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Paper can be reused to efficiently manage biomass consumption, meaning that it has potential as an environmentally friendly material. On the other hand, because of high energy usage during the recycling process and transportation inefficiencies, there is a call for the development of technologies that can mitigate this environmental burden. This study evaluated, from a lifecycle perspective, a new technology that can collect and recycle paper within the office. This technology can reduce by over 90% the amount of water used compared with the conventional recycled paper that is pulped and bleached once by the dry process. It also eliminates transportation from paper collection facilities to recycling factories, reducing greenhouse gas emissions. This new technology is already in use in Japan, and analyses by user data indicate that evaluation results differ greatly depending on the utilization rate of the machine. In the future, environmental information should be shared by both users and manufacturers, so that users could increase their utilization rate, and manufacturers could develop alternative bonding agents in order to further reduce the total environmental burden. [ABSTRACT FROM AUTHOR]

The integration of vast quantities of clean energy causes intense impact on the power grid reliability. Digital Twin can be used to handle the high‐growth data flow generated in the power grid, and thus accelerate its digitalization process to fulfill the clean energy consumption target. As the traditional central cloud network structure can no longer effectively support the operation of digital twin power grid, the mobile edge network can be used as a reasonable substitute. To support the information interaction process of the mobile edge network, considering total profit, time delay and energy consumption, this paper proposes the mobile edge network communication and computing resource joint allocation model. On the basis, the GA‐PSO algorithm is proposed to solve the resource allocation optimization function. The feasibility and effectiveness of the proposed model is verified by the related simulation experiment. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Energy internet zones (EIZ) supply multiple energy carriers to customers in certain regions. They can achieve high energy efficiency by energy cascade utilization. In mid‐term, they participate in the wholesale market and retail market simultaneously. Customers can shift their energy use among different hours and energy carriers to satisfy demand according to the retail prices. Unfortunately, multiple energy systems and markets bring various uncertainties on demand and prices. In this paper, the weekly bidding strategy for the EIZ is proposed to determine the optimal bilateral contracts to sign and the optimal energy retail prices. In retail market, the satisfaction degree and elasticity matrix describe customers' response. Distributionally robust optimization is adopted to consider the distributional uncertainties of random variables and Worst‐case Conditional Value‐at‐Risk is employed for risk management. The distributional uncertainties of pool prices and elasticity matrix are discussed in this paper. An EIZ in Shanghai, China is adopted to illustrate the proposed strategy. The results have great resistance to distributional uncertainties. The risk aversion and satisfaction degree affect the EIZ's strategy in wholesale market and retail market, respectively. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

With the world population growth, energy consumption and the rapid development of industrial economy, a large amount of carbon emissions has brought destruction and threats to the earth's environment on which human beings depend. The development of low-carbon economy has become the consensus of governments all over the world and has been vigorously advocated & promoted. This paper focuses on the top five global GDP nations in 2022: The United States, China, Japan, Germany, and Britain. A comprehensive evaluation index system of urban low-carbon economic development level is constructed from four dimensions: economic development level, environmental quality, energy consumption emission intensity and social development speed by using literature review and field interview. The evaluation measures are determined using the TOPSIS evaluation method with entropy weight and the grey relational model, providing a comprehensive assessment of the low-carbon economy's development level in these five countries." Judging from the comprehensive evaluation score, the overall development of low-carbon economy in American cities is in good condition and has reached the development standard of low-carbon economy; Germany and Japan rank second and third, and they are low-carbon economies. Britain ranks fourth in comprehensive evaluation, although it belongs to a low-carbon economy country, but there is still a certain gap with Germany and Japan; There is still a big gap between China and the other four countries. Based on the measurement and evaluation outcomes, it presents recommendations and strategies to foster the growth of low-carbon economies, offering valuable insights for the advancement of such economies across different nations. The research results guide countries all over the world to reduce carbon emissions in the process of economic development, protect the earth environment on which human beings depend, and make a better tomorrow for sustainable development. [ABSTRACT FROM AUTHOR]

This paper compares the energy consumption of elderly and non-elderly households, recognizing the ever-increasing importance of the aging population for energy policy. Decisions of the domestic (in-home) and transport (out-of-home) sectors at the household level are jointly incorporated by building a multivariate Hierarchical Archimedean Copula model with intra-sector and inter-sector dependencies. Data from a life-oriented behavioral survey in Japan are used, which includes 532 elderly households and 340 non-elderly households. A variety of life-related factors, together with built environment factors, are introduced into the above model. Modeling analysis results show that inter- and intra-sector dependencies are heterogeneous across households in terms of these factors. It is found that almost equal numbers of influential factors are sensitive and insensitive to age-based sample segmentation. Various similarities and dissimilarities across energy types between elderly and non-elderly households are revealed. The paper concludes with a discussion of the policy implications of the results. [ABSTRACT FROM AUTHOR]

Climate change is a significant challenge that the medical community must address. Hospitals are large facilities with high water and energy consumption, as well as high levels of waste generation, which makes it important to pursue green hospital initiatives. Neurosurgery requires substantial energy for surgeries and tests. Based on the keywords "Climate change," "green hospital," "neurosurgery," "energy consumption," "environmental impact" listed in this paper, we extracted representative manuscripts, and the practices employed in the authors' hospital were assessed. The "Guidelines for Environmental Consideration in Hospitals" and "Guidelines for the Sustainability of Hospital Environments" have been developed; however, they are not implemented in most hospitals in Japan. Inhalational anesthetics were found to contribute significantly to greenhouse gas emissions. Educating patients and staff and employing the "8 Rs" (rethink, refuse, reduce, reuse, recycle, research, renovation, and revolution) showed promise in achieving green hospital standards. The advent of 'green hospitals' in Japan is imminent. The active participation of neurosurgeons can play a crucial role in diminishing the environmental footprint of health care while simultaneously enhancing medical standards. Given the pressing challenges posed by climate change, there is a critical need for an overhaul of medical practices. It is imperative for neurosurgeons to pioneer the adoption of new, sustainable medical methodologies. [ABSTRACT FROM AUTHOR]

