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This paper presents an empirical analysis of the impact of adopting energy efficiency measures, labeled “White Certificates”, on the economic performance of companies active in the paper and glass sector in Italy. White Certificates, launched in 2005, represent the longest-lasting and effective policy tool to stimulate energy efficiency, in particular for the manufacturing industry. My analyses exploit financial statements of Italian companies available from the AIDA (Computerized Analysis of Italian Companies) database with the aim to quantify the impact of these measures on the performance of firms in the two industries. The impact of energy efficiency policies is assessed on both productivity and profitability, and the effect is broken down into direct and indirect impacts, obtained by calculating spatial lags of energy efficiency support based on geographical as well social, relational, and technological proximity matrices. Results suggest the existence of a positive and significant association between White Certificates and firm performance. This effect is fostered when support also goes to other firms that are relationally, socially, and technologically close to treated firms. Instead, no synergy between social, relational, and technological connectivity and the geographical co-location of firms is found.

A key challenge in prevention of global warming is how to increase energy efficiency, to be able to deal with increased fossil CO2 emissions from rising energy usage. Increasing energy efficiency will decrease energy usage and is in a key role in emission mitigation. The focus is the pulp and paper industry, which is energy-intensive. Development of industrial energy efficiency has been studied before but the role of industrial transformation is still mostly unknown. The knowledge must be improved, to be able to predict future developments in the most effective way. In this research, impact of various production unit closures and start-ups on energy efficiency of the Finnish pulp and paper industry were studied utilizing statistical analysis. Results indicate that about 20% of the Finnish pulp and paper industry energy efficiency improvement between 2011 and 2017 is caused by the major structural changes. The rest, 80% of the progress, was mainly due to improved technology and more optimal operational modes. Additional findings suggest that modern mill start-ups have a significantly greater potential to reduce energy consumption than old mill closures.

The purified terephthalic and isophthalic acids production process was improved through the exergy analysis approach demonstrated in this work. The overall exergy losses and low-exergy-efficient units were first identified and presented using visualised exergetic flowsheets. Recommendations were then proposed to reduce losses based on the main cause(s) of irreversibility. Three out of the five constituent blocks contained the highest exergy losses. The oxidation block was the main player where it was suggested that using several reactors in series with gradually decreasing temperatures could lower losses. The product refining block had the second-largest irreversibilities, where improving coolers' performances were recommended. The crude terephthalic acid crystallisation block was the third-largest loss producer, where isothermal and isobaric mixing in the solvent dehydrator was suggested to reduce losses. The approach used in this work can be adapted to improve the energy footprint of other chemical processes.

Increasing energy efficiency is a major way of saving energy and thus reducing energy expenses. However, adoption of energy efficiency is generally low, as demonstrated by the energy efficiency gap. To understand that gap, this paper analyses the factors that affect how the energy efficiency attribute is rated in investment in heating, ventilation and air conditioning (HVAC) systems in the hotel industry in Spain. A survey conducted on two hundred owners of hotels, hostels and holiday cottages (referred to jointly here for the sake of convenience as the hotel industry ) shows that the value placed on energy efficiency is influenced not just by climate conditions, environmental concern and type of hotel but also by other attributes of the HVAC system such as brand reliability, price and performance. The hotel industry may also be identifying EE as a proxy for quality rather than savings. Designing the right energy-efficiency policy entails accounting for potential responses by agents, and this analysis helps identify those drivers to which they may or may not respond. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature. This study was undertaken as a part of the CONSumer Energy Efficiency Decision making (CONSEED) project, an EU-funded H2020 research project under grant agreement number 723741. This research is also supported by the Spanish State Research Agency through María de Maeztu Excellence Unit accreditation 2018-2022 (Ref. MDM-2017- 0714) and the Basque Government BERC programme. Financial support from the Government of Spain and the European Regional Development Fund through grants RTI2018-093692-B-I00, RTC2019- 007315-3 and RED2018-102794-T is gratefully acknowledged.

Different streams of low-grade biomass of different origins (road side grass, miscanthus, wheat straw and spruce bark) were upgraded to reasonable quality commodity fuels by significantly reducing the alkali and chlorine content, through washing with water in a first step and torrefaction in a second. The aim was to produce a cleaner fuel with a higher energy content for further densification. The final goal was to demonstrate the improvements attained by the upgrading process during combustion using the lab-scale combustion simulator facility of ECN part of TNO. Analyses of the original, washed and washed/torrefied samples showed that approximately 90% of Cl and up to 60–80% of K can be removed by this upgrading route; during the torrefaction step Cl and S are removed from the solids; during torrefaction K and Na are not significantly altered; the pre-wash step is crucial for the removal of K. Si and Ca remain largely in the solid fraction; post-wash seems to be a viable route to upgrade dry-type of biomasses; “straw” like material requires more time for washing than “grass” type. The combustion results showed that: NOx emissions are generally decreased after upgrading; High temperature chlorine corrosion can be effectively mitigated; Fine particulate matter (submicron/aerosols) formation is strongly reduced, effectively reducing the risk of alkali induced fouling. However, slagging tests revealed that pre-washing and torrefaction has minor impact on the slagging propensity of the fuel. Only, slightly reduced slagging is observable and therefore the use of mineral combustion additives, or smart blending with other fuels in order to further mitigate the slagging risks is strongly recommended.

This paper reports the use of lignin-rich residues from second generation bioethanol production, to produce syngas that can be applied in the gas fermentation process. Three gasification technologies at a different scale were considered in this study. Fixed bed updraft gasification of about 30 kg/h solid feed, bubbling fluidized bed gasification of about 0.3 kg/h solid feed and indirect gasification of about 3 kg/h solid feed. Two lignin-rich residues with different properties were tested and the results were evaluated in terms of feedstock pretreatment (grinding, drying and pelleting) and syngas quality requirements for the fermentation process. The molar H 2 /CO ratio (ranging from 0.6 to 1.0) and the tar yield (18–108 g/Nm 3 ) obtained from the three gasification technologies was quite different. For the syngas fermentation process, low H 2 to CO ratio is preferred, as most of the organisms grow better on CO than H 2 . Furthermore, different contents of impurities that can reduce the fermentability of the gas (such as hydrocarbons, HCN, HCl, NH 3 , COS and other organic S- compounds) were detected in the product gas. The concentration of these compounds in the syngas is related to the content of the corresponding compounds in the original feedstock. The different characteristics of the lignin-rich feedstocks are related to the specific pre-treatment technologies for the (hemi)cellulose extraction. By tuning the pre-treatment technology, the properties of the feedstock can be improved, making it a suitable for gasification. Tar and unsaturated hydrocarbon compounds need to be removed to very low levels prior to the fermentation process. As a next step, the combination of the gasification and the appropriate product gas cleaning, with the syngas fermentation process for the production of bio-alcohols will be evaluated and the overall efficiency of the gasification-fermentation process will be assessed. © 2019

To overcome the inherent complexity of lignocellulosic biomass and improve its biological conversion efficiency, the central composite surface response methodology was used to optimize the process variables (temperature, reaction time and liquid-to-solid ratio) in liquid hot water pretreatment for biomethane production from the anaerobic digestion of Hybrid Pennisetum (a typical energy crop in southern China). Temperature, reaction time and water content were varied between 160–200 °C, 20–60 min and 60–90 mL respectively. The biomethane yields from pretreated material were considered as response variables to different processes conditions. Results showed untreated Hybrid Pennisetum had a biomethane potential of 218.6 L/kg volatile solid (VS) (corresponding to a biodegradability of 62.6%). The effect of liquid hot water pretreatment on the biomethane yield was distinct. Pretreatment severities less than 4.55 resulted in increased biomethane yields. However, further increasing the severity led to lower biomethane yields. The optimum biomethane yield (290.6 L/kg VS) was obtained from pretreated Hybrid Pennisetum at 175 °C for 35 min, with the highest biodegradability of 83.2%. Energy balance showed that, under the optimal pretreatment condition, the highest energy conversion efficiency of 76.1% was attained in theory. If the process energy inputs are included, a process energy efficiency of 51.7% could be realized with proper heat recovery.

