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Patrik Thollander - One of the best experts on this subject based on the ideXlab platform.
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Taxonomy, Saving Potentials and Key Performance Indicators for Energy End-Use and GreenhoUse Gas Emissions in the Aluminium Industry and Aluminium Casting Foundries
'MDPI AG', 2021Co-Authors: Joakim Haraldsson, Simon Johnsson, Patrik Thollander, Magnus WallénAbstract:Increasing Energy efficiency within the industrial sector is one of the main approaches in order to reduce global greenhoUse gas emissions. The production and processing of aluminium is Energy and greenhoUse gas intensive. To make well-founded decisions regarding Energy efficiency and greenhoUse gas mitigating investments, it is necessary to have relevant key performance indicators and information about Energy End-Use. This paper develops a taxonomy and key performance indicators for Energy End-Use and greenhoUse gas emissions in the aluminium industry and aluminium casting foundries. This taxonomy is applied to the Swedish aluminium industry and two foundries. Potentials for Energy saving and greenhoUse gas mitigation are estimated regarding static facility operation. Electrolysis in primary production is by far the largest Energy using and greenhoUse gas emitting process within the Swedish aluminium industry. Notably, almost half of the total greenhoUse gas emissions from electrolysis comes from process-related emissions, while the other half comes from the Use of electricity. In total, about 236 GWh/year (or 9.2% of the total Energy Use) and 5588–202,475 tonnes CO2eq/year can be saved in the Swedish aluminium industry and two aluminium casting foundries. The most important key performance indicators identified for Energy End-Use and greenhoUse gas emissions are MWh/tonne product and tonne CO2-eq/tonne product. The most beneficial option would be to allocate Energy Use and greenhoUse gas emissions to both the process or machine level and the product level, as this would give a more detailed picture of the company’s Energy Use and greenhoUse gas emissions
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Energy End-Use Categorization and Performance Indicators for Energy Management in the Engineering Industry
Energies, 2020Co-Authors: Fayas Malik Kanchiralla, Noor Jalo, Simon Johnsson, Patrik Thollander, Maria AnderssonAbstract:Energy efficiency (EE) improvement is one of the most crucial elements in the decarbonization of industry. EE potential within industries largely remains untapped due to the lack of information regarding potential EE measures (EEM), knowledge regarding Energy Use, and due to the existence of some inconsistencies in the evaluation of Energy Use. Classification of Energy End-using processes would increase the understanding of Energy Use, which in turn would increase the detection and deployment of EEMs. The study presents a novel taxonomy with hierarchical levels for Energy End-Use in manufacturing operations for the engineering industry, analyzes processes in terms of Energy End-Use (EEU) and CO2 emissions, and scrutinizes Energy performance indicators (EnPIs), as well as proposing potential new EnPIs that are suitable for the engineering industry. Even though the study has been conducted with a focus on the Swedish engineering industry, the study may be generalizable to the engineering industry beyond Sweden.
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Energy savings and greenhoUse gas mitigation potential in the swedish wood industry
Energy, 2019Co-Authors: Simon Johnsson, Patrik Thollander, Elias Andersson, Magnus KarlssonAbstract:Improving Energy efficiency in industry is recognized as one of the most crucial actions for mitigating climate change. The lack of knowledge regarding Energy End-Use makes it difficult for compani ...
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Energy End Use and efficiency potentials among swedish industrial small and medium sized enterprises a dataset analysis from the national Energy audit program
Renewable & Sustainable Energy Reviews, 2018Co-Authors: Elias Andersson, Patrik Thollander, Magnus Karlsson, Svetlana ParamonovaAbstract:Abstract Improving Energy efficiency in industry is recognized as one of the most vital activities for the mitigation of climate change. Consequently, policy initiatives from governments addressing both Energy-intensive and small and medium-sized industry have been enacted. In this paper, the Energy End-Use and the Energy efficiency potential among industrial small and medium-sized companies participating in the Swedish Energy Audit Program are reviewed. The three manufacturing industries of wood and cork, food products and metal products (excluding machinery and equipment) are studied. A unique categorization of their production processes’ Energy End-Use is presented, the results of which show that the amount of Energy Used in various categories of production processes differ between these industries. This applies to support processes as well, highlighting the problem of generalizing results without available bottom-up Energy End-Use data. In addition, a calculation of conservation supply curves for measures related to production processes is presented, showing that there still remains Energy saving potential among companies participating in the Swedish Energy Audit Program. However, relevant data in the database Used from the Swedish Energy Audit Program is lacking which limits the conclusions that can be drawn from the conservation supply curves. This study highlights the need to develop Energy policy programs delivering high-quality data. This paper contributes to a further understanding of the intricate matters of industrial Energy End-Use and Energy efficiency measures.
