Search

As the global energy landscape transitions towards a more sustainable future, hydrogen has emerged as a promising energy carrier due to its potential to decarbonize various sectors. However, the economic competitiveness of hydrogen production by water electrolysis strongly depends on renewable energy source (RES) availability. Thus, it is necessary to overcome the challenges related to the intermittent nature of RESs. This paper presents a comprehensive techno-economic analysis of complementing green hydrogen production with grid electricity. An evaluation model for the levelized cost of hydrogen (LCOH) is proposed, considering both CO2 emissions and the influence of RES fluctuations on electrolyzers. A minimum load restriction is required to avoid crossover gas. Moreover, a new operation strategy is developed for hydrogen production plants to determine optimal bidding in the grid electricity market to minimize the LCOH. We evaluate the feasibility of the proposed approach with a case study based on data from the Kyushu area in Japan. The results show that the proposed method can reduce the LCOH by 11% to 33%, and increase hydrogen productivity by 86% to 140%, without significantly increasing CO2 emission levels. [ABSTRACT FROM AUTHOR]

Floating LiDAR systems (FLSs) may replace conventional offshore met masts, and they have been developed well in Europe. However, before using them in Japan, we must determine whether they demonstrate the same performance under the unique East-Asian meteorological and oceanographic conditions. Therefore, herein, we investigate the performance of FLSs by focusing on the differences among models. Four independent wind datasets from three FLSs were simultaneously verified against a reference met mast and vertical LiDAR at a Japanese site. The data availability was confirmed to vary from 62.7 to 98.0% over the period at 63 m. This was strongly affected by the system availability of the buoy and LiDAR, suggesting that buoy system robustness is key to better campaigns with higher data availability. The 10 min averaged wind speed and direction largely satisfied the Carbon Trust's key performance indicators, with a low sensitivity to wave conditions depending on the buoy shape. The standard deviation of the wind speed and turbulence intensity had poorer accuracy than that of the 10 min averaged statistics because of the wave-induced buoy motion, especially for small buoys. In short, this paper provides an overview of a measurement by FLS in Japan. Also, the unique verification with multiple units suggests the need for a low-motion buoy or motion compensation to improve the measurement accuracy of the turbulence component. [ABSTRACT FROM AUTHOR]

Day-ahead electricity price forecasting (DAEPF) holds critical significance for stakeholders in energy markets, particularly in areas with large amounts of renewable energy sources (RES) integration. In Japan, the proliferation of RES has led to instances wherein day-ahead electricity prices drop to nearly zero JPY/kWh during peak RES production periods, substantially affecting transactions between electricity retailers and consumers. This paper introduces an innovative DAEPF framework employing a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) model designed to predict day-ahead electricity prices in the Kyushu area of Japan. To mitigate the inherent uncertainties associated with neural networks, a novel ensemble learning approach is implemented to bolster the DAEPF model's robustness and prediction accuracy. The CNN–LSTM model is verified to outperform a standalone LSTM model in both prediction accuracy and computation time. Additionally, applying a natural logarithm transformation to the target day-ahead electricity price as a pre-processing technique has proven necessary for higher prediction accuracy. A novel "policy-versus-policy" strategy is proposed to address the prediction problem of the zero prices, halving the computation time of the traditional two-stage method. The efficacy of incorporating a suite of multimodal features: areal day-ahead electricity price, day-ahead system electricity price, areal actual power generation, areal meteorological forecasts, calendar forecasts, alongside the rolling features of areal day-ahead electricity price, as explanatory variables to significantly enhance DAEPF accuracy has been validated. With the full integration of the proposed features, the CNN–LSTM ensemble model achieves its highest accuracy, reaching performance metrics of R 2 , MAE, and RMSE of 0.787, 1.936 JPY/kWh, and 2.630 JPY/kWh, respectively, during the test range from 1 March 2023 to 31 March 2023, underscoring the advantages of a comprehensive, multi-dimensional approach to DAEPF. [ABSTRACT FROM AUTHOR]

As an unconventional clean resource with huge reserves and a wide distribution, natural gas hydrates (NGHs) have good application prospects. However, due to limited understanding and available production technology for NGHs, there is still a large gap between current production tests and commercial exploitation. A breakthrough in reservoir stimulation technologies is key to realizing the industrialization of NGHs in the future. Through a comprehensive summary of hydrate production test cases in Japan and China, this paper highlights the difficulties in the transformation of weakly-consolidated reservoirs. By systematically reviewing the theory and technology of hydrate reservoir transformation and engineering applications, this paper elucidates in detail the technical principles and mechanisms of several available stimulation technologies for weakly-consolidated reservoirs, and assesses the feasibility of their application to increase the production of NGHs. Existing problems and challenges are summarized and future prospects are discussed. Finally, suggestions are put forward for research and development of transformation technology for weakly-consolidated NGHs reservoirs in the future. [ABSTRACT FROM AUTHOR]

This paper studies the distribution of emergency relief for electric vehicles (EVs), which considers energy saving, multi-depot, and vehicle routing problems with time windows, and the named energy saving-oriented multi-depot vehicle routing problem with time windows (ESMDVRPTW). Our aim is to find routes for EVs such that all the shelter demands are fulfilled during their time windows and the total cost traveled by the fleet is minimized. To this end, we formulate the ESMDVRPTW as a mixed-integer linear programming model. Since the post-disaster transportation network contains a large number of vertices and arcs composed of vertices, we propose a two-stage approach to solve the ESMDVRPTW. The first stage is to obtain the minimal travel cost between any two vertices in real-time on a post-disaster transportation network using the proposed Floyd algorithm combined with the neighboring list (Floyd-NL algorithm). In the second stage, we develop the genetic algorithm (GA) incorporating large neighborhood search (GA-LNS), which determines the delivery scheme of shelters. Simulation results of the MDVRPTW benchmark illustrate that the performance of the GA-LNS is better than GA, simulated annealing (SA) and tabu search (TS). Finally, case studies are constructed on two real cases acquired from the OpenStreetMap (OSM) generated by the Quantum Geographic Information System (QGIS) in Ichihara city, Japan, and the test results of case studies show the effectiveness of the proposed two-stage approach. [ABSTRACT FROM AUTHOR]

The Japan Electric Power Exchange (JEPX) provides a platform for the trading of electric energy in a manner similar to more traditional financial markets. As the number of market agents increase, there is an increasing need for effective price-forecasting models. Electricity price data are observed to exhibit periods of relatively stable, i.e., low-magnitude, low-variance prices interspersed with periods of higher prices accompanied by larger uncertainty. The price data time series therefore exhibits a temporal non-stationarity characteristic that is difficult to capture with typical time series modeling frameworks. In this paper, we implement models for the occurrence of price spike events where spikes are defined as observing prices above a predefined threshold set here at 25 JPY/kWh. This value corresponds to about the 90th percentile of observed prices during peak trading periods. The price spikes time series is observed to be rare events that occur in clusters. We therefore propose to model the data as a Hawkes process whereby the occurrence of a spike event increases the probability of observing more spikes in the period immediately following a price spike event. We test two variations of the classical Hawkes model: the first variation models the change in the magnitude of the underlying intensity as a function of the magnitude of the price spike while the second variation models the change in the decay rate of the underlying intensity as a function of the magnitude of the price spike. An analysis of the performance of the models based on the mean absolute error (MAE) of the spike occurrence probability, a weighted accuracy index, and the Matthews correlation coefficient (MCC) metrics shows the effectiveness of the variable magnitude variation of the Hawkes model in generating short-term forecasts of the occurrence of price spike events. The modified Hawkes model especially outperforms other candidate models as the length of the forecasting horizon increases. [ABSTRACT FROM AUTHOR]