In this study, the minimum quality loss of 2-phase olive pomace and the maximum system's energy efficiency is targeted during pre-drying of olive pomace in a drum dryer. Vapor pressure and valse rotational speed were selected as the independent variables of drum dryer. For each vapor pressure value (1, 2, 3, 3.5 and 4 bar), drying of 2-phase olive pomace was performed at different valse rotational speeds (0.5, 1, 2, 3, 4.5 and 6 rpm). Drum dryer conditions were optimized with desirability function approach by targeting the moisture content range as 30-50%, minimum peroxide value and maximum specific moisture extraction rate (SMER). the optimum drum dryer conditions were determined as 3.27 bar for vapor pressure and 6 rpm for valse rotational speed. Moreover, the effects of vapor pressure and valse rotational speed on the physical and chemical properties of pre-dried 2-phase olive pomace and the system's energy efficiency were examined. [GRAPHICS] ., Council of Scientific Research ProjectsEge University [16-MUH-024], The authors acknowledge Ege University, Council of Scientific Research Projects (Project Number: 16-MUH-024) for financial support.

Cold homes and fuel poverty have been identified as factors in health and social inequalities that could be alleviated through energy efficiency interventions. Research on fuel poverty and the health impacts of affordable warmth initiatives have to date primarily been conducted using quantitative and statistical methods, limiting the way how fuel poverty is understood. This study took a longitudinal focus group approach that allowed exploration of lived experiences of fuel poverty before and after an energy efficiency intervention. Focus group discussions were held with residents from three low-income communities before (n = 28) and after (n = 22) they received energy efficiency measures funded through a government-led scheme. The results show that improving the energy efficiency of homes at risk of fuel poverty has a profound impact on wellbeing and quality of life, financial stress, thermal comfort, social interactions and indoor space use. However, the process of receiving the intervention was experienced by some as stressful. There is a need for better community engagement and communication to improve the benefits delivered by fuel poverty programmes, as well as further qualitative exploration to better understand the wider impacts of fuel poverty and policy-led intervention schemes.

Biomass feedstock can be used for the production of biofuels or biobased chemicals to reduce anthropogenic greenhouse gas (GHG) emissions. Earlier studies about the techno-economic performance of biofuel or biobased chemical production varied in biomass feedstock, conversion process, and other techno-economic assumptions. This made a fair comparison between different industrial processing pathways difficult. The aim of this study is to quantify uniformly the factory-gate production costs and the GHG emission intensity of biobased ethanol, ethylene, 1,3-propanediol (PDO), and succinic acid, and to compare them with each other and their respective fossil equivalent products. Brazilian sugarcane and eucalyptus are used as biomass feedstock in this study. A uniform approach is applied to determine the production costs and GHG emission intensity of biobased products, taking into account feedstock supply, biobased product yield, capital investment, energy, labor, maintenance, and processing inputs. Economic performance and net avoided GHG emissions of biobased chemicals depend on various uncertain factors, so this study pays particular attention to uncertainty by means of a Monte Carlo analysis. A sensitivity analysis is also performed. As there is uncertainty associated with the parameters used for biobased product yield, feedstock cost, fixed capital investment, industrial scale, and energy costs, the results are presented in ranges. The 60% confidence interval ranges of the biobased product production costs are 0.64–1.10 US$ kg ?1 ethanol, 1.18–2.05 US$ kg ?1 ethylene, 1.37–2.40 US$ kg ?1 1,3-PDO, and 1.91–2.57 US$ kg ?1 succinic acid. The cost ranges of all biobased products partly or completely overlap with the ranges of the production costs of the fossil equivalent products. The results show that sugarcane-based 1,3-PDO and to a lesser extent succinic acid have the highest potential benefit. The ranges of GHG emission reduction are 1.29–2.16, 3.37–4.12, 2.54–5.91, and 0.47–5.22 CO 2eq kg ?1 biobased product for ethanol, ethylene, 1,3-PDO, and succinic acid respectively. Considering the potential GHG emission reduction and profit per hectare, the pathways using sugarcane score are generally better than eucalyptus feedstock due to the high yield of sugarcane in Brazil. Overall, it was not possible to choose a clear winner, (a) because the best performing biobased product strongly depends on the chosen metric, and (b) because of the large ranges found, especially for PDO and succinic acid, independent of the chosen metric. To quantify the performance better, more data are required regarding the biobased product yield, equipment costs, and energy consumption of biobased industrial pathways, but also about the production costs and GHG emission intensity of fossil-equivalent products. © 2019 The Authors. Biofuels, Bioproducts, and Biorefining published by Society of Chemical Industry and John Wiley & Sons, Ltd. © 2019 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Chemical Industry and John Wiley & Sons, Ltd.

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) In recent times, there has been a rise in interest on the applications of electro-technology based food processing methods. With drying in food industries being an energy intensive process with huge environmental impacts, the objective of this study was to design and develop a purpose-built laboratory system, for experimentally characterising an energy efficient electro-osmosis dewatering system. Electro-osmosis is a unique dewatering technique in which, moisture in food materials are removed by the application of low electric field (5-30 V). Different food materials namely, yogurt, orange pulp and egg whites were tested using electro-osmosis at 15 V and 30 V over 15 min and 30 min, respectively. The energy consumption (kWh), carbon footprint (kgCO2e) and cost indices (£/kg dried food) were also evaluated and compared with thermal drying. Department of Mechanical and Aerospace Engineering, Brunel University London for providing

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) The use of energy efficient technologies for dehydration of food materials without compromising final food product quality is gaining increased interest in the food industry. A promising dehydration-enhancing process step that has been applied in the food industry mainly for pasteurisation operations is Ohmic heating. This study investigated the use of Ohmic and conventional thermal heating for dewatering of two citrus products, orange and grapefruit. A number of analyses including electrical thermal conductivity (ETC), energy consumption, cost, greenhouse gas (GHG) emissions, moisture content, PH and Vitamin C levels were performed. The results revealed that there was a positive increase of the ETC over time in both samples, resulting in higher values of 70 0 C for the orange samples and 100 0 C for the grapefruit samples. The moisture content of the samples was significantly (P

The article analyses and evaluates the possibilities of using oak bark, oak leaves, and their mixtures for biofuel. The preparation of this waste for the burning process (milling, granulation) has been investigated and the results have been presented together with the analysis of the prepared granules&rsquo, properties&mdash, humidity, density, strength, elemental composition, ash content, caloric value, and others. The moisture content of the oak waste granules ranged from 8.1% to 12.5%, and the granules&rsquo, density ranged from 975.8 to 1122.2 kg m&minus, 3 DM (dry matter). The amount of oak ash found was very high (from 10.4% to 14.7%)&mdash, about 10 times higher than that of wood waste granules. The calorific value determined after burning the oak bark and leaves pellets was sufficiently high, ranging from 17.3 to 17.7 MJ kg&minus, 1. This thermal value of oak waste granules was close to the calorific value of the herbaceous plant species and some types of wood waste. The environmental impact of burning the granules of oak waste was also assessed. The harmful emissions of carbon monoxide and dioxide, nitrogen oxides, and unburnt hydrocarbons into the environment were found to be below the permissible limits for the incineration of oak waste granules. The highest CO gas concentration, determined when burning the oak leaves, was 1187.70 mg m&minus, 3, and the lowest NOx concentration, determined when burning the oak bark and leaf mixture granules, was 341.2 mg m&minus, 3. The coefficient of energy efficiency R of the granulated oak leaves biofuel, when the oak waste biomass moisture content was reduced by 10%, reached 3.64. It was very similar to the results of previous studies of various types of granulated straw biofuel (3.5&ndash, 3.7). The research results presented show that, given that the main parameters of oak waste meet the basic requirements of solid biofuel, oak bark, leaves, and their mixture can be recommended to be used as solid biofuels.