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benchmarking Energy performance of industrial small and medium sized enterprises using an Energy efficiency index results based on an Energy audit policy program
Journal of Cleaner Production, 2018Co-Authors: Elias Andersson, Oskar Arfwidsson, Patrik ThollanderAbstract:Abstract Improved Energy efficiency among industrial companies is recognized as a key effort to reduce emissions of greenhoUse gases. In this context, benchmarking industrial Energy efficiency plays an important part in increasing industrial companies' awareness of their Energy efficiency potential. A method for calculating an Energy efficiency index is proposed in this paper. The Energy efficiency index is Used to benchmark the Energy performance of industrial small and medium-sized companies' support and production processes. This enables the possibility to compare the Energy performance of single Energy End-Use processes. This paper's proposed Energy efficiency index is applied to Energy data from 11 sawmills that participated in the Swedish national Energy audit program. The index values were compared with each sawmill's Energy saving potential, as stated in the Energy audits. One conclusion is that the Energy efficiency index is suitable as an Energy strategy tool in industrial Energy management and could be Used both by industrial SMEs and by governmental agencies with an auditing role. However, it does require a harmonized categorization of Energy End-Use processes as well as quality assured Energy data. Given this, a national Energy End-Use database could be created to facilitate the calculation of an Energy efficiency index.
Mark D Levine - One of the best experts on this subject based on the ideXlab platform.
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china s Energy and emissions outlook to 2050 perspectives from bottom up Energy End Use model
Energy Policy, 2013Co-Authors: Nan Zhou, David Fridley, Nina Khanna, Michael A Mcneil, Mark D LevineAbstract:E RNEST O RLANDO L AWRENCE B ERKELEY N ATIONAL L ABORATORY China’s Energy and emissions outlook to 2050: Perspectives from bottom-up Energy End-Use model Nan Zhou, David Fridley, Nina Zheng Khanna, Jing Ke, Michael McNeil and Mark Levine China Energy Group Environmental Energy Technologies Division Lawrence Berkeley National Laboratory Reprint version of journal article published in “Energy Policy”, Volume 53, February 2013 March 2013 This work was supported by China Sustainable Energy Program of the Energy Foundation through the U.S. Department of Energy under Contract No. DE-AC02- 05CH11231.
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china s Energy and emissions outlook to 2050 perspectives from bottom up Energy End Use model
Energy Policy, 2013Co-Authors: Nan Zhou, David Fridley, Nina Khanna, Michael A Mcneil, Mark D LevineAbstract:Although China became the world's largest CO2 emitter in 2007, the country has also taken serious actions to reduce its Energy and carbon intensity. This study Uses the bottom-up LBNL China End-Use Energy Model to assess the role of Energy efficiency policies in transitioning China to a lower emission trajectory and meeting its 2020 intensity reduction goals. Two scenarios – Continued Improvement and Accelerated Improvement – were developed to assess the impact of actions already taken by the Chinese government as well as planned and potential actions, and to evaluate the potential for China to reduce Energy demand and emissions. This scenario analysis presents an important modeling approach based in the diffusion of End-Use technologies and physical drivers of Energy demand and thereby help illuminate China's complex and dynamic drivers of Energy consumption and implications of Energy efficiency policies. The findings suggest that China's CO2 emissions will not likely continue growing throughout this century becaUse of saturation effects in appliances, residential and commercial floor area, roadways, fertilizer Use; and population peak around 2030 with slowing urban population growth. The scenarios also underscore the significant role that policy-driven efficiency improvements will play in meeting 2020 carbon mitigation goals along with a decarbonized power supply.
Yoshiyuki Shimoda - One of the best experts on this subject based on the ideXlab platform.
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evaluating decarbonization scenarios and Energy management requirement for the residential sector in japan through bottom up simulations of Energy End Use demand in 2050
Applied Energy, 2021Co-Authors: Yoshiyuki Shimoda, Minami Sugiyama, Ryuya Nishimoto, Takashi MomonokiAbstract:Abstract Decarbonization scenarios for achieving net zero greenhoUse gas emissions in the Japanese residential sector by 2050 were examined using a bottom-up simulation model of Energy End-Use demand. The examined scenarios involve the dissemination of currently available technology, including highly insulated hoUses, high-efficiency equipment, high-efficiency appliances, electrification, and building-integrated photovoltaics (PV) in detached hoUses. The results show that decarbonization can be mostly achieved by the studied scenarios, especially through the dissemination of highly insulated buildings and high-efficiency water heaters as well as the installation of PV for all detached hoUses. This scenario reduced the total primary Energy demand by 61% in 2013. A land-Use strategy for increased detached hoUses is preferable for increasing PV capacity. For the scenario that achieves net zero Energy, the predicted heat load intensity and electricity consumption per capita are almost the same as those of the Low Energy Demand (LED) scenario. Increased depEndence on PV will create an imbalance in the relationship between electricity supply and demand, and 26% of the residential Energy demand would rely on non-battery Energy storage, such as pumped hydropower and hydrogen, owing to the seasonal time gap between residual and deficit electricity.