Copyright of Smart Rail Transit is the property of Smart Rail Transit Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Energy‐efficient train operation (EETO) in high‐speed railways (HSRs) is an extra cost‐effective and flexible means to promote energy‐saving. This paper first examines the energy consumption sources and energy‐saving measures of high‐speed trains (HSTs). Then presents the EETO in HSRs, including three categories: energy‐efficient train control, energy‐efficient train timetabling, and EETO considering train timetabling and driving strategy. Next, the current research status and progress on three aspects of EETO in HSRs, namely optimization algorithm, constraint condition, and oriented scenario, are sorted out. Finally, the research on EETO in HSRs has prospected and proposed directions that can study in depth in the future. By summarizing and reviewing the research on EETO in HSRs, it is hoped to furnish a reference for the railway sector to enhance quality, efficiency, and green, low‐carbon development. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper deals with load extrapolation methods and algorithms for the estimation of the energy efficiency of induction motors, starting from the electrical data generally available after parameter identification. The main aim of this paper is to help the readers move from the theoretical analysis to the experimental verification, which is suitable to be included in its own testing. For this reason, step‐by‐step algorithms are included in this paper. The first part deals with the determination of energy efficiency based on an original load extrapolation. Finally, experimental verification of the high‐power and high‐voltage induction motors is provided. Comparison between the values of the in–out method and load extrapolation method confirms the validity of the proposed algorithms. Compared to the direct in–out method, the error of the load extrapolation proposed in this paper is less than 1%.The load extrapolation method is mainly used for the high‐voltage and high‐power asynchronous motor. The high‐voltage and high‐power motor can be used to drive a low‐power motor to achieve coaxial twin trawling in the absence of a suitable power supply and matched load. The energy efficiency of a high‐power motor under different loads are measured and estimated using a mathematical fitting method. The estimated energy efficiency curves in the whole load range can be used to evaluate the high‐power and high‐voltage induction motor. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In the empirical literature, there is no agreement on the linkage between environmental deterioration and economic growth. Thus, this paper aims to explore the long-run and causal effects of CO2 emissions, globalization energy usage, trade openness and urbanization on economic growth in Japan by employing new econometric techniques. The paper uses a dataset spanning from 1970 to 2015 and employs recent econometric techniques. To the best of the investigator's understanding, no prior studies have examined this linkage utilizing the wavelet coherence technique for Japan. The novelty of the wavelet is that it can capture the causality and long-run linkage between economic variables at different frequencies and periods. Thus, the study's aim is to address the following questions: (i) Is there a long-run and causal linkage between economic growth, energy usage, urbanization, CO2 emissions, trade openness and globalization? (ii) What is the interaction between economic growth and the regressors at various frequencies and periods? The paper utilizes the ARDL, DOLS and FMOLS to catch the long-run effects, whereas the wavelet coherence technique is employed to capture the causal effects among the indicators. The outcomes of the ARDL show that urbanization, CO2 emissions, globalization and energy usage trigger economic growth, while no significant linkage is found between trade openness and economic growth. The wavelet coherence approach reveals (i) positive co-movements between economic growth and the regressors and (ii) a one-way causality from CO2 emissions and energy usage to economic growth. [ABSTRACT FROM AUTHOR]

Scheduling workload is a demand response strategy for data centers to reshape electricity usage, which provides an opportunity for them to utilize renewable energy. Enhancing the flexibility of workload scheduling would promote the data center to integrate renewable energy. Considering that the improvement of flexibility in workload scheduling is tightly related to the Quality of Service (QoS) required by IT consumers (ITCs), it becomes desirable for the data center to collaborate with them to further facilitate renewable energy integration in demand response programs. This paper proposes a QoS‐based bi‐level demand response model for the data center, where game theory is adopted to resolve the conflict of interest in the collaboration between the data center and ITCs. At the upper level, the data center is a leader who provides differential monetary incentives to ITCs while dispatching workload to integrate renewable energy. At the lower level, ITCs act as followers who adjust the workload's QoS to enhance the flexibility of workload scheduling. Simulation results show that the proposed model can decrease the operating cost of the data center while increasing the utilization of renewable energy. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper reports demonstration results of non‐contact out‐of‐plane vibration energy harvesting using an electric‐double‐layer electret (EDLE). Unlike contact types or non‐contact in‐plane types, the proposed operation type can be useful in terms of expanding the operating frequency range and simplifying the device structures. A demonstration system is developed, and power generation is confirmed using an EDLE with a surface potential of −1 V under an atmospheric condition. © 2023 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper proposes an energy management strategy (EMS) based on double‐deep Q‐Networks (DDQN) with demand torque prediction (DTP) to optimize the fuel consumption of hybrid electric vehicles (HEVs) by online utilizing vehicle‐to‐vehicle (V2V) information. The main framework of the EMS is designed as DDQN, combining Q‐learning with the deep neural network to realize real‐time training and online optimization of the torque distribution between the internal combustion engine and the electric motor, and given that the model training easily falls into local minima and overestimation, two different Q‐networks are designed to decouple action selection and target evaluation. Meanwhile, BP‐network predicts future demand torque using the ego vehicle speed, front vehicle speed, and distance between the two vehicles to reduce the burden of model training due to the introduction of traffic information. The predicted demand torque is introduced into the DDQN‐based EMS as states, together with the distance traveled in the driving cycle and the current information on HEV. The effectiveness and adaptability to actual driving cycles of the proposed strategy are verified by comparison with DDQN‐based EMS without DTP and rule‐based EMS. The results show that the fuel consumption using DDQN‐based EMS without DTP is reduced by 4.1% compared with rule‐based EMS. The introduction of demand torque prediction resulted in a further 3.9% reduction in fuel consumption. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

