This paper gives an overview of textile industry processes and compiles available information on the energy savings, environmental and other benefits, costs, commercialization status, and references for 18 emerging technologies to reduce the industry's energy use and environmental emissions. Although studies from around the world identify a variety of sector-specific and cross-cutting energy-efficiency technologies that have already been commercialized for the textile industry, information is scarce and/or scattered regarding emerging or advanced energy-efficiency and low-carbon technologies that are not yet commercialized or at the very early stage of adoption. This paper is intended to be a resource on these emerging technologies for engineers, researchers, investors, textile manufacturers, policy makers, and other interested parties. [ABSTRACT FROM AUTHOR]

Energy management systems are considered as appropriate instruments to identify and realize energy efficiency potentials in industrial plants. Studies point out a largely untapped potential for energy efficiency in industry through the adoption of systematic energy management. We suggest introducing qualitative and quantitative modelling tools into energy management to facilitate a focused process to set priorities and identify effective measures. This paper describes the case of voestalpine Austria Draht GmbH, an Austrian wire rolling mill. voestalpine Austria Draht GmbH at present is implementing a knowledge based energy management system. Within the work described in this paper, first an overview of energy flows using Sankey diagrams was elaborated. Then a qualitative systems analysis was developed for the plant and a gap analysis done for priority areas. Subsequently physical input–output models for several energy intensive units were prepared. The paper describes the models for the cooling water system and product cooling. This study revealed a significant potential to save electricity by optimizing the control of cooling water pumps along the milling train and to recover heat from the final products. 2 GWh of electricity can be saved annually. The biggest single energy loss in the mill is the heat from air cooling the products on hook conveyors. These heat flows contain about 30–50 % of the energy input for heating up the billets. Following a theoretical analysis of the potential, a demonstration plant was developed and pilot tests were run to characterize the realistic potential of heat recovery on the hook conveyor. Based on the test results, feasibility studies for large scale plants were carried out. As a result, 0.8 GWh of heat can be recovered annually. The method was found useful because it helped to structure the existing information with a reasonable effort mostly by the operators themselves in their work and to build a conceptual model of energy flows and energy efficiency of the total plant. [ABSTRACT FROM AUTHOR]

The European Union energy label informs consumers at the point of sale about the energy efficiency and electricity consumption of various electric goods. The label should enable consumers to purchase energy-friendly products (i.e., products with low energy consumption), thereby making a significant contribution to the reduction of overall energy consumption. This paper offers a systematic analysis of consumers' interpretation of the energy label. The results of a set of experimental studies revealed that consumers tend to base their estimates of a product's energy consumption mainly on the energy efficiency class (e.g., A) communicated on the energy label and largely ignore information about annual electricity consumption (e.g., 120 kWh/year). Thereby, consumers potentially overestimate the energy friendliness of a product assigned a high energy efficiency rating. This also holds true when consumers directly compare two products in terms of energy friendliness. Thus, participants chose a higher-consuming product because it had a high energy efficiency rating. High energy efficiency ratings (e.g., A +++ ) can distort consumers' perceptions of product categories that consume excessively (e.g., freezers). Participants were seduced into thinking that a high energy efficiency rating (e.g., A ++ ) means the energy consumption of energy hogs is no longer problematic. This paper provides evidence that the energy label could have a contrary effect than the one intended due to people's susceptibility to an energy efficiency fallacy. This misinterpretation of the energy label could further explain why overall energy demand is increasing despite enhanced energy efficiency. Finally, implications for policy makers and further research for enhancement of the energy label are discussed. [ABSTRACT FROM AUTHOR]