After the Fukushima nuclear accident in Japan, whether the structural safety of the nuclear power plant (NPP) can be guaranteed under an earthquake has been of wide concern. Automatic seismic trip systems (ASTS) have been deployed in NPPs. There are generally two units or more double units on the one NPP site, and the vibration energy of the structure can certainly affect its adjacent structures through the soil, and there is energy transfer and conversion between adjacent structures. At present, the distance between two reactors of NPPs of different reactor types is generally 100–200 m (this distance is referring to the distance between the centers of two reactors, which is slightly different for different reactor types). In the past, seismic instruments were used in the ASTS and the setting of shutdown threshold, so the impact of only one unit was considered in the structural analysis of NPPs, and the interaction of two reactors through site conditions was not considered. In addition, as the site conditions of NPPs become more and more complex, it is necessary to consider the impact of one reactor structure on another reactor structure through the soil on the same site under an earthquake. In order to analyze the influence of structure–soil–structure interaction (SSSI), a three-dimensional refined finite element model of NPPs is established in this paper. The soil–structure interaction (SSI) is considered by using viscoelastic boundary. The seismic responses of different positions of the raft foundation and NPP structure, under the conditions of considering SSI effect (one reactor) and SSSI effect (two reactors), are compared. The influence of SSSI effect on the seismic responses of the raft foundation and NPP structure is revealed. It is proposed that SSSI effect should be reasonably considered according to the site conditions for the structural analysis of NPPs for the NPP ASTS. [ABSTRACT FROM AUTHOR]

Energy is the prerequisite for social and economic development of a community and country. In Japan, national government is promoting small hydropower (SHP) through a renewable energy policy by providing a high FIT price of 34 yen (≒0.32 US$/kWh) on energy generated from an SHP of less than 200 kW. Until now, the energy generation was controlled by national government agencies, but now independent power generation businesses are growing at the local community level in rural Japan. For the future growth of SHP, it is necessary to make electricity generation at the local community level. Therefore, these local communities will install and manage their renewable electricity by themselves. It will help to make the community self-sustainable and independent from the national government, and at the same time, it will also lead them to achieve the Sustainable Developments Goals (SDGs) target from community-based action. This paper aimed to discuss an SHP development business model in which local community will become the business owner of the SHP. It means "of the community, by the community and for the community". The community identifies their renewable energy potential and needs, they borrow money from the financial organization or banks, install the power plant and do necessary maintenance and management by themselves. The revenue earned by selling electricity is used to repay the loan, and the rest is used for community development directly (such as local roads construction, agriculture land improvements, community hall maintenance, waterways maintenance, welfare, etc.). This paper also discussed a community-based 50 kW SHP installed in Miyazaki prefecture of Japan as a case study. This SHP is one of the best examples of a community ownership model (Community-based business model). A detailed explanation from planning to investment has been discussed. The local community is getting approximately 112,000 USD per year by selling the electricity, and 162-ton CO2 is estimated to decrease yearly, which will support the achievement of SDGs. Finally, installing this kind of SHP in remote areas will provide managerial skills to the local community directly, plant operation knowledge, and education to local students. Local communities learn the problem-solving skills, which lead them to solve the local problem on a community level by themselves. [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]

In this paper, methane hydrate R&D in Japan was examined in the context of Japan's evolving energy policies. Methane hydrates have been studied extensively in Japanese national R&D programs since 1993, with the goal of utilizing them as an energy resource. Currently, the Research Consortium for Methane Hydrate Resources in Japan (MH 21) is in the third phase of a project that began in early 2002. Based on publicly available reports and other publications, and presentations made at the ten International Workshops for Methane Hydrate Research and Development, we have attempted to provide a timeline and a succinct summary of the major technical accomplishments of MH 21 during project Phases 1, 2, and 3. [ABSTRACT FROM AUTHOR]

This study presents a stress testing operation conducted using a wireline formation tester in a newly discovered gas hydrate prospect located offshore in Japan. The campaign, which spanned from December 2021 to January 2022, involved drilling a well using logging-while-drilling technology. Subsequently, wireline formation testing and stress testing were successfully conducted at three different depths within a gas hydrate-concentrated zone. The testing was accomplished in a single riserless descent, with the primary goal of obtaining crucial data such as mobility, formation pressure, and fracture gradient for one of the prospects. This operation marked the first stress testing job performed with dual packers in an open water and deepwater environment specifically for gas hydrate reservoirs. The study also provides a comprehensive interpretation of the data gathered during the operation. Moreover, it evaluates various properties such as formation mobility, formation pressure, initial breakdown pressure, closure pressure, fracture propagation pressure, and instantaneous shut-in pressure. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine a productive efficiency index that incorporates two new production factors of sustainability—an environmental variable as an undesirable output and a well-being indicator as a desirable output—for 12 years of data from 2007 to 2018 pertaining to 47 prefectures in Japan. This study proposes a combination of a new data envelopment analysis (DEA) intermediate approach with the DEA super-efficiency model to measure the integrated productive efficiency. The approach incorporates CO2 emissions and a well-being indicator into the conventional productivity index. A three-stage analysis is conducted by sequentially adding new factors, CO2 emissions, and a well-being indicator. We also conduct a club convergence analysis of the productive efficiency and observe how clubs are formed, what their characteristics are, and how the efficiency changes over time. Through these approaches, we examine the practicality of the new efficiency measure and discuss regional policy implications. We found that higher labor productivity and carbon productivity in major industries caused increased productive efficiency. Adding sustainability factors to the conventional production factors in efficiency measurement widened the efficiency gap among prefectures. [ABSTRACT FROM AUTHOR]

To reduce CO2 emissions in the residential and transportation sectors, distributed energy technologies, such as photovoltaic power generation (PV), stationary storage batteries (SBs), battery electric vehicles (BEVs), and vehicle-to-home (V2H) systems, are expected to be introduced. The objective of this study was to analyze the impact of the installed capacity of PV and SB, the type of vehicle, and their combination on the economic and environmental performance of the total energy consumption of residences and vehicles. Thus, this study developed a model to optimize the technological configuration of residential energy systems, including various vehicle types and driving patterns. The simulation results showed that it is more economically and environmentally efficient to install a BEV and a V2H system in households with longer parking times at the residence and to install an SB in addition to these technologies in households with shorter parking times at the residence. Furthermore, comparing a gasoline vehicle and an SB, the most economical combination, with a BEV and a V2H system and with a BEV, a V2H system, and an SB, estimated the carbon tax rate necessary for cost equivalence. The result indicated that the carbon tax rate needs to be increased from its current level. [ABSTRACT FROM AUTHOR]