With rapid industrialization, rising fossil fuel consumption, and environmental concerns, developing clean and green energy is an inescapable option. Hydrogen has emerged as a significant potential energy carrier and a viable future replacement fuel for fossil fuels due to its renewable and pollution-free properties. Previous review papers have significantly contributed to the body of literature on the various technologies for producing hydrogen by revealing key insights into their working principles and conditions, as well as the economic and environmental aspects. In addition, they also highlighted the potential pathways to enable the application of these technologies in the context of carbon neutrality. However, these studies have not broken down the evolutionary patterns and developmental progress of either fossil fuel-based or renewable energy-based technologies used to produce hydrogen. In addition, the currently available literature does not contain the most recent research that focuses on the evolution and life cycle of each technology category from a chronological point of view. The key drivers, countries/regions, and their contributions to the field's development have received little attention. As a result, it is critical to monitor technological advances in hydrogen energy production and investigate the key enablers of these advancements. Against this backdrop, the current study employs patent analysis tools to achieve four primary goals: (1) to track the development trends in the field of hydrogen production from 2000 to 2019; (2) to identify and compare the recent development trends in the last five years according to the feedstock, i.e., fossil fuel, water, and biomass-based technologies; (3) to predict the technology life cycle of the two main groups of hydrogen production technologies (fossil and renewable); (4) to identify and compare the key drivers of hydrogen production technologies from a statistical standpoint. The findings of the study may aid in identifying technical prospects in the field of fossil and renewable-based hydrogen production, and decision-makers may use them as a reference in developing a strategic plan for future technological growth. • Patent review on hydrogen production technologies from 2000 to 2019. • Japan, US, China are the leading countries in the field. • Recent developments are focused on renewable energy-based technologies especially water. • Technology maturity rate of renewable-based technologies is about 57%. • R&D expenditure strongly promotes hydrogen production innovations. [ABSTRACT FROM AUTHOR]

In order to construct an efficient and reliable global path for unmanned surface vehicles (USVs), this paper proposes a USV global path planning algorithm based on an optimized ant colony algorithm (OACA). The algorithm constructs a USV global path planning model by comprehensively considering energy consumption costs and turning control costs. In order to ensure the adaptability of the model to the task environment, the USV's motion characteristics are analyzed with full consideration of external interference, and on this basis, the characterization of energy consumption costs and turning control costs is completed. In order to obtain the global optimal solution of the model and accelerate the convergence speed of the model, in the initialization process of the ant colony algorithm, the initial pheromone is distributed unevenly by introducing the distance relationship among the intermediate node, the starting point, and ending point to improve the initial search efficiency. In the iterative process of searching for the optimal solution, enhancing the guidance effect of the current optimal solution on the offspring ants by introducing a weight factor to improve the update rule of pheromone, which accelerates the convergence speed of the algorithm. In the last two steps of the deadlock path, the number of lost ants is reduced by introducing a penalty factor to punish the pheromone which can guarantee the diversity of ants, and the algorithm's premature convergence is overcome. The simulation results prove the effectiveness of this algorithm. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In order to provide guidance for demand‐side management and improve energy efficiency, the accuracy of residential electricity demand forecasting plays a significant role. Data‐driven methods and deep learning network methods have been proved an effective methods for time series forecasting. In the context, the current research work proposes a novel neural network model based on convolutional neural network (CNN)‐attention‐bidirectional long‐short term memory (BiLSTM) to predict residential energy consumption. The proposed approach combines CNN, attention mechanism, and BiLSTM, initially implementing CNN to extract the effective features of the original data. Subsequently, the extracted segments are employed as the input of attention‐BiLSTM to predict energy consumption, where the attention mechanism comprehensively considers the output of BiLSTM neurons and assigns weights to neurons at each timestamp. In this article, we evaluate the proposed method using household electricity consumption data. This paper selects different input timestamp lengths (10/60/120 min, respectively) to validate the model's performance. We compare evaluation indicators (root mean square error, mean absolute error, mean absolute percentage error [MAPE]) between the proposed method and the state‐of‐the‐art prediction methods. The experimental result shows that the proposed method achieves higher energy consumption forecasting accuracy and has the lowest average MAPE (3.7%). © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The induction machine (IM) has advantages of simple structure, low cost, reliable operation, and convenient maintenance, and the application of ultra‐high efficiency IM could effectively improve the energy utilization rate and realize the emission reduction. Therefore, in this paper, the radial skewed rotor and the stator energy‐saving winding are first designed to improve the efficiency of IM. Then the Taguchi method, differential evolution algorithm, sequential subspace multi‐objective optimization, and 6σ evaluation criterion are integrated to realize the multi‐objective robust optimization design (MOROD). In the proposed MOROD scheme, the combined surrogate model is also researched to reduce the calculation burden during the optimization process. Furthermore, the MOROD scheme is applied to the design of a 22 kW, four poles ultra‐high efficiency IM to validate its effectiveness. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

With regard to environmental degradation in Japan, the world's third-largest economy, limited studies have been performed to illustrate the ecological aspects of the country's core and recent economic policies such as globalization, technological innovation, and renewable energy usage policies. Given this motivation, this research reveals a new perspective on the connection between CO2 emissions and GDP growth, renewable energy, technological innovation and globalization in Japan by employing wavelet statistical tools. The paper employs series of wavelet tools for datasets covering the period from 1990Q1 to 2015Q4. The empirical outcomes demonstrate proof of the interaction between renewable energy use, economic growth, technological innovation, globalization and CO2 emissions in both time and frequency. The empirical results of the wavelet analyses reveal that globalization, GDP growth, and technological innovation increase CO2 emissions in Japan, while renewable energy usage mitigates CO2 in the short and medium terms. The results demonstrate the significance of implementing policies effectively coordinated by the policymakers to curb the significant environmental degradation in Japan. Moreover, Japan should actively support renewable energy development and create a more competitive climate for investment in the renewable energy market. [ABSTRACT FROM AUTHOR]

SUMMARY This paper evaluates the impact of an extensive introduction of electric vehicles (EVs) and plug-in hybrid vehicles (PHEVs) on the energy supply mix in Japan. Energy consumption in Japan's transport sector has been dominated by petroleum, and CO2 emissions in this sector account for 20% of Japan's CO2 emissions. Therefore, the deployment of clean energy vehicles, such as EV and PHEV, is expected to play a significant role in tackling energy security and environmental concerns. In order to assess the energy and environmental benefits of EV and PHEV, we develop an energy system model integrating an optimal power generation mix model and a vehicle penetration model, with consideration of the optimal electricity charging profile of those advanced vehicles. The calculated results suggest that massive EV penetration serves as an energy saving measure in Japan's whole energy system due to significant petroleum reductions exceeding the growth of fuel input into the power generation sector derived from significant EV and PHEV penetration. Massive EV deployment is estimated to contribute to CO2 mitigation in the energy system as well. Evaluating CO2 emissions by mileage by automobile, however, carbon emissions by mileage for EVs is almost equivalent to that of gasoline hybrid vehicles (HEVs) in the case of decommissioning of nuclear power plants, which eventually causes a higher carbon intensity of the electricity supply. [ABSTRACT FROM AUTHOR]