Enhanced biofuel production routes utilizing separate lignin and carbohydrate processing of lignocellulose are analyzed and compared with two conventional routes; the methanol and methane production via syngas from biomass. The enhanced processes studied are: hydrocarbons production by hydrogenation of biomass based sugars by hydrogen obtained from lignin gasification, and ethanol production by biomass hydrolysis and fermentation and conversion of residual lignin into methanol via syngas. The analysis of processes was done by rigorous flowsheet modeling including power production calculations and realistic heat integration and evaluation based on energy yield, greenhouse gas (GHG) reduction and net present value (NPV). The enhanced processes via separate lignin and sugar processing can run in two modes: either being energy self-sufficient or utilizing external low temperature heat and power. The processes can operate with high efficiency as ‘waste heat and power to gas and liquids’ processes for p...

In present study, the energetic and exergetic performances of a diesel engine fueled with conventional diesel and various biodiesel fuels were investigated experimentally. Energetic and exergetic performance parameters of the engine fueled with neat diesel, neat opium poppy and neat palm biodiesel fuels were calculated and compared with each other. Moreover, the sustainability analysis was carried out in the study. The findings of this study indicated that the energetic and exergetic performance parameters were profoundly affected by the engine speed and the fuel type. Both the thermal and exergetic efficiencies were the highest at the engine speed of 1600 rpm for all tested fuels. At this engine speed, the lowest thermal efficiency of the engine occurred with palm biodiesel as 34.92%, while the highest thermal efficiency value was 35.85% with diesel fuel. The exergy efficiencies of corresponding fuel types ranged from 32.50% to 33.64% for palm biodiesel and diesel fuels, respectively. In addition, the difference between the exergy efficiencies of diesel fuel and opium poppy biodiesel fuel was about 0.90%. Both the energy and exergy efficiencies diminished with the increment of engine speed higher than 1600 rpm for all fuel types. The maximum values of sustainability index for all fuel types were obtained at the engine speed of 1600 rpm. The best exergetically-sustainable fuel was the diesel fuel followed by the opium poppy biodiesel fuel. According to the results, opium poppy biodiesel might replace with the conventional diesel fuel due to the similarity of energetic and exergetic performance parameters.

Industry is a large energy user in nearly all countries. Approximately half of all industrial energy use is used in specific processes in the energy-intensive industries. On the other hand, various general energy conversion technologies and end uses can also be distinguished (e.g., steam production, motive power, lighting). Opportunities and potentials exist for energy savings through energy efficiency improvement in all sectors and countries. Technology development, as well as policies aimed at dissemination and implementation of these technologies, can help to realize the potential benefits. Technologies do not now, nor will they in the foreseeable future, provide a limitation on continuing energy efficiency improvements.

Bagasse is an abundant by-product from sugarcane production that can be used for conversion into biofuels. Nonetheless, the recalcitrant structures of lignocellulosic fibers required a pretreatment prior conversion into biofuels. In this study, four mechanical deconstruction methods were compared in terms of energy demand and energy efficiency at lab scale: BM (ball mill), VBM (vibratory ball mill), CM (centrifugal mill) and JM (jet mill). Results indicate that VBM was more effective compared to BM, JM and CM in enzymatic accessibility and sugars solubilization: VBM-3h > BM-72 h > JM-5000 rpm > CM-0.12 mm. However, preliminary energetic assessment showed that at lab scale, the CM (centrifugal mill) as mechanical fractionation process appears to be the most efficient in terms of energy-efficiency (kg glucose/kWh) compared to BM, VBM and JM. A comparison with literature pretreatments data highlighted that fine and/or ultrafine milling process (BM, VBM, CM) are simpler saccharification technologies, which not required any chemical or water inputs, thus minimizing waste generation and treatment.

The use of lignocellulosic biomass is promising for biofuels and materials and new technologies for the conversion need to be developed. However, the inherent properties of native lignocellulosic materials make them resistant to enzymatic and chemical degradation. Lignocellulosic biomass requires being pretreated to change the physical and chemical properties of lignocellulosic matrix in order to increase cell wall polymers accessibility and bioavailability. Mechanical size reduction may be chemical free intensive operation thanks to decreasing particles size and cellulose crystallinity, and increasing accessible surface area. Changes in these parameters improve the digestibility and the bioconversion of lignocellulosic biomass. However, mechanical size reduction requires cost-effective approaches from an energy input point of view. Therefore, the energy consumption in relation to physicochemical properties of lignocellulosic biomass was discussed. Even more, chemical treatments combined with physicochemical size reduction approaches are proposed to reduce energy consumption in this review. (C) 2013 Elsevier Ltd. All rights reserved.

This paper presents a building construction approach that is based on forty years of experience and a focus on multi-disciplinary synergies. After 1980, the migration science-based design was accelerated by the “Integrated Design Process (IDP)”. As a result, building science became a significant force in reducing the effects of climate change. The component associated with heating, cooling, and ventilation that is labeled “Environmental Quality Management” (EQM) or EQM-retro for interior applications will be discussed. The critical aspects of EQM-retro are: (1) A two-stage process for new and retro construction that modifies financing patterns. In stage one, the object is to develop the best possible performance within an investment limit. In stage two, the cost is minimized; (2) Building Automatic Control Systems (BACS) are important for control thermal mass contributions of while achieving adaptable indoor climate as well as an integration of the HVAC system with the building structure; (3) This is achieved with use of a monitoring application and performance evaluation (MAPE); (4) Introduction of BACS and MAPE during design process improves the integration of building subsystems and energy optimization. Examples showing increaseased occupant-controlled comfort, energy efficiency and flexibility of energy demand are presented in the paper.

Half-bridge GaN power converters are susceptible to false turn-on events, which can lead to shoot-through and potentially device-damaging currents. There are three main parameters that can be adjusted in PWM schemes to reduce the likelihood of false turn-on events: negative gate bias, gate resistance, and deadtime. However, these PWM parameters also affect converter efficiency in the inverse way, meaning less false turn-on events must be balanced with lowered efficiency. The novelty of this paper is to investigate the trade-off between reducing GaN false turn-on events (by reducing the transient peak of gate to source voltage) and maximizing the power converter efficiency, which has not been done in prior work. This paper investigates this trade-off using a synchronous buck converter over numerous operating points with variation of the three key PWM parameters. Six converter scenarios are considered with input voltage of 200/400V, switching frequency of 50/100kHz, and output power of 500W/1kW. For each scenario, negative gate bias is set to ™4.4V and −5V, gate on-resistance is set to $10\Omega $ and $12.5\Omega $ , and deadtime is varied at 60ns, 80ns, and 110ns. The results are organized into Pareto plots to find optimal points for efficiency and reduction of false turn-on events. The experimental results show that a further negative gate bias (−5V) most significantly reduces the false turn-on voltage peak and still achieves very high efficiency with appropriate selection of gate resistance and deadtime.