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residential Energy End Use model as evaluation tool for residential micro generation
Applied Thermal Engineering, 2017Co-Authors: Yoshiyuki Shimoda, Takuya Inoue, Masaya Otsuki, Ayako Taniguchimatsuoka, Yohei YamaguchiAbstract:It is expected that dissemination of micro-generation in the residential sector will have various kinds of impacts on urban- and grid-scale Energy systems. To evaluate these impacts quantitatively, it is necessary to Use an urban-scale Energy End-Use simulation model. The authors have been developing a city-scale residential Energy End-Use simulation model in a bottom-up manner. This model has three features. First, the model estimates all of the Energy demand profiles for each hoUsehold category. Second, the demand profile is estimated at 5-min intervals to simulate the realistic operation of a cogeneration system. Third, all hoUseholds in a target region are classified into detailed hoUsehold categories according to hoUsehold type and building properties. Therefore, this model can evaluate the potential contribution of residential cogeneration systems to Energy conservation and global warming mitigation on a city scale. In this paper, the Energy, economic, and environmental performances of micro-generation systems (SOFC, PEFC, gas engines) are evaluated for each hoUsehold category by this model. From these results, the CO2 reduction potential by disseminating micro-generation on a city scale is estimated in relation to cost. The change of the electricity load curve by dissemination of micro-generation into the residential sector is also evaluated.
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estimation of the contribution of the residential sector to summer peak demand reduction in japan using an Energy End Use simulation model
Energy and Buildings, 2016Co-Authors: Ayako Taniguchi, Takuya Inoue, Masaya Otsuki, Y Yamaguchi, Yoshiyuki Shimoda, Akinobu Takami, Kanako HanaokaAbstract:Abstract The effect of electricity peak demand reduction by electricity saving measures in the Japanese residential sector on the power system scale during summer was evaluated through the Use of a simulation model developed by the authors. In order to simulate the electricity peak demand on the power system scale, the model was improved so as to (1) represent the hoUsehold distribution and residential stock on the power system scale and (2) improve the temporal resolution of the simulation. The proposed model is a bottom-up type model that simulates residential electricity demand based on occupant behavior considering numerous factors, such as family composition, residence floor area, and building insulation level. Therefore, the proposed model can be Used to evaluate both occupant behavioral changes and Energy conservation technologies. As a result, we determined that the most influential behavioral measure in reducing summer peak demand is turning off the lights. The peak demand reduction effect when 5% of hoUseholds turned off the lights was 13 MW, which is equivalent to approximately 0.2% of the residential electricity demand during the daytime in summer in the Kansai region. The model also clarified differences in the electricity savings for each countermeasure among several family composition categories.
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prediction of greenhoUse gas reduction potential in japanese residential sector by residential Energy End Use model
Applied Energy, 2010Co-Authors: Yoshiyuki Shimoda, Ayako Taniguchi, Yukio Yamaguchi, Tomo Okamura, Yohei YamaguchiAbstract:A model is developed that simulates nationwide Energy consumption of the residential sector by considering the diversity of hoUsehold and building types. Since this model can simulate the Energy consumption for each hoUsehold and building category by dynamic Energy Use based on the schedule of the occupants' activities and a heating and cooling load calculation model, various kinds of Energy-saving policies can be evaluated with considerable accuracy. In addition, the average Energy efficiency of major electric appliances Used in the residential sector and the percentages of housing insulation levels of existing hoUses is predicted by the "stock transition model." In this paper, Energy consumption and CO2 emissions in the Japanese residential sector until 2025 are predicted. For example, as a business - as-usual (BAU) case, CO2 emissions will be reduced by 7% from the 1990 level. Also evaluated are mitigation measures such as the Energy efficiency standard for home electric appliances, thermal insulation code, reduction of standby power, high-efficiency water heaters, Energy-efficient behavior of occupants, and dissemination of photovoltaic panels.
Hiroshi Yoshino - One of the best experts on this subject based on the ideXlab platform.