This paper focuses on the post-Great East Japan Earthquake narratives and discourses related to various types of energies currently in use in East Asia. Methodologically, interpretive study and textual analysis of collected secondary literatures, media reports as well as some policy resources was conducted. It examines the factional interests, narratives, discourses and schools of thought influencing the outcome of energy issues or decisions as they are reported in the media or trade publications. It argues that decision-makers and policy implementers are not a hegemonic singular entity but encompass many factional interests and contesting agendas. [ABSTRACT FROM AUTHOR]

In this paper, we present an ensemble stacked generalization (ESG) approach for better prediction of electric vehicles (EVs) energy consumption. ESG is a weighted combination of multiple base regression models to one meta-regressor, which enhances the model prediction and decreases the model variance over a single regressor model. For the current study, we develop ESG by combining three individual base machine learning algorithms, i.e., Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN), to predict the EVs' energy consumption. Tackling the challenge of predicting EVs' energy consumption, the data were collected from Aichi Prefecture, Japan, combining the digital elevation map with long-term GPS tracking data. EVs energy consumption in terms of energy efficiency (kWh/km) was estimated using several important variables such as average trip speed (km/h), trip distance, nighttime lighting, air conditioner (A/C), heater usage ratio, and road gradient. Several statistical evaluation metrics were used to evaluate the performance of the proposed methods. The prediction results show that ESG is more robust in predicting EVs' energy consumption and outperformed other models by yielding more acceptable values for proposed evaluation metrics. The results further demonstrate that the accuracy of predictive models for EVs energy consumption can be reasonably accomplished by adopting stacking techniques. The finding of this study could provide essential guidance to decision-makers and practitioners for planned development and optimal placing of EV charging infrastructures in urban areas. [ABSTRACT FROM AUTHOR]

In this study, we clarify the effectiveness of the energy‐effective techniques for the occupancy lighting control that is based on an occupancy sensor. The time delay from detecting no occupant to turning off the light is used for performing the occupancy control to avoid erroneously turning off the light (hereafter referred to as false‐off). Our experiment was conducted at an actual home environment over 8 days. We evaluated the performance of an image‐based sensor, which detects the occupants using image‐processing techniques and time‐delay adaptation, which decreases the time delay without false‐off. Compared with a passive infrared sensor, the image‐based sensor increased the average sensing accuracy for occupants with small movements by 21.58% or more. In addition, compared with the no‐adaptation case, the time‐delay adaptation increased the rate of average lighting energy saving by 3.94% or more. However, the experimental results suggested that the parameter of the time‐delay adaptation should be carefully set in terms of the energy‐saving effect and false‐off. The analysis and its practical discussions are included in this paper to achieve further energy efficiency. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

A high‐voltage direct‐current circuit breaker is a key equipment to construct a flexible direct current transmission system. Most of the existing design schemes have some shortcomings such as slow fault‐breaking speed, poor current‐limiting effect, large capacity of the arrester, and long reclosing operation time. To solve the above problems, this paper proposes an H‐type high‐voltage direct current circuit breaker with a current‐limiting function. The current‐limiting inductance is put into operation by judging the fault condition. It has good current‐limiting ability in the process of fault‐breaking and can maintain the dynamic performance of the power grid in the normal operation of the system. It has the advantages of fast fault‐breaking speed, buffered energy consumption, early separation of fault points, and small capacity of the arrester. During reclosing operation, the transfer branch can be turned on at no‐voltage. The different working states in the process of fault‐breaking are analyzed theoretically based on the description of the topological structure and working principle. Finally, using the PSCAD/EMTDC simulation platform, the functional verification and system verification of fault‐breaking and the reclosing operation process is conducted. Compared with the typical scheme, the simulation analysis shows the effectiveness and applicability of the function of fast fault‐breaking and fault current‐limiting. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The main hindrances to employing non‐volatile memory (NVM) to the embedded system are the extra energy consumption and long latency of switching states of NVM cells. To mitigate these drawbacks, several schemes have been studied based on the read‐before‐write scheme (RBW), which reduces the number of write operations by skipping writing bits that are the same in the existing values and new values. Thus, they compare all bits before updating the data. However, these studies also need extra read operations for every write operation. To address this problem, a zero‐bit pattern scheme is proposed that skips accessing bit cells determined as zero‐bits. In addition, the granularity of the zero‐bit pattern is dynamically adjusted depending on the pattern of the non‐leading zeroes. The results of the experiments show that dynamic energy is reduced by 43.5% with 4.7% storage overhead. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In light of climate change, there is pressure worldwide to curb emissions via energy efficiency, conservation, and renewable energy. Woody biomass has a role in sustainable energy transitions, contributing to emissions reduction, economic development, and energy security as a dispatchable resource. This potential is recognized globally, but the woody biomass supply chain has faced technical and social challenges. Smart technologies are increasingly discussed in discourse on supply chain management, such as their potential to improve transparency and efficiency. Despite a variety of research related to woody biomass as well as smart technologies, little attention has been given to integrating the two perspectives. This study explores this intersection by highlighting smart technologies and mechanisms by which they may contribute to overcoming challenges in the woody biomass supply chain, exemplified by the case of Japan. Based on qualitative expert interviews, exploratory results suggest potential of smart technologies that would contribute to addressing both social and technical challenges of woody biomass in Japan. These challenges include transportation infrastructure, biomass quality management, business model integration (cascading), stakeholder relationship management, and local community revitalization and socioeconomic development. This contribution is based on various mechanisms such as improved transparency, information-sharing, accountability, automation, and value maximization. The results of this paper delineate a potential future development path that integrates smart technologies, woody biomass supply chains, and sustainability goals. This is an important further consideration for energy policy in academia, industry, as well as government. [ABSTRACT FROM AUTHOR]