There are continuous research and practical interest to combine different renewable sources within one Smart Grid network. The paper aims to estimate the influence of key economic and social drivers of renewable energy and Smart Grid promotion in OECD member countries. The random effect of the generalized least squares method was used to estimate the empirical model based on the World Bank, OECD, Heritage Foundation, and World Energy Council datasets for a panel of 36 OECD counties. For the empirical estimation, the dependent variables considered are energy renewable electricity output and energy trilemma index, taken as two proxies for Smart Grid development. The results suggest that an increase in GDP p. c. in national economies by 10,000 USD leads on average to a 3.9% decrease in renewable electricity output during 2001–2015. The richer the society, the less renewable energy sources were used for power generation in a group of OECD countries. The last is also supported by the fact that gross fixed capital formation treated as a percentage value of GDP is negatively correlated with structural changes in renewable energy output. The empirical conclusion is that during the study period, OECD countries were mainly oriented to economic growth, which was achieved by consuming non-renewable energy resources, and limited attention was paid to sustainability and Millennium Development Goals. The paper provides policy recommendations for Smart Grid development and points in the future research within OECD countries. AcknowledgmentsComments from the Editor and anonymous referees have been gratefully acknowledged. Leonid Melnyk gratefully acknowledges financial support from the Ministry of Education and Science of Ukraine (0118U003578). Oleksandra Kubatko gratefully acknowledges financial support from the Ministry of Education and Science of Ukraine (0119U100766) and National Research Foundation of Ukraine (2020.01/0135).

The current industrial context favors the generation of large amounts of data, most of which still seems to remain unexplored by the majority of enterprises. This paper presents a literature review on methodologies reported in the scientific literature exploring the potential value of industrial data via the utilization of Machine Learning tools for energy efficiency related goals. This work identifies and examines in detail the scientific contributions published up to date. A total of 42 published papers are found to present original contributions in this field, and addressing multiple energy efficiency challenges. A descriptive analysis is presented and demonstrates that the number of published works in this field is rapidly growing. The majority of contributions address challenges in petrochemical industries, and namely in ethylene production. There is still a very limited number of published papers addressing the application of Machine Learning tools on energy related objectives in other types of industries. The technical content of all identified papers is thoroughly reviewed and their key features and objectives are highlighted. A number of important themes across the final list of papers emerges, addressing challenges such as energy consumption forecast, energy analysis and energy optimization. A framework identifying the key goals reported on the set of 42 papers and the tools proposed to address them is suggested. This framework provides a summary on existing tools and facilitates the identification of research needs in this field. Additionally, the proposed framework serves as a reference guideline for the manufacturing and process industries on the selection of adequate Machine Learning tools for energy efficiency objectives via the utilization of industrial data.

In the study presented in this paper, the deterioration in the performance of an industrial gas turbine during the operation design point was simulated by using the thermodynamic principle and a multi feedforward artificial neural networks (MFANN) system. Initially the thermodynamic model was constructed using the components performance map technique, that entailed calculating the operating point which was compliant with the performance map for each component. The various design operation points were generated by changing the engine component’s efficiency or outer environmental conditions and simulating the engine’s performance for each case. The MFANN model was constructed by using these operation points for the training and testing stage. In this way, the two MFANN models were established. The aim of the first model was to calculate the engine’s performance while the second model was used to detect the deterioration of the components of the engine This paper presents a robust fault diagnosis system for gas turbine degradation detection with the aim of improving energy efficiency.

The paper represents an analysis of the public policies implemented in the First District of Bucharest related to the energy efficiency. Energy represents a strategic factor for the socio-economic development of Romania and finding the best solutions for increasing energy efficiency will contribute to the objectives for durability and competitiveness in the European Union. The importance of the theme is given by the requirement of the European Union through Energy Efficiency Directive that require member states to set up plans at every three years and evaluate the progress towards energy efficiency annually. Also, for the next period, 2021-2030, all member states must elaborate the 10-year integrated national energy and climate plan (NECP), presenting the solutions in order to meet the different targets for 2030, including energy efficiency. The objective of the article is to find the best solutions for increasing the energy efficiency, having as case study the 1-st District of Bucharest. The author is presenting three solutions, as follows: multistorey thermal rehabilitation, domestic elevators modernization, individual houses thermal rehabilitation. The impact of the solutions presented in the paper are the following: decrease of energy consumption, decrease of CO2 emissions, safety increase.

In this study, energy efficiency applications and corresponding energy saving results were evaluated in a Turkish fabric dyeing factory. The relationship between energy consumption and the production were evaluated by regression analysis. They were detailed with energy intensity index (EII), cumulative sum values (CUSUM), specific energy consumption (SEC), and radar chart. The energy efficiency efforts should be initiated from heat and electrical energy, which are the main energy types extensively used in the textile industry. Average energy consumption value of the last four years (2015-2018), which is 7134 TOE is reduced 49% including waste heat, flash steam and cooling water recovery, and insulation in dyeing machines, in the factory due to the implementation of the energy saving actions. Accordingly, a reduction of 25% SEC value is possible. Moreover, production planning has a significant impact on the total energy consumption in terms of full load capacity operation of the dyeing machines, which may cause 23% energy saving that is of great importance. Turkish Energy and Natural Resources Ministry (ETKB) This paper is based on the Master of Science thesis of Behcet Guven entitled Application example of energy efficiency in textile industry finishing sector. Additionally, some data obtained by the Energy Efficiency Improvement in Industry project, which is supported by the Turkish Energy and Natural Resources Ministry (ETKB) were evaluated. We are thankful to Ozen Textiles, Dyeing and Finishing Enterprises Inc. for the cooperation. The early outputs of this study were published in the IEEE Xplore Digital Library with a paper entitled Energy efficiency implementation in a fabric finishing factory in Turkey.

Kindergartens are probably the very first public buildings we actively use in our lives. Therefore, they can be considered as the physical structures that are providing for the very important educational and social function. Additionally, they can also be considered as the specific learning tool for future generations where they can encounter the ideas of green and energy-efficient buildings. One of the results of the research project ?Energy efficiency in public buildings? has been formulated through the development of Serbian National Typology of Kindergartens which was conceived as a specific tool that can be used for improving this portion of building stock. The paper presents the methodology for identification of typical kindergarten buildings, covering various construction periods, building sizes and illustrates the type of analysis performed for model representatives. The potential for energy upgrades covering physical structure, installed technological systems, as well as expected impact on energy performance, has been estimated. The study presents results based on the analysis of the data derived from the National Typology, stressing out that energy retrofits of large and medium-sized kindergartens built during the 1970s and 1980s should be the primary focus of refurbishment activities. Accounting for almost 60% of total buildings and 69.59% of heated area, they are responsible for 75.97% of energy demands. Estimated energy savings of more than 60% indicate the effectiveness of their retrofit. The paper also presents the potential uses of National Typology as a retrofit tool on various scales, from single-building considerations to a strategic approach at the national level.