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development of a ranking procedure for Energy performance evaluation of buildings based on occupant behavior
Energy and Buildings, 2019Co-Authors: Milad Ashouri, Fariborz Haghighat, Benjamin C M Fung, Hiroshi YoshinoAbstract:Abstract Identifying the impacts of occupants on building Energy consumption has become an important issue in recent years. This is due to the interrelationship of influencing factors such as urban climate, building characteristics, occupant behavior, and building services and operation, which makes it challenging to identify the role of occupants in Energy consumption. The research problem in this study lies in the fact that the occupants of a building may not be cautious regarding Energy savings, and there exists no ground to assess their Energy consumption behavior. One solution is the development of a systematic comparison procedure between similar buildings. This paper introduces a new procedure for comparison between occupants of several buildings to show the rank of each building among others and suggest occupants on reducing their Energy consumption and improving their rank. The proposed framework is developed based on multiple data-mining methods, including clustering, association rules mining, and neural networks. The proposed methodology is composed of two levels. The first considers the amount of Energy usage by occupants after filtering effects unrelated to the occupant behavior. The second ranks the buildings in terms of achieved and potential savings during the time under investigation. To demonstrate the application, the methodology was applied on a set of monitored residential buildings in Japan. Results suggest that the proposed method enhances the evaluation of buildings’ Energy-saving potential by revealing the occupants’ contribution. It also provides diverse and prioritized strategies to help occupants manage their Energy consumption by revealing the building Energy End-Use patterns.
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a systematic procedure to study the influence of occupant behavior on building Energy consumption
Energy and Buildings, 2011Co-Authors: Benjamin C M Fung, Fariborz Haghighat, Hiroshi Yoshino, Edward MorofskyAbstract:Efforts have been devoted to the identification of the impacts of occupant behavior on building Energy consumption. Various factors influence building Energy consumption at the same time, leading to the lack of precision when identifying the individual effects of occupant behavior. This paper reports the development of a new methodology for examining the influences of occupant behavior on building Energy consumption; the method is based on a basic data mining technique (cluster analysis). To deal with data inconsistencies, min–max normalization is performed as a data preprocessing step before clustering. Grey relational grades, a measure of relevancy between two factors, are Used as weighted coefficients of different attributes in cluster analysis. To demonstrate the applicability of the proposed method, the method was applied to a set of residential buildings’ measurement data. The results show that the method facilitates the evaluation of building Energy-saving potential by improving the behavior of building occupants, and provides multifaceted insights into building Energy End-Use patterns associated with the occupant behavior. The results obtained could help prioritize efforts at modification of occupant behavior in order to reduce building Energy consumption, and help improve modeling of occupant behavior in numerical simulation.
Yohei Yamaguchi - One of the best experts on this subject based on the ideXlab platform.
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residential Energy End Use model as evaluation tool for residential micro generation
Applied Thermal Engineering, 2017Co-Authors: Yoshiyuki Shimoda, Takuya Inoue, Masaya Otsuki, Ayako Taniguchimatsuoka, Yohei YamaguchiAbstract:It is expected that dissemination of micro-generation in the residential sector will have various kinds of impacts on urban- and grid-scale Energy systems. To evaluate these impacts quantitatively, it is necessary to Use an urban-scale Energy End-Use simulation model. The authors have been developing a city-scale residential Energy End-Use simulation model in a bottom-up manner. This model has three features. First, the model estimates all of the Energy demand profiles for each hoUsehold category. Second, the demand profile is estimated at 5-min intervals to simulate the realistic operation of a cogeneration system. Third, all hoUseholds in a target region are classified into detailed hoUsehold categories according to hoUsehold type and building properties. Therefore, this model can evaluate the potential contribution of residential cogeneration systems to Energy conservation and global warming mitigation on a city scale. In this paper, the Energy, economic, and environmental performances of micro-generation systems (SOFC, PEFC, gas engines) are evaluated for each hoUsehold category by this model. From these results, the CO2 reduction potential by disseminating micro-generation on a city scale is estimated in relation to cost. The change of the electricity load curve by dissemination of micro-generation into the residential sector is also evaluated.
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prediction of greenhoUse gas reduction potential in japanese residential sector by residential Energy End Use model
Applied Energy, 2010Co-Authors: Yoshiyuki Shimoda, Ayako Taniguchi, Yukio Yamaguchi, Tomo Okamura, Yohei YamaguchiAbstract:A model is developed that simulates nationwide Energy consumption of the residential sector by considering the diversity of hoUsehold and building types. Since this model can simulate the Energy consumption for each hoUsehold and building category by dynamic Energy Use based on the schedule of the occupants' activities and a heating and cooling load calculation model, various kinds of Energy-saving policies can be evaluated with considerable accuracy. In addition, the average Energy efficiency of major electric appliances Used in the residential sector and the percentages of housing insulation levels of existing hoUses is predicted by the "stock transition model." In this paper, Energy consumption and CO2 emissions in the Japanese residential sector until 2025 are predicted. For example, as a business - as-usual (BAU) case, CO2 emissions will be reduced by 7% from the 1990 level. Also evaluated are mitigation measures such as the Energy efficiency standard for home electric appliances, thermal insulation code, reduction of standby power, high-efficiency water heaters, Energy-efficient behavior of occupants, and dissemination of photovoltaic panels.