Load forecasting is an essential task in the operation management of a power system. Electric power companies utilize short-term load forecasting (STLF) technology to make reasonable power generation plans. A forecasting model with low prediction errors helps reduce operating costs and risks for the operators. In recent years, machine learning has become one of the most popular technologies for load forecasting. In this paper, a two-stage STLF model based on long short-term memory (LSTM) and multilayer perceptron (MLP), which improves the forecasting accuracy over the entire time horizon, is proposed. In the first stage, a sequence-to-sequence (seq2seq) architecture, which can handle a multi-sequence of input to extract more features of historical data than that of single sequence, is used to make multistep predictions. In the second stage, the MLP is used for residual modification by perceiving other information that the LSTM cannot. To construct the model, we collected the electrical load, calendar, and meteorological records of Kanto region in Japan for four years. Unlike other LSTM-based hybrid architectures, the proposed model uses two independent neural networks instead of making the neural network deeper by concatenating a series of LSTM cells and convolutional neural networks (CNNs). Therefore, the proposed model is easy to be trained and more interpretable. The seq2seq module performs well in the first few hours of the predictions. The MLP inherits the advantage of the seq2seq module and improves the results by feeding artificially selected features both from historical data and information of the target day. Compared to the LSTM-AM model and single MLP model, the mean absolute percentage error (MAPE) of the proposed model decreases from 2.82% and 2.65% to 2%, respectively. The results demonstrate that the MLP helps improve the prediction accuracy of seq2seq module and the proposed model achieves better performance than other popular models. In addition, this paper also reveals the reason why the MLP achieves the improvement. [ABSTRACT FROM AUTHOR]

The growing demand for electricity, driven by factors such as the shift to carbon neutrality and economic growth, is a challenge shared by South Korea and Japan. South Korea, a peninsula nation, and Japan, an island country, which are both heavily dependent on foreign energy sources and have manufacturing-based industrial structures, are actively working to secure stable power supplies for their economic development. This article carries out a quantitative analysis of the roles of the South Korean and Japanese electric power sectors (EPSs) in their respective economies, seeking to identify differences and generate actionable insights for decision making and policy formulation. Utilizing the input–output (IO) technique with the latest available data, the analysis includes a demand-side model, a supply-side model, and a price-side model to examine various effects of the EPSs. The key findings reveal differences in the production-inducing, value-added creation, and job-creation effects between the two countries, highlighting operational disparities in their electricity sectors. Additionally, South Korea exhibits higher wage-inducing, supply shortage, and price-side effects than Japan, because of its public enterprise-oriented high-wage structure and a substantial manufacturing sector. These quantitative results provide valuable reference material for future government decisions and policy development in the EPS and emphasize the significant role and impact of the power sector in both countries. [ABSTRACT FROM AUTHOR]

Ground source heat pump systems are one of the renewable energy heat utilization technologies that can reduce the energy for HVAC and hot water supplies and consequently mitigate the progression of global warming. On the other hand, the development of ground heat exchangers that can be installed in small buildings with low installation costs is an important challenge for increasing the installation number of ground source heat pump systems in Japan. This study proposes H-shaped PC pile ground heat exchangers to reduce installation costs. The installation test and installation cost estimation of H-shaped PC pile ground heat exchangers showed that installation costs could be reduced to less than half compared to the conventional borehole double U-tube ground heat exchanger. The coefficient of heat extraction/injection of H-shaped PC pile ground heat exchangers was evaluated as 2.2–2.4 W/(m K) from the results of actual measurements during the heating and cooling operation of the GSHP system, and this was slightly high compared to the borehole single U-tube ground heat exchanger. In addition, the GSHP system with an 8 by 8 m long H-shaped PC pile ground heat exchanger could supply adequate heating output for the heating load of the residential house and operate with an SCOP of more than 3.0. Finally, the authors have confirmed that the GSHP system with H-shaped PC pile ground heat exchangers can reduce installation costs by 40% or more while maintaining the same running cost compared to conventional GSHP systems. [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]

Climate change and global warming are significantly affected by carbon emissions that arise from the burning of fossil fuels, specifically coal, oil, and gas. Accurate prices are essential for the purposes of measuring, capturing, storing, and trading in carbon emissions at regional, national, and international levels, especially as carbon emissions can be taxed appropriately when the price is known and widely accepted. This paper uses a novel Capital (K), Labor (L), Energy (E) and Materials (M) (or KLEM) production function approach to calculate the latent carbon emission prices, where carbon emission is the output and capital (K), labor (L), energy (E) (or electricity), and materials (M) are the inputs for the production process. The variables K, L, and M are essentially fixed on a daily or monthly basis, whereas E can be changed more frequently, such as daily or monthly, so that changes in carbon emissions depend on changes in E. If prices are assumed to depend on the average cost pricing, the prices of carbon emissions and energy may be approximated by an energy production model with a constant factor of proportionality, so that carbon emission prices are a function of energy prices. Using this novel modeling approach, this paper estimates the carbon emission prices for Japan using seasonally adjusted and unadjusted monthly data on the volumes of carbon emissions and energy, as well as energy prices, from December 2008 to April 2018. The econometric models show that, as sources of electricity, the logarithms of coal and oil, though not Liquefied Natural Gas (LNG,) are statistically significant in explaining the logarithm of carbon emissions, with oil being more significant than coal. The models generally displayed a high power in predicting the latent prices of carbon emissions. The usefulness of the empirical findings suggest that the methodology can also be applied for other countries where carbon emission prices are latent. [ABSTRACT FROM AUTHOR]

The present paper suggests fuel consumption modeling for HDVs based on the code from the Japanese Ministry of the Environment. Two interpolation models (inversed distance weighted (IDW) and Hermite) and three types of fuel efficiency maps (coarse, medium, and dense) were adopted to determine the most appropriate combination for further studies. Finally, sensitivity analysis studies were conducted to determine which parameters greatly impact the fuel efficiency prediction results for HDVs. While vitiating each parameter at specific percentages (± 1%, ± 3%, ± 5%, ± 10%), the change rate of the fuel efficiency results was analyzed, and the main factors affecting fuel efficiency were summarized. As a result, the Japanese transformation algorithm program showed good agreement with slightly increased prediction accuracy for the fuel efficiency test results when applying the Hermite interpolation method compared to IDW interpolation. The prediction accuracy of fuel efficiency remained unchanged regardless of the chosen fuel efficiency map data density. According to the sensitivity analysis study, three parameters (fuel consumption map data, driving force, and gross vehicle weight) have the greatest impact on fuel efficiency (± 5% to ± 10% changes). [ABSTRACT FROM AUTHOR]