Copyright of LogForum is the property of LogForum and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Decoupling of GDP from all energy sources under multiple principles are examined. • World economy achieved weak energy decoupling in most years during 2000–2011. • World economy coupled with coal use and tended to couple with cleaner energy use. • None of studied economies achieved long-term GDP-embodied energy decoupling. • Decoupling delusions occurred when only considering direct and total energy use. Decoupling indicators are widely used to understand links between economic growth and energy use. However, traditional decoupling analyses mostly focus on domestic energy consumption (i.e., the production-based principle) and neglect off-site energy use across global supply chains to satisfy an economy's final consumption (i.e., the consumption-based principle). Moreover, analyses for total primary energy conceal an economy's preference for different energy sources. Therefore, this paper evaluates decoupling states of GDP from all types of primary energy use under consumption-based principle, for world economy and eight typical economies during 2000–2011. Regarding total primary energy, world economy witnessed weak decoupling in most years, and most economies studied (e.g., USA, Japan and China) achieved decoupling initially but performed negative decoupling finally. For EU, USA, Japan, Russia and India, production-based decoupling performances were generally better than consumption-based ones. Decoupling phenomena detected under production-based principle even became coupling or negative decoupling under consumption-based principle in some cases. As for each energy source, world economy decoupled from oil use, but still coupled with coal use, and gradually showed a trend to couple with natural gas and renewables use. Different energy sources showed distinct decoupling degrees from GDP, affected by individual embodied energy requirement structure. This paper uncovers potential energy decoupling delusions to deepen the understanding of relationships between energy use and economic growth. [ABSTRACT FROM AUTHOR]

This paper aims to offer a quantitative contribution to energy-environment policy in Japan in the aftermath of the Fukushima nuclear power accident. Since then, nuclear power energy supply has almost entirely been banned, and consequently, an intensive search for alternative forms of energy supply (ranging from fossil fuels to renewable forms of energy, such as solar or thermal power) has started. There is no clear-cut direction for energy policy, as each option involves costs and CO consequences; Japan has even withdrawn from the Kyoto protocol. A balanced energy-environment policy is difficult to achieve in the short term, and therefore, there is an urgent need for a comprehensive efficiency and performance analysis of the Japanese energy sector. A popular standard tool to judge the efficiency or performance of a decision-making unit (DMU) is a data envelopment analysis (DEA). The existence of multiple efficiency-improvement solutions has prompted much criticism in recent years. In the meantime, much progress has been made in extending this approach in several directions. An example is the euclidean distance minimisation (EDM) method, based on a generalised distance function, which serves to improve a DMU's performance by tracing the most appropriate movement towards the efficiency frontier. The EDM model is able to calculate an optimal input reduction value and an optimal output increase value in order to reach an efficiency score of 1.0, even though in reality this may be hard to achieve for low-efficiency DMUs. In contrast, high-efficiency DMUs might find it easier to reach an efficiency score of 1.0, or in the case of a super-efficiency DEA, a score of above 1.0. This paper aims to present a newly developed adjusted DEA model, emerging from a blend of the EDM and the target-oriented (TO) approach based on a super-efficiency model, for generating an appropriate efficiency-improving projection model. The TO approach specifies a target-efficiency score (TES) for inefficient DMUs. This approach can compute an input reduction value and an output increase value in order to achieve a higher TES. The abovementioned TO-EDM model will be applied to an efficiency analysis of the energy-environment interface for 10 regions in Japan. The focus will be on one input cost criterion (viz. expenditures) and two output performance criteria (viz. electricity generation and CO emission). Based on an extensive database, a comparative performance analysis of the 10 Japan regions under consideration will be pursued. [ABSTRACT FROM AUTHOR]

The equipment energy efficiency improvement policy (EEEIP) is one of the important measures of energy conservation and emission reduction in various countries. However, due to the simultaneous implementation of variety policies, the effect of the single policy cannot be clearly reflected. In this paper, a method of identification and evaluation of EEEIP was proposed, and the application was verified by analyzing the example of EEEIP in Japan (Top Runner policy, TRP). Firstly, through the factor decomposition model, this paper studied the energy conservation and emission reduction potential of this policy area in Japan. Then, the TRP was identified by using moving windows and correlation analysis, and the impact of specific equipment in TRP was analyzed. Finally, through the calculation of the rebound effect of the carbon footprint (REC), this paper analyzed the energy consumption and emission reduction effects of TRP in the short-term and whole life cycle. It showed that the policy has a good effect in tertiary industry and transportation, while the effect in residential is poor. For life cycle, the TRP of air conditioning and passenger car can bring better CO2 emission reduction effect, but the emission reduction effect of lighting is basically offset. [ABSTRACT FROM AUTHOR]

Using annual data from 1970 to 2014, this paper examines the effects of globalization on CO2 emissions in Japan while accounting for economic growth and energy consumption as potential determinants of carbon emissions. The structural breaks and asymmetries arising due to policy shifts require attention, and hence, an asymmetric threshold version of the ARDL model is utilized. The results show the presence of threshold asymmetric cointegration between variables. Threshold-based positive and negative shocks arising from globalization increase carbon emissions, while the impact of the latter is more profound. Energy consumption (economic growth) also has a significant positive effect on carbon emissions. Globalization, economic growth, and energy consumption significantly increase carbon emissions in the short run. We suggest that policy makers in Japan consider globalization and energy consumption as policy tools in formulating their policies regarding protecting sustainable environmental quality in the long run. Otherwise, the Japanese economy may continue to face environmental consequences such as undesirable climate change and massive warming at the micro and macro levels as a result of potential shocks arising from globalization and energy consumption. [ABSTRACT FROM AUTHOR]