Європейська політика енергоефективності має ключову роль при формуванні нової моделі енергетичного ринку та вуглецево-нейтральної економіки в Україні. У цій статті виконано огляд актуальних дискурсивних питань на шляху до реалізації європейської політики енергетичної ефективності та зелених інновацій, наведені pro et contra таких реформ. Результативність національних політик може обмежуватися ринковими інструментами, рівнем забезпеченості розумними технологіями та сприйняттям інновацій у секторах енергетики, інституційного розвитку загалом. Тому основною метою дослідження було пояснення політики сталого розвитку та стимулювання зелених інновацій в Україні через економіко-математичне моделювання факторів енергоефективності за 2000-2019 роки. Для інтегрального оцінювання ефективності енергетичної політики в Україні авторами роботи була обрана OLS модель, що містить дев’ять субіндикаторів з чотирьох цілей сталого розвитку в ЄС (а саме: "Доступна та чиста енергія", "Гідна праця та економічне зростання", "Відповідальне споживання та виробництво" та "Боротьба зі зміною клімату"), а також – показник інноваційних витрат промислових підприємств в енергетичній сфері в Україні. Методичним інструментарієм для проведення дослідження стало використання пакету statsmodels в Python 3.6.11, з допомогою якого були виконані розрахунки та перевірка гіпотез моделі. При використанні стратегії розрахунків від загальної до конкретної моделі, була знайдена значима функція за сім раундів оптимізації. Відповідно до результатів OLS моделювання, на показник ефективності енергетичної політики в Україні мають вплив такі змінні, як: "залежність від імпорту енергії за продуктами", "реальний ВВП на душу населення", та "кінцеве споживання енергії". Оцінка останньої змінної має значно менший ефект на результати регресії, та показує негативний зв'язок з показником енергоефективності. Результати моделей були перевірені за допомогою RESET та тестів Jarque-Bera, та показали коректність запропонованої моделі. The European energy policy is a core role in the developing of the new model of the energy market and carbon-free economy in Ukraine. In the paper, the authors analysed the key issues on the way to implement the European policy on increasing of energy efficiency and green innovations which emphasized in pro et contra. The performance of national energy policy could be limited by the market instruments, the efficiency of the smart grid and perception of innovations in the energy sectors, institutional development in general. Thus, the paper aimed to indicate the impact of green innovations on sustainable development and the country’s energy efficiency for 2000-2019. The authors used economic and mathematical modelling. The Ordinary Least Square Model was used for the integral assessment of energy efficiency policy. The authors analysed nine sub-indicators from four Sustainable development goals (Affordable and Clean Energy, Decent Work and Economic Growth, Responsible Consumption and Production, Combating Climate Change) and the indicator which characterized the innovation costs of industrial enterprises in the energy sector in Ukraine. The methodological instrument for checking the hypothesis and empirical justification was software stats models Python 3.6.11. Due to the seven rounds of optimisation, the authors developed significant functioning. Considering to the finding of Ordinary Least Square Modelling, the authors highlighted the determinants which influenced on the efficiency of energy policy: dependence on energy imports by-products, real GDP per capita, and final energy consumption. At the same time, the final energy consumption had less effect on the efficiency of energy policy and demonstrated the negative relationships with energy efficiency. The results of the models were verified using RESET and Jarque-Bera tests and confirmed the correctness of the proposed model.

The goal of this paper is to analyse the collected data on energy efficiency of electric vehicles from researches done by other authors and also to summarise all the factors affecting it. The majority of data available are obtained through simulations – therefore the emphasis in this paper will be placed on experimentally acquired data. The results of the analysis will be used for the planned e-bus eco-driving project for the purpose of Belgrade’s public transportation system. Currently there are only 5 (ultracapacitor type) e-buses operating in Belgrade city public transport, which makes only 0.2 % of all vehicles in rolling stock (making 16 % together with other electric-powered vehicles – trams and trolleybuses), but there are plans to acquire new 80 electric buses. With the rise of the number of electric vehicles, appropriate training of drivers is gaining more and more importance, and the results of the presented analysis make the basis for such training. This will hopefully increase the range of the buses used and help save the energy spent by public transportation, thus giving a little contribution to global fight for cleaner planet.

PurposeRefurbishing houses is considered a key measure to improve the energy efficiency of the built environment. However, little is known about the implementation and outcome of housing renovation for energy upgrades in the Vietnamese practice. The purpose of this paper is to investigate the energy performance of the current housing stock in Vietnam and the potential to reduce energy use in households.Design/methodology/approachThe paper is based on a survey with 153 respondents in three major climatic regions of Vietnam. The survey focusses on building characteristics, environmental performance, energy performance and refurbishment activities. Data collected from the survey were statistically analysed to give insight into the current performance of the housing stock and its energy saving potential.FindingsThis paper concludes that building design and construction, particularly the building envelope, have a significant influence on the occupants’ comfort. However, the energy consumption in houses is not statistically associated with building design and indoor environment. It is suggested that financial status and occupants’ behaviour currently have a strong influence on the household energy use. The survey also showed that refurbishment improves the housing performance, especially if improving the indoor environment was one of the drivers.Originality/valueThere are very few studies on energy use in households in Vietnam, especially with regards to actual energy consumption. This paper brings insights into the actual energy consumption and reveals the “performance gap” in Vietnamese housing stock.

In this paper, we use an evolutionary swarm intelligence approach to build an automatic electric dispatch controller for an offshore wind power plant (WPP). The optimal power flow (OPF) problem for this WPP is solved by the Canonical Differential Evolutionary Particle Swarm Optimization algorithm (C-DEEPSO). In this paper, C-DEEPSO works as a control system for reactive sources in energy production. The control operation takes place in a daily energy dispatch, scheduled into 15 min intervals and resulting in 96 operating test scenarios. As the nature of the optimization problem is dynamic, a fine-tuning of the initialization parameters of the optimization algorithm is performed at each dispatch interval. Therefore, a version of the C-DEEPSO algorithm has been built to automatically learn the best set of initialization parameters for each scenario. For this, we have coupled C-DEEPSO with the irace tool (an extension of the iterated F-race (I/F-Race)) by using inferential statistic techniques. The experiments carried out showed that the methodology employed here is robust and able to tackle this OPF-like modeling. Moreover, the methodology works as an automatic control system for a dynamic schedule operation., European Commission, Agencia Estatal de Investigación, Comunidad de Madrid

Countries are making important efforts decarbonising their electricity generation mix. In this context, improving the operational efficiency enables better use to be made by renewables and the grids. However, the location of new capacity might be relevant from the social welfare point of view when private decisions might affect the power system efficiency. In this paper, we analyze the Spanish transmission grid with the aim to explore in the power system efficiencies with a high share of renewables in the generation mix. We explore in the location of the generation technologies to see how efficient they are located with regard to the consumption. We find wind is one of the least efficiently located, which has implied relevant grid investments paid by consumers. Moreover, a high concentration of renewables increases grid-congestions, which might constrain locations for future capacity. Our results highlight there is a trade-off between incomes from RES and grid costs paid by consumers. Therefore, we suggest RES policies should include some locational incentives. We analyze pros and cons from some choices and conclude countries should provide further grid information to incumbents and also include locational incentives in future RES auctions. Indeed, results from this paper represent a first stage in the design of these locational incentives. We acknowledge financial support from the Chair of Energy Sustainability (IEB, University of Barcelona), FUNSEAM and from the projects RTI2018-100710-B-I00 (MCIU/AEI/FEDER, UE) and 2017-SGR-739 (Government of Catalonia).