Managing energy-producing companies as well as managing the entire energy sector in the light of legal and environmental requirements requires a new vision, mission, and strategy. The paper analyses the strategies of energy enterprises. It is not enough now to produce energy and deliver it at appropriate, acceptable prices to consumers; it must be generated with the least negative impact on the environment. To achieve that plan, companies should cut the carbon intensity of their products by 20% by 2030, 45% by 2035, and 100% by 2050, using a baseline of 2016. To compared to 1990 levels, the greenhouse gas emission reduction target for 2030 should be increased to 55%. Bioenergy will represent 18% of total final energy consumption in 2050. Additionally, this requires the development of a long-term strategy that can force companies to completely reorganize their production or start a new operation and activities. A low-cost strategy or a competition strategy are insufficient, and it is necessary to look for new strategies that combine adaptation to the requirements of the external environment with the use of innovative solutions. The article analyzes the possibilities of implementing an innovative strategy based on biomass, especially bamboo biomass. The reduction in CO2 emissions of bamboo, taking into account life cycle emissions, can reach up to 85%. The novelty is to show the possibility of producing electricity by a large-scale power plant solely based on bamboo biomass on the example of a power plant located in the Tokushima prefecture, Japan. Another novelty is the fact that this article draws attention to the problem of burning bamboo in a power plant. The problem is that, as a result of burning bamboo, the clinker settles quite quickly. The study analyzes the selected ingredients for co-firing, which improve the combustion parameters of bamboo biomass (e.g., blended 20% bamboo with 80% pine or 30% bamboo with 70% tree bark). The importance of this research lies in the fact that it shows new innovative solutions in the energy sector that will help to achieve emission reductions. In addition, the article proposes to use eco-innovations and pay attention to eco-efficiency. Such solutions are an opportunity for ecological development through the use of bamboo as a fuel, which is classified as a renewable energy source by power plants. [ABSTRACT FROM AUTHOR]

Because a significant portion of the topography in Japan is characterized by steep, complex terrain, which results in a complex spatial distribution of wind speed, great care is necessary for selecting a site for the construction of Wind Turbine Generators (WTGs). We have developed a CFD model for unsteady flow called Research Institute for Applied Mechanics, Kyushu University, COMputational Prediction of Airflow over Complex Terrain (RIAM-COMPACT®). The RIAM-COMPACT® CFD model is based on Large-Eddy Simulation (LES) technique. The computational domain of RIAM-COMPACT® can extend from several meters to several kilometers, and RIAM-COMPACT® can predict airflow and gas diffusion over complex terrains with high accuracy. First, the present paper proposes a technique for evaluating the deployment location of WTGs. Next, wind simulation of an actual wind farm was executed using the high resolution elevation data. As a result, an appropriate point and an inappropriate point for locating WTGs were shown based on the numerical results obtained. This cause was found to be a topographical irregularity in front of WTGs. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) energy trading is gaining attention as a technology to effectively handle already existing distributed energy resources (DER). In order to manage a large number of DER, it is necessary to increase the number of P2P energy trading participants. For that, designing incentives for participants to engage in P2P energy trading is important. This paper describes a user-centric cooperative mechanism that enhances user participation in P2P energy trading. The key components of this incentive for participants to engage in P2P energy trading are described and evaluated in this study. The goal of the proposal is to make it possible to conduct economic transactions while reflecting the preferences of the traders in the ordering process, making it possible to conduct transactions with minimal effort. As a case study, the Higashi-Fuji demonstration experiment conducted in Japan verified the proposed mechanism. In this experiment, 19 households and 9 plugin hybrid vehicles (PHV) were evaluated. As a result, the study confirmed that prosumers were able to sell their surplus electricity, and consumers were able to preferentially purchase renewable energy when it was available. In addition, those trades were made economically. All trades were made automatically, and this efficiency allowed the users to continue using the P2P energy trading. [ABSTRACT FROM AUTHOR]

Japan faces the challenge of reducing its greenhouse gas emissions while maintaining economic growth and energy security. This study aims to analyze the potential impact on Japan's economy and industries if the country achieves its 2030 greenhouse gas reduction target, implements a power mix plan to meet that target, and simultaneously pursues the Growth Strategy Council's proposal for a power mix plan to achieve carbon neutrality by 2050. The study also investigates an alternative carbon neutrality pathway without nuclear power. The research question is whether these low-carbon policies can lead to both economic growth and decarbonization in Japan. To address this question, the study uses the E3ME-FTT macroeconomic model with endogenous technology diffusion to simulate different policy scenarios and assess their economic and environmental impacts. The results indicate that by 2050, Japan could meet its carbon neutrality target, and at the same time, the GDP could increase by approximately 3% compared with the baseline scenario, with or without nuclear power. This growth is expected to occur in several sectors due to increased demand for decarbonization-related investments and strong private consumption. Additionally, the overall economy is expected to benefit from the increased demand for low-carbon and decarbonization-related investments, reduced costs associated with renewable energy generation, and an improved trade balance resulting from a significant decrease in fossil fuel imports. [ABSTRACT FROM AUTHOR]

A field survey of indoor environmental measurements and questionnaires on thermal sensation, overall comfort, and behaviors was conducted in four office buildings in Japan by visiting each office every month over a duration of more than a year during the coronavirus disease 2019 (COVID-19) pandemic. The indoor environment was measured concurrently. We obtained 1047 votes from office workers in their 20s to 60s. The regression and Griffiths' methods were used to calculate the indoor comfort temperature. A logistic regression analysis was used to develop the occupant behavior model. Over 70% of the occupants found the indoor environment comfortable at a mean comfort temperature of 23.2 to 25.9 °C. Gender differences were observed in thermal sensation and overall comfort, but a gender difference was observed only in the cooling mode for the indoor comfort temperature. An adaptive model was developed for the office buildings in Nagasaki city to predict the indoor comfort temperature from the outdoor air temperature. The proportions of heating, cooling, and fan usage can be predicted from the outdoor air temperature using a logistic regression analysis. The adaptive model and occupant behavior model are useful for the indoor temperature control of the existing buildings and thermal simulation of the new building design. [ABSTRACT FROM AUTHOR]

Backflashover rate (BFR) is strongly dependent on the cumulative peak current distribution (CCD) adopted in the calculations. An original aspect of the present work is that such dependence is simultaneously assessed in estimating the probability of the critical current being exceeded as well as in the annual number of flashes to the line. An IEEE brochure recommends that the distribution values that characterize the atmospheric characteristic of the region under study as accurately as possible be used. The objective of this article is to evaluate the impact of the use of different CCDs, related to several measurements carried out around the world, in the estimation of the lightning performance of transmission lines (TLs). Structures of 138, 230 and 500 kV were analyzed. In the simulations, representative curves of lightning associated with measurements taken at Monte San Salvatore (MSS), Morro do Cachimbo (MCS) and TLs in Japan (TLJ) were considered. The distributions recommended by the IEEE and by the CIGRE and the distributions of Berger obtained from MSS, MCS and TLJ were considered. The presented results indicate differences of up to 100% between the considered work distributions and the IEEE one for certain values of tower footing impedance. [ABSTRACT FROM AUTHOR]