This paper provides a detailed analysis of the Tokyo Metropolitan Emissions Trading Scheme (Tokyo ETS), Japan’s first emissions trading scheme with mandatory cap initiated by the government of Tokyo. Unlike trading schemes in other countries, the Tokyo ETS covers indirect emissions from the commercial sector. It is well known that a variety of market barriers impede full realization of energy efficiency opportunities, especially in the commercial sector. Experiences with the Tokyo ETS should therefore provide important lessons for the design of climate change mitigation policies, especially when targeting the commercial sector. The emissions from covered entities have been drastically reduced from those at the scheme’s outset, with an average 14% reduction as of the end of the first commitment period of five years (2010-2014) compared with 2009 levels. This paper shows that the Tokyo ETS alone did not cause these reductions; there were other drivers. Among them, the energy savings triggered by the Great East Japan Earthquake in 2011 were crucial. The contribution of credit trading, in contrast, was limited since most of the covered entities reduced emissions by themselves. Through an investigation of official reports, an assessment of the emissions data from the covered entities compared to those of uncovered entities and in-depth interviews with firms covered by the scheme, this paper confirms that the main drivers of emissions reductions by covered entities were separate from the ETS. In fact, the advisory aspect of the scheme seems to be much more important in encouraging energy-saving actions. Key policy insights Most of the observed emission reductions were not caused by the Tokyo ETS alone. An advisory instrument was crucial to the effectiveness of the Tokyo ETS. The experience of the Tokyo ETS suggests that making full use of the advantages of emissions trading is difficult in the case of the commercial sector. Price signals have not provided a stimulus to climate change mitigation actions, which implies that establishing a cap to yield effective carbon prices poses a challenge. [ABSTRACT FROM AUTHOR]

In this paper, we develop a new approach that combines the spectral clustering method and input–output analysis to detect environmentally important supply chain clusters. The newly developed method was applied to automobile manufacturing in Japan, and major clusters with high energy intensities in the automobile supply chain were identified. This paper proposes that the car manufacturers will be able to regularly publish their life-cycle assessment reports with a focus on the indirect energy consumptions within the critical supply chains and request key auto-part manufacturers in the cluster to reduce the indirect consumptions through the relevant supply chain engagement. [ABSTRACT FROM AUTHOR]

This paper examines whether voluntary actions can lead to manufacturing sector investment that reduces environmental impact. Our approach relies on unique firm-level panel data. First, we investigate the effects of the Keidanren's (Japanese Business Federation) voluntary action plans (VAP) on investment in energy efficiency and environmental preservation. We also consider the type of VAP used by a firm, whether absolute or relative targets. We conclude that firms with absolute targets are more likely to invest in energy-efficiency processes than those with relative targets. Our simulation confirms that the use of absolute targets can increase investment in energy efficiency by 7%. Hence, we confirmed that voluntary action plans with absolute targets are effective in increasing investment related to energy efficiency. Second, we examine whether VAP promotes investment in low-emission processes at the expense of productive investment. We conclude that VAP promotes investment in energy efficiency and protecting the environment by reducing productive investment. Finally, our results did not verify the existence of a liquidity constraint for emission reduction investment for large firms. [ABSTRACT FROM AUTHOR]

The aim of this paper is to define low carbon society (LCS) based on the phase diagram with the variables from the IPAT [Human Impact (I) on the environment equals the product of population (P) affluence (A) and technology (T)], starting from the problem definitions: (1) Economy is not everything for LCS and (2) it is not clear if speed on the constraint is more important than liberation from it. To tackle these problems, two research questions are set: (1) What are the basic indicators, objects, and constraints to shape the argument of LCSs and (2) what are the historical paths of several countries and what can be said for their future paths toward carbon societies? Time series data from 1900 or before are used, while the phase diagram with the variables from the IPAT equation is used as the core methodology. In addition to the IPAT variables, the importance of land per capita shall be considered as another basic indicator for LCS related to the carrying capacity. The three different kinds of objects [i.e., total gross domestic product (GDP), GDP per capita, and social indicator] and the two constraints (i.e., total emission and emission per capita) are considered, and it is shown that the combination of these objects and constraints strongly affects the argument of the carrying capacity of climate and land, development of economic system and economic man, and other human developments. Among the four cases analyzed in the phase diagram, the case where GDP per capita is object and total emission is constraint is given the most attention and requires the further research in the future since it does not contradict with a definition of LCS. It is also suggested that if changing the direction of the path with low carbon technology development takes time and cost, institutional arrangement would be additionally necessary in addition to market mechanism where optimal solutions are found on constraint. [ABSTRACT FROM AUTHOR]

The implementation of tax reforms to reduce carbon dioxide (CO2) emissions has become increasingly popular. Nevertheless before prescribing these measures, they should be subject to a cost-benefit analysis. This paper evaluates the effects, in Spain, of a rise in the excise duties on energy to a level equal to the average of the EU-15. To this end, a complete demand model, comprising four energy products and fourteen nonenergy products, is estimated. The results indicate that such a reform, despite the fact that it would reduce CO2 emissions by 11 million tons per year, would produce efficiency costs of 15.88¢ for each euro collected, causing households an average annual welfare loss of 228€. Moreover, the progressivity and redistributive capacity of Spanish indirect taxation would be also reduced. As a result, the private welfare loss arising from the reform would be approximately four times greater than its estimated social benefits. [ABSTRACT FROM AUTHOR]

This paper proposes an I-O SDA model, based on a commodity technology assumption, to identify the sources of changes in the energy demand structure, the non-energy input structure, the non-energy product-mix and the non-energy final demand of embodied energy requirements. The model contains two features. First, the hybrid rectangular input-output framework expressed in both monetary and physical terms is introduced to relax the effects of different energy prices among industrial sectors on the input structure in physical terms. Second, the demand structure of the input-output system is decomposed into the structure of energy sectors and other sectors by applying the hierarchy system with feedback loops of non-energy sectors. We identify the sources of the changes in Japan's energy use structure between 1985 and 1990. The major findings are that the total energy requirement has increased, mainly because of the changes in the non-energy final demand, while the product-mix changes have opposite effects, that is, energy savings. [ABSTRACT FROM AUTHOR]

Energy is one of the important elements in the production of goods and satisfies the required services. The economy of Japan is basically dependent on imported energy resources for 97% of its total domestic energy consumption per year, the highest percentage of any major industrialized nations. Thus, reducing dependency and import expenditures are always main issues in the energy policy of Japan. In this study, four indices are constructed to measure Energy Supply Security: Dependency Index, Intensity Index, Local Production Index, and Composite Index. This paper investigates the causal relationship between aggregated and disaggregated levels of energy supply security indices and the input parameters that are: petroleum prices, total primary energy supply, energy consumption per capita, share of renewable energy sources, carbon dioxide emissions, human development index, and the mean of democracy indices of energy supplier countries of Japan for the period of 1975–2007. [ABSTRACT FROM PUBLISHER]