China’s recent development has been nothing short of remarkable, but energy-saving, and environmental protection is still a serious problem. The improvement of energy efficiency (EE) is an important factor for China to better follow the path of energy conservation, sustainable development, and environmental protection. Meanwhile, market segmentation is a unique phenomenon in the process of China’s economic development. Hence, studying market segmentation on energy efficiency has positive significance for improving energy efficiency. The major objective of this study is to investigate the relationship between EE and market segmentation. This paper measures market segmentation by the Price-Based Approach, calculating EE by super slack-based measure (super-SBM), and integrated spatial Durbin model and geographically weighted regression model. Based on the panel data of 30 provinces in China from 1995 to 2018, this paper finds that: (1) Regional market segmentation has a significant negative effect on EE. Moreover, in terms of spatial effect, market segmentation has a positive spatial spillover on EE estimated by 0-1 matrix suggesting that market segmentation in the surrounding area has a positive impact on local EE. (2) The negative effect of Market segmentation on EE demonstrates the obvious regional difference: Eastern region &gt, central region &gt, western region. In addition, geographically weighted regression results show that the impact of market segmentation on EE shows that in regional spatial distribution, Shanghai, Jiangsu, Zhejiang, and Anhui have the strongest negative effect, second in Fujian, Jiangxi, Shandong, Henan, Hubei, Beijing, Tianjin, and Hebei. (3) This paper confirms that market segmentation can affect EE through local protectionism, technological difference, and scale effect. Finally, through the above research basis, put forward the corresponding policy suggestions.

In this paper, a finite-element-based model is being introduced and developed, using the Cast3m (CEA, Paris, France) simulation tool, to evaluate the thermo-mechanical behavior of a small-scale test bed. In fact, many studies on thermal behavior of cavities have been carried out in literature. However, none of them took into account the co-existence of all thermal phenomena (conduction, convection, internal/external radiation). The work presented in this paper presents a thermo-mechanical model, which aims to combine, in a holistic way, these phenomena. An experimental validation of the thermal model has been first carried out using an infrared camera and DS18B20 (Maxim Integrated Products, Dallas, TX, USA) numerical sensors. Results are reported and show the accuracy of the proposed model since both numerical and experimental values of heat transmittance fit together. The main objective is to evaluate heat losses through the walls, by means of heat transmittance calculation, and proposing new functional materials that will help in energy harvesting, as a perspective of this work. As for the mechanical study, it was meant to investigate the distribution of the mechanical stress towards the building envelope submitted to its own weight. Results showed that the stress is uniformly distributed on the lateral walls of the structure as well as on the floor.

This comparison study of the implementation of energy-saving projects in buildings was conducted in order to consider the diversity of experiences between Western European countries, which have experience and expertise in this area, and those countries in Eastern Europe that are in the beginning stages. The goal of this paper is to analyze obstacles and incentives for investment in energy conservation in buildings by comparing European countries with a diverse landscape of institutional and economic developments, social-cultural values, and environmental framework conditions in order to understand if these differences are influencing the implementation of energy saving measures and how this can be used to overcome the existing obstacles. The study is based on survey results received from experts in Eastern and Western European countries. The main value of the research is that it offers an overview of the potentials and constraints (barriers) to energy efficiency in Europe, based on data from a sample of western and eastern European countries. Among the most important incentives that were implemented to stimulate energy-saving measures are costs savings and the need to meet regulatory requirements. The main obstacles that still restrict the number of already implemented projects in Europe are a lack of proper financial incentives and that many Eastern countries are still struggling to develop the market of Energy Saving Services (ESS) and to operate better energy waste control systems. The paper concludes with the successful incentives that were implemented to stimulate the energy-saving measures and the main obstacles that still restrict the number of already implemented projects in Europe. Additionally, a set of indicators related to the environmental friendliness and social significance of energy-saving measures was proposed for evaluation of the project results. These were used based on the fact that they may be measured and cater for comparisons. This paper can help improve policy-makers’ selections in order to improve economic instruments appropriate to energy-saving policy objectives and specific national contexts.

In recent years, there has been a significant development in “green” and energy efficient propulsion systems, which fits into the general trend of environmentally friendly “green shipping”. The pursued goal is to construct a safe passenger ship that is low in energy demand and equipped with a highly energy efficient, emission-free propulsion system. The paper presents main problems encountered by designers of a small, hybrid-powered ferry powered lithium batteries. The conducted research allowed to create a design of an energy efficient hull shape, which decreases the demand for energy. Completed remote control model tests resulted in a proposal of an energy efficient and safe propulsion system with good manoeuvring capabilities. Measurements completed on an existing ferry permitted completing energy balance and forming an energy management policy. The paper contains the emission calculations computed for the existing ferry that are necessary for the environmental impact analysis. The soon to be constructed, newly designed vessel will provide a valuable contribution to hybrid-propulsion, energy management and unmanned technologies research.

African countries are in a unique position to reap thesocio-economic and environmental benefitsofrenewable resourcesas a means for meeting increasing energy demand in a sustainable way. A critical obstacle for the deployment ofrenewable energy technologiesin Africa is the difficulty of attracting sufficient and affordable finance. This paper compares the impact of financial conditions on the cost of electricity generation across six renewable and three fossil-based technologies in 46 African countries. The results show large cost variations and highlight the extent to which renewables are disadvantaged by current financial practices. The energy-economy-environment model TIAM-ECN is used to show how lowering financing costs results in a much higher deployment of renewables. For example, solar PV could account for 10–15% of total electricity generation by 2050, even without explicit climate policy, thanks to financial de-risking programmes. The results demonstrate that changes in financing schemes could outweigh the impact of technology learning. This paper also demonstrates that, once ambitious climate policies are in place, reducing financing costs for renewables could be an efficient way to lowergreenhouse gas emissions. Financial de-risking is thus a key ingredient for unlocking the renewable energy potential in Africa.

In response to the increased energy consumption in residential buildings, various efforts have been devoted to increase occupant awareness using energy feedback systems. However, it was shown that the feedback provided by these systems is not enough to inform occupant actions to reduce energy consumption. Another approach is to control energy consumption using automated energy management systems. The automatic control of appliances takes out the occupant sense of control, which is proved to be uncomfortable in many cases. This paper proposes an energy messaging intervention that keeps the control for occupants while supporting them with actionable messages. The messages inform occupants about energy waste incidents happening in their house in real time, which enables occupants to take actions to reduce their consumption. Besides, a heuristic is defined to make the intervention non-intrusive by controlling the rate and time of the messages sent to occupants. The proposed intervention is evaluated in a novel layered agent-based model. The first layer of the model generates the detailed energy consumption and realistic occupant activities. The second layer is designed to simulate the peer pressure effect on the energy consumption behavior of the individuals. The third layer is a customizable layer that simulates energy interventions. The implemented intervention in this paper is the proposed non-intrusive messaging intervention. A number of scenarios are presented in the experiments to show how the model can be used to evaluate the proposed intervention and achieve energy efficiency targets.

In this paper, we focus on an essential energy management approach for enhancing energy efficiency (EE) as well as reducing fuel consumption of off-grid cellular networks whose base stations (BSs) are supplied with hybrid power sources including solar PV array and diesel generator (DG). To take the full advantage of PV technology, this paper examines the reliability performance and carbon footprint implications in addition to EE. This paper also investigates the benefits of unevenly harvested green energy sharing mechanism under zero fuel consumption scheme via physically installed resistive power lines taking into account of dynamic nature of renewable energy (RE) generation and traffic arrival density. Furthermore, joint transmission coordinated multipoint (JT-CoMP) user association technique is integrated for achieving higher throughput and EE performance providing the best SINR quality to a connected user equipment (UE). A comprehensive Monte-Carlo based simulation study has been carried out for evaluating EE, EE index (EEI), and energy saving performances in downlink LTE-advanced networks under a wide range of network settings. The results reveal that the proposed system can attain up to 26% energy savings via cooperation mechanism and 48.7% more energy efficient in terms of EEI under peak load over the conventional hybrid paradigm.