Hydrogen is currently receiving significant attention and investment as a key enabler of defossilised global energy systems. Many believe this will eventually result in the international trade of hydrogen as a commodity from countries with significant renewable energy resources, for example New Zealand and Australia, to net energy importing countries including Japan and Korea. Japan has, since 2014, been actively exploring the components of the necessary supply chains, including the assessment of different hydrogen carriers. Public/private partnerships have invested in demonstration projects to assess the comparative merits of liquid hydrogen, ammonia, and organic carriers. On the supply side, significant projects have been proposed in Australia while the impending closure of New Zealand's Tiwai Point aluminium smelter at the end of 2024 may provide an opportunity for green hydrogen production. However, it is also evident that the transition to a hydrogen economy will take some years and confidence around the timing of supply and demand capacity is essential for new energy infrastructure investment. This paper reviews the expected development of an export market to Japan and concludes that large scale imports are unlikely before the late 2020s. Comparative evaluation of the energy efficiency of various hydrogen carriers concludes that it is too early to call a winner, but that ammonia has key advantages as a fungible commodity today, while liquid hydrogen has the potential to be a more efficient energy carrier. Ultimately it will be the delivered cost of hydrogen that will determine which carriers are used, and while energy efficiency is a key metric, there are other considerations such as infrastructure availability, and capital and operating costs. [ABSTRACT FROM AUTHOR]

In order to reduce global greenhouse gas emissions, renewable energy technologies such as wind power and solar photovoltaic power systems have recently become more widespread. However, Japan as a nation faces high reliance on imported fossil fuels for electricity generation despite having great potential for further renewable energy development. The focus of this study examines untapped geographical locations in Japan's northern most prefecture, Hokkaido, that possess large wind power potential. The possibility of exploiting this potential for the purpose of producing green hydrogen is explored. In particular, its integration with a year-round conversion of Kraft lignin into bio-oil from nearby paper pulp mills through a near critical water depolymerization process is examined. The proposed bio-oil and aromatic chemical production, as well as the process' economics are calculated based upon the total available Kraft lignin in Hokkaido, including the magnitude of wind power capacity that would be required for producing the necessary hydrogen for such a large-scale process. Green hydrogen integration with other processes in Japan and in other regions is also discussed. Finally, the potential benefits and challenges are outlined from an energy policy point-of-view. [ABSTRACT FROM AUTHOR]

The iron and steel industry is a large emitter of CO2 globally. This is especially true for the iron and steel industries in China, Japan, and Korea due to their production volumes and the prevalence of carbon-based steel production. With few low-carbon and commercially available alternatives, the iron and steel industry is truly a hard-to-abate sector. Each of the countries of interest have committed to a net-zero future involving the mitigation of emissions from steel production. However, few studies have investigated the means by which to achieve decarbonization beyond the inclusion of price signalling policies (e.g., carbon tax or emission trading schemes). Here, we use E3ME-FTT:Steel to simulate technology diffusion in the ISI under several policy environments and we investigate the likely impacts on the wider economy. The results show that penalizing carbon intensive processes can incentivize a transition towards scrap recycling, but it is relatively unsuccessful in aiding the uptake of low carbon primary steelmaking. A combination of support and penalizing policies can achieve deep decarbonisation (>80% emission reduction compared with the baseline). Mitigating the emissions in the iron and steel industry can lead to economic benefits in terms of GDP (China: +0.8%; Japan: +1.3%; Korea: +0.1%), and employment (Japan: +0.7%; Korea: +0.3%) with China, where job losses in the coal sector would negate job gains elsewhere, as the exception. [ABSTRACT FROM AUTHOR]

Due to the inherent uncertainty of wind conditions as well as the price unpredictability in the competitive electricity market, wind power producers are exposed to the risk of concurrent fluctuations in both price and volume. Therefore, it is imperative to develop strategies to effectively stabilize their revenues, or cash flows, when trading wind power output in the electricity market. In light of this context, we present a novel endeavor to construct multivariate derivatives for mitigating the risk of fluctuating cash flows that are associated with trading wind power generation in electricity markets. Our approach involves leveraging nonparametric techniques to identify optimal payoff structures or compute the positions of derivatives with fine granularity, utilizing multiple underlying indexes including spot electricity price, area-wide wind power production index, and local wind conditions. These derivatives, referred to as mixed derivatives, offer advantages in terms of hedge effectiveness and contracting efficiency. Notably, we develop a methodology to enhance the hedge effects by modeling multivariate functions of wind speed and wind direction, incorporating periodicity constraints on wind direction via tensor product spline functions. By conducting an empirical analysis using data from Japan, we elucidate the extent to which the hedge effectiveness is improved by constructing mixed derivatives from various perspectives. Furthermore, we compare the hedge performance between high-granular (hourly) and low-granular (daily) formulations, revealing the advantages of utilizing a high-granular hedging approach. [ABSTRACT FROM AUTHOR]

With growing concern about risks related to energy security around the world, the development of hydrogen cooperation between India and Japan has become very important to ensure the economic security of the two countries and to deepen economic cooperation. This report covers both public and private initiatives in the hydrogen area in both countries and visualizes the high potential and potential areas where both countries could cooperate in the hydrogen area, as well as the challenges that are necessary for cooperation. The following four factors are strong incentives for India and Japan to deepen cooperation in the hydrogen field: (1) India has a high potential hydrogen supply capacity, (2) India is very active in implementing hydrogen in society, (3) Japan is already conducting R&D in areas of high interest to India and (4) Japan will need to import hydrogen from other countries in the future. The issues of (1) cost visualization, including transportation costs, (2) harmonization of regulations, (3) harmonization of promotion measures between the two countries, (4) definition of "green hydrogen," and (5) protection of intellectual property are main challenges to be overcome. Thus, disclosures of necessary data for cost visualization of hydrogen transportation, further inter-governmental cooperations between India and Japan, and facilitation of the discussions on hydrogen among various stakes are key actions for materializing various joint hydrogen projects between both countries. [ABSTRACT FROM AUTHOR]

Indoor solar-heating systems that use ventilated roofs have drawn attention in recent years. The effectiveness and efficiency of such air-heating systems vary depending on the design and operation methods. In Japan, by introducing outside air into a ventilated roof cavity and circulating the air indoors, systems that simultaneously obtain ventilation, solar heating, and heat-storage effects have been actively developed. The conventional systems intake a large volume of outside air to increase the solar heat collection effect. However, there is a risk of heat loss and over-drying when a large amount of cold dry air during winter is introduced. In this paper, plans are presented for improving these solar heating and heat-storage effects by preventing over-drying using indoor air circulation via ventilated cavities in the roof and indoor wall. By comparing the results of the proposed system with those of the conventional system via numerical simulation, the heating load is found to be reduced by 50% or more by circulating indoor air to the ventilated roof and storing the heat in the indoor wall. Moreover, an increased relative humidity of approximately 10% was confirmed by reducing the intrusion of the outside air and keeping the moisture indoors. [ABSTRACT FROM AUTHOR]