Competitive bidding is an important policy tool for governments to procure goods and services at the lowest possible cost in the market. Under the traditional public procurement system, however, it is difficult to purchase a highly customized object, such as energy efficiency services, because not only prices but also other nonmonetary aspects need to be taken into account. Multidimensional auctions are useful in such cases. The paper examines the cluster of characteristics of the winning bids of multidimensional auctions for public energy service company (ESCO) projects in Japan. As theory predicts, it is found that the competition effect is significant. Other institutional aspects-such as preannouncement of an energy savings target-are also found important to promote energy efficiency. The results also indicate that the public sector should absorb the regulatory and institutional risks that are related to ESCO projects. [ABSTRACT FROM AUTHOR]

Japan's energy consumption in 2018 was about 2.5 times that in 1975, with the increase in the household sector being the largest at 28%. Most of primary energy is still fossil fuel, and it is urgent to reduce energy consumption in the household sector. The purpose of this paper was to identify ways to reduce household energy consumption without compromising the quality of life in residence. However, the reduction methods vary by region, building specifications, household type, equipment specifications, season, and weather. The value of this paper is based on a systematic analysis of home energy management systems (HEMS) data from about 50,000 households under various conditions. We are analyzing ways to reduce energy consumption. Few studies have analyzed this much back-up data, which is likely to lead to a reduction in CO2 emissions across the household sector. To explore ways to reduce energy consumption in this sector, the company has introduced and provided services for home energy management systems (HEMS) since 2011 and is currently collecting HEMS data for up to 50,000 households. In order to grasp the actual state of energy consumption in each household, HEMS data are systematically analyzed, necessary conditions for energy reduction and self-sufficiency rate (SSR) improvement are analyzed, and energy consumption under certain conditions is estimated using storage batteries (SB) and heat pump water heaters (HPWH). In addition, energy consumption was investigated by actual measurement and simulation for several hundred households. Since power generation and consumption vary greatly depending on the region, building specifications, household type, equipment specifications, season, weather, etc., it is necessary to analyze these factors systematically. As a conclusion, in order to improve SSR, it is necessary to (1) reduce surplus power consumption and energy consumption of heat pump water heaters (HPWHs), (2) increase solar power generation, and (3) increase the size of SB. This study contributes to the spread of advanced housing and the reduction of CO2 emissions in the household sector. [ABSTRACT FROM AUTHOR]

To date no technical-economic-environmental review has been carried out on the use of hybrid wind-solar power plants in Japan. The study reported in this paper used HOMER soft- ware to analyze the electricity supply from renewable energy systems at 198 stations in Japan. The ranges of wind speed and solar radiation of the locations are 1.6-12 m/s and 2.723- 5.435 kWh/m2-day, respectively. The results show that the average, maximum and minimum use of renewable energy in Japan are 96.2%, 100% and 89%, respectively. Also, the av- erage, maximum and minimum cost per kWh of energy are $ 0.434, $ 0.526, and $ 0.249, respectively. The cheapest wind turbine system (the cheapest renewable energy system), the cheapest solar system, the cheapest hybrid wind-solar system, and the most expensive hybrid system, have a price per kWh of energy $ 0.294, $ 0.349, $ 0.339 and $ 0.526, respectively. These systems are located at Fuji Mountain, Minamitorishima, Iwojima and Tokyo, respectively. [ABSTRACT FROM AUTHOR]

SUMMARY This paper focuses on residential photovoltaic systems in Japan. It projects the installation and installed capacity of residential photovoltaic systems by analyzing the correlation between their payback period and annual installation in new and existing homes. Exponential and hyperbolic curves are used for correlation analysis. However, the exponential curve gives a better fit than the hyperbolic one. PV installation in new houses shows a stronger correlation with the payback period than with existing houses. For the installation projections, target and delayed scenarios are assumed. In the target scenario, the target price is achieved as planned. However, it is achieved later in the delayed scenario. Ongoing subsidies and feed-in tariffs are also assumed. Based on the results of the analysis, the target cumulative installation and installed capacity are achieved in the target scenario. They are not significantly affected even without subsidies and feed-in tariffs. But they are reduced by almost half in the delayed scenario compared with the target scenario. This means that systemic price reductions resulting from research and development as well as mass production are more effective than ongoing dissemination promotion programs. To achieve the target capacity, not only cost reductions but also conversion efficiency improvements through research and development are indispensable. [ABSTRACT FROM AUTHOR]

The steelmaking industry in Japan has significantly reduced its energy use for the past several decades and has kept the highest energy efficiency in the world. However, the steelmaking industry is strongly required to develop new technologies for further energy conservation in view of energy security, high and volatile energy prices, and climate change. One of the key technologies to achieve the requirement is waste heat recovery. This paper describes the thermoelectric generation (TEG) system using the waste heat in the steelmaking process. In this system, the TEG unit, which consists of 16 thermoelectric modules made of Bi-Te thermoelectric materials, generates the electrical power directly by converting the radiant heat released from hot steel products. Each thermoelectric module, whose size is 50 mm × 50 mm × 4.2 mm, generates 18 W when the hot-side temperature is 523 K and the cold-side is 303 K. Therefore, the output of the TEG unit is over 250 W. The performance and the durability of the system have been investigated under various operating conditions in steel works. The results of the verification tests in the JFE steel Corporation's continuous casting line will be discussed. [ABSTRACT FROM AUTHOR]