Energy efficiency of hydrostatic transmissions, and especially efficiencies of drives with motor speed controlled by throttle, as well as efficiency of hydraulic servomechanisms can in fact be higher than the efficiency values most frequently given by the respective literature in this field. With the progress achieved in recent years in the development of hydraulic systems it is becoming necessary to develop methods for precise energy efficiency calculation of such systems. It is difficult to imagine that more and more, better and better machines and control elements could be used without the possibility of a mathematical tool at our disposal to enable an accurate analysis and assessment of behavior of the system in which such machines and control elements have been applied. The paper discusses energy savings using mathematical model of losses in elements, the energy efficiency of the system. There are possibilities to reduce energy losses in proportional control systems (in the pump, in the throttle control unit, especially in the cylinder), and thus to improve the energy efficiency of the throttling manifold. The considerations allow for comparison of the loss power resulting from the applied hydraulic control structure of the hydraulic cylinder and the power consumed by the pump from the electric motor that drives it, the power necessary to provide pump-driven hydraulic cylinder. The article shows the impact on the output (useful) power consumed in the considered systems, and the impact on the power consumed of the loss power in the individual elements. The paper presents also formulas of loss power, formulas of energy efficiency connected with investigated hydrostatic drives, two schematic diagrams of hydraulic systems, their principle of operation and problems of studying losses in elements and energy efficiency characteristics of systems consisting of a feed assembly, control set and cylinder. It also includes a subject matter connected with an energy loss power of hydrostatic systems with hydraulic cylinder controlled by proportional directional control valve. Diagrams of loss power of two hydraulic systems worked at the same parameters of speed and load of a cylinder, which were different due to structure and ability of energy saving, were presented and compared.

This paper presents a novel incentive-based load shedding management scheme within a microgrid environment equipped with the required IoT infrastructure. The proposed mechanism works on the principles of reverse combinatorial auction. We consider a region of multiple consumers who are willing to curtail their load in the peak hours in order to gain some incentives later. Using the properties of combinatorial auctions, the participants can bid in packages or combinations in order to maximize their and overall social welfare of the system. The winner determination problem of the proposed combinatorial auction, determined using particle swarm optimization algorithm and hybrid genetic algorithm, is also presented in this paper. The performance evaluation and stability test of the proposed scheme are simulated using MATLAB and presented in this paper. The results indicate that combinatorial auctions are an excellent choice for load shedding management where a maximum of 50 users participate.

Historic, listed, or unlisted, buildings account for 30% of the European building stock. Since they are complex systems of cultural, architectural, and identity value, they need particular attention to ensure that they are preserved, used, and managed over time in a sustainable way. This implies a demand for retrofit solutions able to improve indoor thermal conditions while reducing the use of energy sources and preserving the heritage significance. Often, however, the choice and implementation of retrofit solutions in historic buildings is limited by socio-technical barriers (regulations, lack of knowledge on the hygrothermal behaviour of built heritage, economic viability, etc.). This paper presents the approach devised in the IEA-SHC Task 59 project (Renovating Historic Buildings Towards Zero Energy) to support decision makers in selecting retrofit solutions, in accordance with the provision of the EN 16883:2017 standard. In particular, the method followed by the project partners to gather and assess compatible solutions for historic buildings retrofitting is presented. It focuses on best practices for walls, windows, HVAC systems, and solar technologies. This work demonstrates that well-balanced retrofit solutions can exist and can be evaluated case-by-case through detailedassessment criteria. As a main result, the paper encourages decision makers to opt for tailored energy retrofit to solve the conflict between conservation and energy performance requirements. Historic, listed, or unlisted, buildings account for 30% of the European building stock. Since they are complex systems of cultural, architectural, and identity value, they need particular attention to ensure that they are preserved, used, and managed over time in a sustainable way. This implies a demand for retrofit solutions able to improve indoor thermal conditions while reducing the use of energy sources and preserving the heritage significance. Often, however, the choice and implementation of retrofit solutions in historic buildings is limited by socio-technical barriers (regulations, lack of knowledge on the hygrothermal behaviour of built heritage, economic viability, etc.). This paper presents the approach devised in the IEA-SHC Task 59 project (Renovating Historic Buildings Towards Zero Energy) to support decision makers in selecting retrofit solutions, in accordance with the provision of the EN 16883:2017 standard. In particular, the method followed by the project partners to gather and assess compatible solutions for historic buildings retrofitting is presented. It focuses on best practices for walls, windows, HVAC systems, and solar technologies. This work demonstrates that well-balanced retrofit solutions can exist and can be evaluated case-by-case through detailed assessment criteria. As a main result, the paper encourages decision makers to opt for tailored energy retrofit to solve the conflict between conservation and energy performance requirements.

Hygrothermal assessment is essential to the production of healthy and energy efficient buildings. This has given rise to the demand for the development of a hygrothermal laboratory, as input data to hygrothermal modeling tools can only be sourced and validated through appropriate empirical measurements in a laboratory. These data are then used to quantify a building’s dynamic characteristic moisture transport vis-a-vis a much more comprehensive energy performance analysis through simulation. This paper discusses the methods used to establish Australia’s first hygrothermal laboratory for testing the water vapor resistivity properties of construction materials. The approach included establishing a climatically controlled hygrothermal test room with an automatic integrated system which controls heating, cooling, humidifying, and de-humidifying as required. The data acquisition for this hygrothermal test room operates with the installation of environmental sensors connected to specific and responsive programming codes. The room was successfully controlled to deliver a relative humidity of 50% with ±1%RH deviation and at 23 °C temperature with ±1 °C fluctuation during the testing of the water vapor diffusion properties of a pliable membrane common in Australian residential construction. To validate the potential of this testing facility, an independent measurement was also conducted at the Fraunhofer Institute of Building Physics laboratory (IBP) Holzkirchen, Germany for the diffusion properties of the same pliable membrane. The inter-laboratory testing results were subjected to statistical analysis of variance, this indicates that there is no significant difference between the result obtained in both laboratories. In conclusion, this paper demonstrates that a low-cost hygrothermally controlled test room can successfully replace the more expensive climatic chamber.

The Heat Loss Coefficient (HLC) characterizes the envelope efficiency of a building under in-use conditions, and it represents one of the main causes of the performance gap between the building design and its real operation. Accurate estimations of the HLC contribute to optimizing the energy consumption of a building. In this context, the application of black-box models in building energy analysis has been consolidated in recent years. The aim of this paper is to estimate the HLC of an existing building through the prediction of building thermal demands using a methodology based on Machine Learning (ML) models. Specifically, three different ML methods are applied to a public library in the northwest of Spain and compared, eXtreme Gradient Boosting (XGBoost), Support Vector Regression (SVR) and Multi-Layer Perceptron (MLP) neural network. Furthermore, the accuracy of the results is measured, on the one hand, using both CV(RMSE) and Normalized Mean Biased Error (NMBE), as advised by AHSRAE, for thermal demand predictions and, on the other, an absolute error for HLC estimations. The main novelty of this paper lies in the estimation of the HLC of a building considering thermal demand predictions reducing the requirement for monitoring. The results show that the most accurate model is capable of estimating the HLC of the building with an absolute error between 4 and 6%.