In this paper, various modern power engines developed by the American, Japanese, and European automobile industries will be compared. Specific data, including the efficiency, emission rate of nitrogen oxides (NOx), fuel consumption, and electronic vehicle technology, will be developed. Since the first invention of the automobile engine in the late 19th century, companies came up with unique innovations, including its structure, control systems, and additional mechanical installations to improve efficiency and reduce emissions. Numerous companies, including Ford, Toyota, and Mercedes-Benz, compete in the automobile industry to improve their engine's efficiency and emission rates to create a clean environment. In addition, each country has its regulations on emission rates and automobile structure. Therefore, to meet these regulations, the structure and the system of the engines vary between companies in different countries. A variety of variable valve timing (VVT) systems, which is a mechanical part installed in the engine, are being developed by several companies. The VVT controls the opening and closing of the air inlet valve and the exhaust valve, which improves the reduction of fuel consumption and thermal efficiency. Furthermore, changing the engine structure is also another method that automobile companies are developing. Changing the engine's shape can improve the vehicle's performance (e.g., the engine vibration while running, the power output, and the smoothness of driving). Due to the emissions caused by petrol and diesel engines, the electrified vehicles have been developing to achieve a cleaner environment. This includes battery electric vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, and fuel cell electric vehicles. By comparing these features in the engine, it is possible to understand what the companies in the US, Japan, and the European countries are working on to improve their engines and provide a clean environment. [ABSTRACT FROM AUTHOR]

A residential ground-source heat pump system often requires a long payback time to recover the capital cost. Long-term uncertainty in such a system's performance increases as the climate changes. This study compares 20-years hourly heating/cooling demands of a typical residence in the present (2000–2020) and in the future (2076–2095) for two locations in Japan. This study also calculated soil temperatures as heat sources through 1D heat-transfer simulation based on the A1B climate scenario in the Intergovernmental Panel on Climate Change's Special Report. System performance and simple payback times were compared in one cold and one warm city in Japan (Sapporo and Tokyo, respectively). Soil temperatures at a middle depth of a borehole heat exchanger were predicted to increase in the future by ~1 °C, with insignificant effects on a borehole heat exchanger. Seasonal performance factors increased in Sapporo because thermal demands would be kept even in the future, but decreased in Tokyo, which has a higher ratio of the energy used in operating the system in cooling mode compared with its small heating demand. The simple payback time was estimated at 16.2 and >20 years in Sapporo and Tokyo, respectively, both in the present and future, with the constant energy prices. If oil and gas prices doubled, the payback time would be halved in Sapporo to 8.4 years but remain around 20 years or more in Tokyo. [ABSTRACT FROM AUTHOR]

While international trade drives countries' economic growth and promotes employment, it also has some environmental impact. To investigate the impact of trade on carbon emissions and employment, this study performs a detailed decomposition and measurement of embodied carbon emissions and employment in value-added trade between China, Japan, and Korea from 2007–2019. The current study established that, while China's trade with Japan and Korea created many domestic jobs, it also resulted in significant domestic carbon emissions. While Japan and Korea's trade with China reduced carbon emissions, employment in their own countries was reduced and replaced by employment in China. At the value chain route level, trade among the three countries through each value chain route either achieves employment promotion at the cost of increased carbon emissions or promotes domestic emissions reduction at the cost of employment loss. However, it is worth noting that, when trade between Japan and Korea was conducted through simple GVCs (route 2), it not only helped reduce Japan's carbon emissions, but also effectively promoted employment. This is the ideal trade route. The results of this study can provide useful reference information for developing countries such as China, to achieve sustainable economic growth, carbon emission reduction, and employment promotion in the context of trade globalization. [ABSTRACT FROM AUTHOR]

Combined heat and power (CHP) is crucial for promoting thorough energy conservation and advanced energy use, aimed toward greenhouse gas reduction. Solid oxide fuel cell (SOFC)-CHP is expected to be introduced as a measure against global warming and has been the focus of attention, and this study examined the effects of its introduction. This study introduces a linear programming evaluation model that can simulate optimized facility configuration and operation, based on the power supply and demand. The novelty of the proposed model is the consideration of geographic characteristics, which influences parameters dependent on gas transportation infrastructure and electricity. A sensitivity analysis was conducted considering the number of units and location of SOFC-CHP introductions in the National Capital Region of Japan. As a result, it was predicted that SOFC-CHP would likely begin to be introduced in areas where there is a large shadow price difference between electricity and gas at each node. The total power generation will decrease, as transmission and distribution losses decrease, owing to the diffusion of SOFC-CHP installed in the vicinity of demand. The widespread use of SOFC-CHP is an economically feasible CO2 emissions reduction pathway. These results will help assess the introduction of various distributed power sources in addition to SOFC-CHP to reduce CO2 emissions. [ABSTRACT FROM AUTHOR]

Forests cover two-thirds of Japan's land area, and woody biomass is attracting attention as one of the most promising renewable energy sources in the country. The Feed-in Tariff (FIT) Act came into effect in 2012, and since then, woody biomass power generation has spread rapidly. Gasification power generation, which can generate electricity on a relatively small scale, has attracted a lot of attention. However, the technical issues of this technology remain poorly defined. This paper aims to clarify the problems of woody biomass gasification power generation in Japan, specifically on the challenges of improving energy utilization rate, the problem of controlling the moisture content, and the different performance of power generation facilities that uses different tree species. We also describe the technological development of a 2 MW updraft reactor for gasification and bio-oil coproduction to improve the energy utilization rate. The lower heating value of bio-oil, which was obtained in the experiment, was found to be about 70% of A-fuel oil. Among the results, the importance of controlling the moisture content of wood chips is identified from the measurement evaluation of a 0.36 MW-scale downdraft gasifier's actual operation. We discuss the effects of tree species variation and ash on gasification power generation based on the results of pyrolysis analysis, industry analysis for each tree species. These results indicate the necessity of building a system specifically suited to Japan's climate and forestry industry to allow woody biomass gasification power generation to become widespread in Japan. [ABSTRACT FROM AUTHOR]

This paper aims at the optimal designing of a stand-alone microgrid (PV/wind/battery/diesel) system, which can be utilized to meet the demand load requirements of a small residential area in Kasuga City, Fukuoka. The simulation part is developed to estimate the electrical power generated by each component, taking into account the variation of the weather parameters, such as wind, solar irradiation, and ambient temperature. The optimal system design is then based on the Particle Swarm Optimization (PSO) method to find the optimal configuration of the proposed system, using the least-cost perspective approach. [ABSTRACT FROM AUTHOR]