SUMMARY Reducing the rates of nuclear power generation for all electric power sources has been seriously discussed in Japan since the accident at the Fukushima No. 1 nuclear power plant in March 2011. Thus, the distributed power supply is expected to expand. The local production of safe and clean energy for local consumption is greatly needed in Japan. In this paper, the Saroma Lake green microgrid (SLMG), a fuel cell microgrid using tidal power generation and photovoltaics, has been planned. Energy balance equations were used to investigate this system's method of operation. Further simulated analysis of the facility, its operation cost, and the electric power quality of the network were conducted using MATLAB/Simulink, and the relationships among the capacity of a facility, the cost, and supply rate of green energy and the electric power quality (interphase voltage, frequency, and higher harmonic wave) of the power network were clarified. The total projected cost of the equipment and operation for introducing the proposed SLMG is ¥1,500,000,000/10 years. Increasing the supply rate of green energy and reducing the facility cost will require the introduction of biofuels and the reduction of the facility costs of solid oxide fuel cells in the SLMG. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Higher demand for energy consumption and importance of environmental issues has encouraged researchers and policy makers to consider renewable energies more seriously. Geothermal resources are a green energy source that can make a considerable contribution in some countries. Japan has the third ranking geothermal energy potential, and its geothermal electricity production is currently eighth in the world. Since the nature of geothermal resources dictates its method of utilization, it is important to categorize available resources. There is no consensus on classification of geothermal resources. Most scientists, from geologist to engineers, agree on the term temperature. However, temperature or enthalpy alone cannot describe the nature of fluids; they can have same temperature with different phases, such as saturated water or saturated steam. Using exergy for resource classification benefits their comparison, according to their ability to do work. In this paper, exergetic classification of geothermal resources was applied to 18 under-operating geothermal power plants in Japan. Six geothermal fields have high exergy resources according to their SExI values in excess of 0.5. The remaining geothermal fields in Japan are classified in the medium resources zone. Classification results can be used by decision makers as a reference for future geothermal development. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a hybrid intelligent system is proposed for designing a contract model of the weather derivatives between energy utilities. In recent years, the weather conditions often bring about uncertainties on profits to companies that are related to weather conditions. As a result, they require a strategy to equalize the profits and avoid unexpected deficits. To satisfy the requirements, weather derivatives are developed to the companies. They may be expressed as the function of the weather conditions such as the average, the maximum temperature, etc. So far, a lot of the derivatives have been developed, but it is not clear how to design them due to the nondisclosure on practical knowledge. In this paper, an efficient method is presented to determine a contract model of weather derivatives. As the first stage, this paper focuses on the normal data. A reasonable model is constructed by the learning process for the normal data. This paper formulates the contract model as a two-phased problem. Phase 1 carries out data clustering of curves to extract the normal data with DA (Deterministic Annealing) of global clustering technique. Phase 2 optimizes the parameters of the model that equalizes the payoffs between two companies in a sense that the mean and the variance of the payoff are equalized for both companies with EPSO (Evolutionary Particle Swarm Optimization) of meta- heuristics. The proposed method is successfully applied to the real data in Tokyo, Japan. [Copyright &y& Elsevier]

• Operating time of SMEs is estimated using a SOM and hourly demand data. • The estimated operating time is used for hourly AC demand disaggregation. • The average errors of yearly AC demand estimation are better than 10%. • Hourly disaggregation highlights season and time period of AC demand peaks. Despite the growing penetration of smart meters and energy management systems in recent years, few tools have been proposed for energy demand data analysis and visualization to promote energy conservation in small- and medium-sized enterprises (SMEs). In this paper, we propose a new method consisting of operating time estimation and simplified disaggregation based only on the SME's hourly electricity demand data and actual outdoor temperature data. The method first estimates the operating time using a self-organizing map, which categorizes the hourly data as operating, half-operating, or non-operating time and eliminates manual parameter adjustment that requires user trial and error. Then, using the estimated operating time, our simplified disaggregation method estimates hourly air conditioning (AC) demand considering the variation in each office's temperature at which air conditioners are switched on. The method was evaluated using a public business energy management system dataset from Japan, and the average errors of yearly AC demand estimation were better than 10%. The outputs of the proposed method may provide information that is more relevant, reliable, and specific to each customer and efficiently promote energy conservation measures in SMEs. [ABSTRACT FROM AUTHOR]

This paper presents a review of historical changes in residential energy demand, everyday practices and related societal systems in Japan by using an analytical framework designed based on social theories of practice. The purpose was to understand the overall societal structure that determines energy demand and its trajectories. The review addressed mutual relationships between 1) everyday practices and societal systems that have shaped everyday practices, 2) those of life course practices, which are social activities performed by individuals over life time span, such as marriage, parenting and occupation, 3) everyday and life course practices, and 4) societal elements that have shaped everyday and life course practices. Thus, residential energy demand is an outcome of dynamics in the complex system constituted by these practices and respective societal systems. Dynamics in each element and the mutual relationships account for continuous changes in everyday practices and residential energy demand. Based on the overall structure and its trajectories, several energy management implications were derived. The framework also allows the welfare system to be designated as a key support of life course and everyday practices. This application shows that its ongoing transition has a significant impact on household practices and energy demand. • Practice-theory-based framework reviewed Japanese households and energy demand. • Life course and everyday practices and societal systems shaping them coevolve. • Relationship between changes in society, practice and energy demand is addressed. • There is a societal structure making household small and behave more independently. [ABSTRACT FROM AUTHOR]

ABSTRACT Despite the lack of mandatory thermal requirements in the housing sector, an average Japanese household consumes around one-third of the energy for heating and cooling compared with a UK or German household. Based on a policy analysis and interviews, this paper identifies the concept and policies for sustainable building in Japan considering the characteristics of the building stock and household energy use behaviour. Energy and housing policies are described in terms of regulations, fiscal instruments and labels, and visualized in the context of a market transformation. The research shows that the Japanese policy has a clear preference for market-based instruments. Thermal regulations are limited to large developments only (over 300 m2) and exclude most of the residential sector. The market transformation is likely to work with appliances, and the Top Runner programme has proved to be an effective policy in making a current market leader a future standard, but the 'scrap and build' housing policy leaves little incentive for energy investments in the building sector; in 24 years the resale value of a Japanese home declines to almost zero and the payback time of most environmental measures exceeds the life-cycle of a building. As the implementation of environmental policies is voluntary, and the insulation levels low, the low heating demand per household seem to be due to different behavioural culture. The research concludes the necessity of introducing mandatory thermal regulations in housing in addition to market based instruments in order to gain further savings in the housing sector. Copyright © 2011 John Wiley & Sons, Ltd and ERP Environment. [ABSTRACT FROM AUTHOR]