The mining industry is facing sustainable development challenges, among which the energy efficiency issues seem to be of major importance. As transport of the mined ore is considered as one of the most energy intensive operations, the improvement of its energy efficiency is a key indicator in terms of sustainable actions taken by mining companies. In open-pit mines, the material handling operations are mostly performed with trucks. Their electrified version&mdash, truck trolley systems&mdash, surpass diesel trucks&rsquo, efficiency while comparing the increased production capacity and the reduction of maintenance cost and fuel consumption. The paper analyzes the opportunities and benefits of the replacement of an ore transport system based on hauling trucks with a regenerative belt conveying in an open-pit mine. Presented case study has been analyzed from energy consumption and environmental impact reduction perspectives. Generally, conception of a regenerative conveyor is based on recuperation of energy or continuous braking needed while a conveyor is running downhill. Energy generated during the braking process (converted from the potential gravitational energy of the conveyed material) is fed back to the electrical grid. Then the regenerative conveyor can be considered as a machine that mines energy as an additional by-product of an exploited deposit. It was shown that difference in transportation cost between haul trucks and energy efficient regenerative conveyors is around 95%. The paper points the conditioning elements to allow the implementation of a regenerative belt conveyor system.

The growing risk of climate change caused by the emission of greenhouse gases poses new challenges to contemporary countries. The development of economies is usually related to increasing levels of greenhouse gas emissions. Therefore, the question arises whether it is possible to achieve sustainable economic and financial development and simultaneously reduce greenhouse gas emissions. This paper assumes it is possible if energy efficiency is increased. The aim of the paper is to show the link between energy efficiency and sustainable economic and financial development in Organisation for Economic Co-operation and Development (OECD) countries for the period 2000–2018 by using data envelopment analysis (DEA) and regression analysis. The results show a slight upward trend of total factor energy efficiency (TFEE) in OECD countries for the analysed period; however, there is a difference in TFEE levels. Developed OECD countries have higher TFEE levels than developing OECD countries. The links between total factor energy efficiency and sustainable economic and financial development reveal different impacts depending on the variables taken into consideration.

open access article Amidst the challenge of improving energy efficiency in the built environment, increasing attention is being put on how to engage and empower building users. Research shows that improving and widening user engagement, such as involving users in co-designing interventions, has potential to foster greater acceptance and impact. In this context, Information and Communication Technology (ICT) has a major role to play, through feedback tools, smartphone or web-based apps, interactive dashboards and gamification. However, there are few empirical accounts exploring how user engagement can effectively shape development of an ICT-based energy efficiency intervention. This paper presents findings from the eTEACHER project which aims to empower building energy end-users to reduce energy consumption through a set of related ICT-based interventions. These interventions, including a web-based app and building-specific ‘what-if’ analysis have been developed by drawing upon feedback from pilot users in 12 buildings, including both residential and non-domestic, across three EU countries. A structured evidence-based approach to user engagement was followed, which included site visits, a series of building user workshops and a questionnaire. The paper reflects on the challenges and benefits of empowering and engaging building users across a wide range of building types, residential, offices, schools and health care centres using a single app. Our findings show common challenges across building types in tackling existing inefficient energy behaviours. However significant hurdles were encountered in implementing the ICT-based interventions, which are building specific. Based upon this, recommendations on how engagement processes can support the development of ICT-based interventions are put forward.

This paper presents a review of electrical heating for the recovery of heavy oil which the work adopts methods used in the past and the prospects for crude oil recovery in the future. Heavy oil is one of the crude oils with API more than 22 which has the potential to overcome the current light oil crisis. However, high viscosity and density are challenges in heavy oil recovery. The method is often used to overcome these challenges by using thermal injection methods, but this method results in economic and environmental issues. The electrical heating method could be a solution to replace conventional thermal methods in which the methodology of electrical heating is to transfer heat into the reservoir due to increasing oil mobility. Because the temperature rises, it could help to reduce oil viscosity, then heavy oil will flow easily. The applications of electrical heating have been adopted in this paper where the prospects of electrical heating are carried out to be useful as guidelines of electrical heating. The challenge of electrical heating is the excessive heat will damage the formation that must be addressed in the prospect of electrical heating which must meet energy efficiency. The use of Artificial intelligence becomes a new technology to overcome problems that are often found in conventional thermal methods where this method could avoid steam breakthrough and excessive heat. Therefore, it becomes more efficient and could reduce costs.

Energy efficiency has long been an important issue to the global economic and political theaters, however, searching for an effective and concise measure for efficiency remains a contentious and intriguing topic. There are two obvious flaws with the commonly used metrics in existing literature. First, there is a sense of confusion and misunderstanding between the definitions of energy efficiency and efficacy. As a result, the formulae and methods for measuring efficiency are often the subject of criticism. Second, even if the definition of efficiency is clear, the method of estimation can be quite cumbersome, making it difficult to comprehend or implement. This study attempts to address these two issues. With an OECD comparative dataset, it first presents the contradiction between efficiency and efficacy, explains the loss of effectiveness with the existing measurements, and then proposes a new and easy-to-use method for gauging energy efficiency, so that the succinctness and robustness of the measurement can be re-established. The paper serves as a guide to those who are interested in the controversial issues related to measuring energy efficiency. Both practitioners and policy makers will find an easy and reliable tool from this paper for measuring energy efficiency.

Food and Beverage industry is one of the fastest growing manufacturing industries in Nigeria with its attendant carbon emission. In this paper, retrofitting (one of the demand side management (DSM) techniques) is adopted as a strategy to reducing energy consumption and the associated greenhouse gas emission of three selected food and beverages industries in Nigeria. This is achieved by carrying out a walk through energy audit on the selected industries with the aim of reducing their carbon footprint by reducing the electrical energy consumption pattern. Retrofitting exercise involves identification of energy-inefficient electrical equipment within the industry and thereafter replacing them with available identical device but with better energy efficiency. The investment cost for adopting energy efficient technology and its corresponding payback period are estimated. Recommendations for policy documents were proposed based on the study. The energy audit reveals that electric motor, lighting points (lamps) and computer system constitute electrical load that are inefficiently operated within the selected industries. Applying DSM by retrofitting on these components of electrical load reduces the overall electrical energy consumption of the industry by 17%, 20% and 14% for industries A, B and C, respectively. An estimated reduction in CO2 emission of 159,471.2 kg, 139,598.7 kg and 186,696.4 kg is achieved for industries A, B and C, respectively, using the DSM. This paper is useful as it provides scientific information on the need to retrofit inefficient devices in Nigeria industries.

This paper deals with the impact of the use of daylight on the overall energy demand for heating, cooling, and lighting in educational buildings. The energy performance of buildings is currently of the utmost importance as current European regulations, starting from 31st December 2020 impose that all new buildings must meet nearly zero-energy building requirements. This paper presents a study of the illuminance distribution in an educational room obtained from measurements and simulation results using two different models. One of the models, integrated with a thermal simulation software, was used to estimate the impact of daylight on the energy demand. The analysis included the use of various window types, lighting control system, reference point location, and daylight calculation model for a sample room in an educational building. Results of the analysis indicate that, due to the high share of lighting demand (reaching up to 78% of the primary energy balance), there is a need to take into account the efficiency of lighting systems during the design process to correctly determine the actual energy balance of a building, increase the quality of the design of lighting systems, as well as to select the optimal parameters of windows.