Considering the heat capacity inside vertical spiral ground heat exchanger (VSGHEX) in the simulation is one of the most noteworthy challenge to design the ground source heat pump (GSHP) system with VSGHEXs. In this paper, a new simulation model for VSGHEXs is developed by combining the ICS model with the CaRM. The developed simulation model can consider the heat capacity inside VSGHEX and provide dynamic calculation with high speed and appropriate precision. In order to apply the CaRM, the equivalent length was introduced. Then, the equivalent length was approximated by comparing the results of the CaRM and the numerical calculation. In addition, the calculation model of the VSGHEX was integrated into the design and simulation tool for the GSHP system. The accuracy of the tool was verified by comparing with the measurements. The error between supply temperatures of the measurements and calculation is approximately 2 °C at the maximum. Finally, assuming GSHP systems with VSGHEXs, whose spiral diameter was 500 mm and depth was 4 m, were installed in residential houses in Japan, the required numbers of VSGHEXs were estimated. The results showed a strong correlation between the total heating or cooling load and the required number. Therefore, the required number can be estimated by using the simplified approximate equation. [ABSTRACT FROM AUTHOR]

The number of photovoltaic (PV) power systems being installed worldwide has been increasing. This has resulted in maintenance of an adequate balance between demand and supply becoming a great concern for power system operators. Forecasting PV power outputs is a promising countermeasure that has been garnering significant interest. Conventional methods for achieving this often use learning methods, such as neural networks and support vector regression. In contrast, this paper proposes a short-term power-forecasting method for geographically distributed PV systems that uses only their previous output power data. In the proposed method, first, the ratio of the power generation output to the maximum power output value for each observation instance in a designated period for each PV system at a certain date and time is obtained. Then, the future geographical distribution of the ratio is predicted from the temporal change (motion) of the preceding distribution. Finally, the predicted ratio is reconverted into the power output to perform short-term power forecasting. The results of total PV output power prediction in the Kanto area of Japan indicate that the proposed method has an average mean absolute percentage error of 4.23% and root mean square error of 0.69 kW, which verifies its efficacy. [ABSTRACT FROM AUTHOR]

CO2 emissions associated with hydrogen production can be reduced replacing steam methane reforming with electrolysis using renewable electricity with a trade-off of increasing energy consumption, water consumption and cost. In this research, a linear programming optimization model of a hydrogen production system that considers simultaneously energy consumption, water consumption, CO2 emissions and cost on a cradle-to-gate basis was developed. The model was used to evaluate the impact of CO2 intensity on the optimum design of a hydrogen production system for Japan considering different stakeholders' priorities. Hydrogen is produced using steam methane reforming and electrolysis. Electricity sources include grid, wind, solar photovoltaic, geothermal and hydro. Independent of the stakeholders' priorities, steam methane reforming dominates hydrogen production for cradle-to-gate CO2 intensities larger than 9 kg CO2/kg H2, while electrolysis using renewable electricity dominates for lower cradle-to-gate CO2 intensities. Reducing the cradle-to-gate CO2 intensity increases energy consumption, water consumption and specific cost of hydrogen production. For a cradle-to-gate CO2 intensity of 0 kg CO2/kg H2, the specific cost of hydrogen production varies between 8.81 and 13.6 USD/kg H2; higher than the specific cost of hydrogen production targeted by the Japanese government in 2030 of 30 JPY/Nm3, 3.19 USD/kg H2. [ABSTRACT FROM AUTHOR]

Comfort temperature is important to investigate because the chosen office indoor temperatures affect the energy used in a building, and a thermally comfortable environment makes the occupants be more productive. The effects of temperature on comfort are broadly recognized for thermal comfort. Japanese office buildings are well equipped with air-conditioning systems to improve the thermal comfort of the occupants. The main objectives of this research were to compare the winter comfort temperature in mixed mode (MM) and heating, ventilation and air-conditioning (HVAC) office buildings and to investigate the relationship between the comfort temperature and the indoor air temperature. This study measured the thermal environmental conditions of the office buildings and surveyed the thermal comfort of the occupants. The field survey was conducted during winter in seven office buildings located in the Aichi prefecture of Japan. In total, 4466 subjective votes were collected from 46 occupants. The result suggested that the occupants were found to be more satisfied with the thermal environment of MM buildings than that of HVAC office buildings. Overall, 95% of comfort temperatures were in the range 22~28 °C in MM and HVAC buildings, which were higher than the indoor temperature of 20 °C recommended by the Japanese government. The comfort temperature was highly correlated to the indoor air temperature of the MM buildings than to that of HVAC buildings. This indicated that the occupants were more adapted towards the given thermal environment of MM buildings. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative hydrogen-based hybrid renewable energy system (HRES), which can be used to provide electricity, heat, hydrogen, and water to the small community in remote areas. The HRES introduced in this study is based on the integration of solar power generation, hydrogen generation from supercritical water gasification (SCWG) of wet biomass feedstock, hydrogen generation from solar water electrolysis, and a fuel cell to convert hydrogen to electricity and heat. The wet biomass feedstock contains aqueous sludge, kitchen waste, and organic wastewater. A simulation model is designed and used to investigate the control strategy for the hydrogen and electricity management through detailed size estimation of the system to meet the load requirements of a selected household area, including ten detached houses in a subject district around the Shinchi station located in Shinchi-machi, Fukushima prefecture, Japan. As indicated by results, the proposed HRES can generate about 47.3 MWh of electricity and about 2.6 ton of hydrogen per annum, using the annual wet biomass consumption of 98 tons, with a Levelized Cost of Energy (electricity and heat) of the system at 0.38 $/kWh. The implementation of the proposed HRES in the selected residential area has GHG emissions reduction potential of about 21 tons of CO2-eq per year. [ABSTRACT FROM AUTHOR]

The mass introduction of variable renewable energies, including wind and solar photovoltaic, leads to additional costs caused by the intermittency. Many recent studies have addressed these "integration costs," and proposed novel metrics that replace the traditional metric known as the levelized cost of electricity (LCOE). However, the policy relevance of those metrics remains unclear. In this study, the author investigates and re-defines the concept of system LCOE, referring to prior studies, and proposes concrete methods to estimate them. Average system LCOE allocates the integration cost to each power source, dividing that by the adjusted power output. Marginal system LCOE revises the concept of system LCOE and value-adjusted LCOE proposed by prior studies, to be clearer and more policy-relevant. These metrics are also applied to Japan's power sector in 2050, suggesting the necessity of aiming for a "well-balanced energy mix" in future power systems with decarbonised power sources. [ABSTRACT FROM AUTHOR]

The clean hydrogen in the prioritized value chain platform could provide energy incentives and reduce environmental impacts. In the current study, strengths, weaknesses, opportunities, and threats (SWOT) analysis has been successfully applied to the clean hydrogen value chain in different sectors to determine Japan's clean hydrogen value chain's strengths, weaknesses, opportunities, and threats as a case study. Japan was chosen as a case study since we believe that it is the only pioneer country in that chain with a national strategy, investments, and current projects, which make it unique in this way. The analyses include evaluations of clean energy development, power supply chains, regional energy planning, and renewable energy development, including the internal and external elements that may influence the growth of the hydrogen economy in Japan. The ability of Japan to produce and use large quantities of clean hydrogen at a price that is competitive with fossil fuels is critical to the country's future success. The implementation of an efficient carbon tax and carbon pricing is also necessary for cost parity. There will be an increasing demand for global policy coordination and inter-industry cooperation. The results obtained from this research will be a suitable model for other countries to be aware of the strengths, weaknesses, opportunities, and threats in this field in order to make proper decisions according to their infrastructures, potentials, economies, and socio-political states in that field. [ABSTRACT FROM AUTHOR]

Hydrogen fuel cell vehicles can complement other electric vehicle technologies as a zero-emission technology and contribute to global efforts to achieve the emission reduction targets. This article spotlights the current deployment status of fuel cells in road transport. For this purpose, data collection was performed by the Advanced Fuel Cells Technology Collaboration Programme. Moreover, the available incentives for purchasing a fuel cell vehicle in different countries were reviewed and future perspectives summarized. Based on the collected information, the development trends in the last five years were analyzed and possible further trends that could see the realization of the defined goals derived. The number of registered vehicles was estimated to be 51,437 units, with South Korea leading the market, with 90% of the vehicles being concentrated in four countries. A total of 729 hydrogen refueling stations were in operation, with Japan having the highest number of these. The analysis results clearly indicate a very positive development trend for fuel cell vehicles and hydrogen refueling stations in 2021, with the highest number of new vehicles and stations in a single year, paralleling the year's overall economic recovery. Yet, a more ambitious ramp-up in the coming years is required to achieve the set targets. [ABSTRACT FROM AUTHOR]

Smart buildings that utilize innovative technologies such as artificial intelligence (AI), the internet of things (IoT), and cloud computing to improve comfort and reduce energy waste are gaining popularity. Smart buildings comprise a range of sensors to measure real-time indoor environment variables essential for the heating, ventilation, and air conditioning (HVAC) system control strategies. For accuracy and smooth operation, current HVAC system control strategies require multiple sensors to capture the indoor environment variables. However, using too many sensors creates an extensive network that is costly and complex to maintain. Our proposed research solves the mentioned problem by implementing a machine-learning algorithm to estimate unmeasured variables utilizing a limited number of sensors. Using a six-month data set collected from a three-story smart building in Japan, several extreme gradient boosting (XGBoost) models were designed and trained to estimate unmeasured room temperature, relative humidity, and CO2 concentrations. Our models accurately estimated temperature, humidity, and CO2 concentration under various case studies with an average root mean squared error (RMSE) of 0.3 degrees, 2.6%, and 26.25 ppm, respectively. Obtained results show an accurate estimation of indoor environment measurements that is applicable for optimal HVAC system control in smart buildings with a reduced number of required sensors. [ABSTRACT FROM AUTHOR]

The conversion of biomass to olefin by employing gasification has recently gained the attention of the petrochemical sector, and syngas composition is a keystone during the evaluation of process design. Process simulation software is a preferred evaluation tool that employs stoichiometric and kinetic approaches. Despite the available literature, the estimation errors of these simulation methods have scarcely been contrasted. This study compares the errors of stoichiometric and kinetic models by simulating a downdraft steam gasifier in PRO/II. The quantitative examination identifies the model that best predicts the composition of products for the gasification of Japanese wood waste. The simulation adopts reaction mechanisms, flowsheet topology, reactions parameters, and component properties reported in the literature. The results of previous studies are used to validate the models in a comparison of the syngas composition and yield of products. The models are used to reproduce gasification at temperatures of 600∼900 °C and steam-to-biomass mass ratios of 0∼4. Both models reproduce experimental results more accurately for changes in the steam-to-biomass mass ratio than for temperature variations. The kinetic model is more accurate for predicting composition and yields, having global errors of 3.91%-mol/mol and 8.16%-g/gBM, respectively, whereas the simple stoichiometric model has an error of 7.96%-mol/mol and 16.21%-g/gBM. [ABSTRACT FROM AUTHOR]

Windows are among building components that have the strongest effect on thermal load. They play a significant role in heat loss in buildings because they usually have a largely higher thermal conductance than other components of the building envelope. Although many studies have highlighted the relevance of heat transfer through frames and aimed to improve their thermal performance, poorly insulated aluminum frames (thermal conductivity of aluminum is 160 W/m·K, while that of polyvinyl chloride [PVC] is 0.17 W/m·K) are still in use in Japan. Therefore, the U-values of different window frames were calculated, and annual thermal loads were calculated according to the window configurations, including the frame, glazing, and cavity. We focused on standard residential buildings in Japan with a total floor area of 120.6 m2 (two-story building), and the number of newly built houses and the application rate of window configurations in 2019 were surveyed to estimate the CO2 emissions by regions. CO2 emissions were reduced by approximately 3.98–6.58% with the application of PVC frames. Furthermore, CO2 emissions were converted into the amount of CO2 gas absorbed by cedar trees, which cover nearly 18% of the total land area of Japan. In conclusion, analogous to the amount of CO2 gas absorbed by cedar trees, the absorption effect was equivalent to 327,743–564,416 cedar trees. Changing the window frame material can facilitate a significant energy-saving effect as a considerable amount of energy is saved, especially at a city scale. [ABSTRACT FROM AUTHOR]

Carbon pricing, such as a carbon tax, is an invisible hand that leads to the construction of a sustainable low-carbon society, and precise analysis of the impact of carbon pricing on each sector of the economy is indispensable for its design. In this study, an equilibrium price model based on the 2015 input-output table was used for the analysis of next-generation energy systems (2015 IONGES) and the effect of the introduction of a carbon tax on the price of the industrial sector was assessed. Based on the existing energy-related tax system in Japan, the introduction of a carbon tax is regarded as an increase in the tax for global-warming countermeasures (TGWC) in the petroleum and coal tax (PCT). While existing energy-related taxes are designed to place a relatively heavy burden on the transportation sector, tax reform of the petroleum and coal tax has a relatively large effect on raising prices in energy-conversion and energy-intensive sectors. As a result, the reform of the energy-related tax may promote the introduction of energy-saving technology and decarbonization technology, both in the transportation sector and in a wider range of sectors, and may work to correct the unfairness of the tax burden between sectors. [ABSTRACT FROM AUTHOR]

There was an unprecedented growth of SHP (small hydropower) in Japan during recent years because the government has provided a high FIT (USD 0.32/kWh) for SHP development projects of less than 200 kW. The public and private sectors are committed to harnessing this natural energy to achieve the renewable energy goal as well as to improve local communities social and economic conditions. This paper will discuss about renewable energy initiatives by a food corporation enterprise (FCOOP) based in Fukuoka prefecture of Japan to reduce their net carbon emissions. A detailed approach for social enterprises-based SHP development has been discussed which will be a role model concept for other social enterprises in Japan and in the world that are willing to reduce CO2 emissions. Also, this kind of project connects urban stake holders with local community where resources are available and it leads to development of the local community living standards. As a demonstrated example, a case study of a 20 kW SHP installed in Japan by a FCOOP has been discussed. [ABSTRACT FROM AUTHOR]