Many studies and projects have been conducted with the aim of reducing carbon dioxide emissions. One of the possible solutions is Biocoke. As it can be produced from various materials including biomass and has a higher compressive strength than coal coke, it is expected to be a new solid fuel that can help achieve a carbon neutral society. In this study, we looked to its agricultural applications and evaluated the operation stability and the reduction volume of carbon dioxide when Biocoke was used as a substitute for heavy oil to heat a large mango greenhouse. The Biocoke we used was produced from buckwheat hulls. We found that the temperature control inside the greenhouse was good because of Biocoke’s slow combustion characteristic, and therefore the operation stability was great. With regard to carbon dioxide emissions, we could reduce them by 11 ton/year per 10 acres when approximately 63% of annual heavy oil usage (6,882kg) was replaced by Biocoke. The cost analysis on this mango farmer’s case shows that it would be difficult for individual farmers to achieve the practical use of Biocoke with their own funds as the capital investment in Biocoke manufacturing facilities is large at present.

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Short-term load forecasting (STLF) using artificial intelligence (AI) methods has become an active and important research topic with the recent rapid advancement in data processing capabilities of computers．In this paper, we attempted to predict next-day hourly electric loads in Chubu area of Japan using artificial neural networks (ANNs). The model used in this study exploits principal component analysis (PCA) and the selective ensembling (SE) method to achieve a good predictive performance. The effects of changing several hyperparameters, such as the number of hidden layers and neurons, as well as the selection of the input data and the activation function, were tested on the load data obtained from the website of Chubu Electric Power Company. We obtained the following results:
1) With the optimal model configuration, mean absolute percentage error (MAPE) was reduced by 0.19 percentage points,from2.32% to 2.13%.
2) Using relative humidity forecasts as part of the input data to ANN reduced MAPE by 0.34 and 0.19 percentage points in Augustand September, respectively.

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In recent years, energy consumption in residential buildings account for about 40% of global energy consumption and contribute more than 30% of CO₂ emissions. A large proportion of it is used for thermal comfort satisfaction in residential buildings. On the one hand, saving energy only by reducing air conditioning will reduce human thermal comfort level. Therefore, to solve this issue, balancing between energy conservation and thermal comfort is significant. On the other hand, it is possible to estimate human thermal comfort level by analyzing the LF/HF value. Additionally, the heat flow rate between human skin surface and the surrounding air does has correlations with the LF/HF value, which has not been discovered before, this paper shows that there is a possibility to utilize heat flow rate and the LF/HF value to evaluate human thermal comfort level.

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A vehicle fleet stock turnover model was developed to study the impact of vehicle automation and powertrain electrification on light-duty vehicle fleet energy consumption, CO₂ emissions and cost in the case of Japan. 24 vehicle types were considered: four powertrains, internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), battery electric vehicles (BEVs) and fuel cell hybrid electric vehicles (FCHEVs); using two automation levels, no automation (level 0) and full automation (Level 5); available for three vehicle size classes, normal, compact and mini-sized vehicles. In the base scenario, tank to wheel CO₂ emissions can be reduced from 110.3 Mt-CO₂/year to 53.1 Mt-CO₂/year between 2012 and 2050. Diffusion of BEVs has the largest potential for tank to wheel CO₂ emissions reduction, 86.9% compared to the 2050 baseline values; with a net cash flow of 17.4 Billion USD/year. In contrast, diffusion of FCHEVs can reduce tank to wheel CO₂ emissions up to 80.8% by 2050; with a negative cash flow. SDVs diffusion has larger CO₂ emissions reductions in ICEV and HEV scenarios than in BEV and FCHEV scenarios. Capital cost increments due to automation cannot be compensated by energy savings, causing an increment in the net cash flow.

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This paper analyzed Japan’s fusion energy development scenarios by using a global energy systems model considering a combination of uncertainties of future socioeconomic development, CO₂ emission pathways corresponding to the long-term target of the Paris Agreement and future fusion power plants. Fusion power plants will be installed in Japan and could contribute about 20% on average in power sector in the latter half of the century because of the limited-potentials of affordable renewable energies and carbon capture and storage in Japan. The benefit of fusion introduction in Japan is estimated to be about 10 billion US$/yr on average in 2050-2100. Its value increases with reduction of the capital costs of future fusion power plants, lower penetration of fission power plants and deeper decarbonization pathways. When considering unique characteristics of fusion energy development, i.e., long-term and large-scale projects and DEMO as a single step between ITER and a first commercial plant, demonstration and prospect of economic viability under DEMO projects becomes critically important. This systems analysis also suggests that an alternative option of fusion energy which directly produces hydrogen by high-temperature steam electrolysis could become economically attractive.

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This study develops a regionally-disaggregated global energy system model, aiming to assess the role of low-carbon technologies for climate change mitigation. Detailed spatial resolution, totaling 363 nodes, enables the model to explicitly consider the local resource endowments as well as energy and CO₂ transportation infrastructure. Simulation results indicate that energy savings and alternative fuel use—such as hydrogen (H₂) and solid biomass—in the end-use sectors, combined with significant decarbonization of the electricity sector, are the cost-optimal strategy. Most H₂ is locally produced and consumed near demand centers, implying economic challenges for global H₂ trade. CO₂ storage in aquifer plays a crucial role for emissions reduction, significantly affecting global marginal CO₂ abatement cost. If aquifer storage is excluded from the list of mitigation options, renewables and nuclear become more important; international CO₂ trade is also estimated to be cost-efficient to access other CO₂ storage sites, such depleted gas wells, which suggests cooperation opportunities between energy consuming and gasrich countries.

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In this paper, I estimated the price elasticity of residential electricity demand and the change in price elasticity after the Great East Japan earthquake in 2011 for nine regions in Japan using panel data of household income and expenditure survey. The model is simple but I have carefully checked to avoid multicollinearity bias. I obtained the following results. 1) Short-term price elasticities vary from -0.19 (Tokyo) to -0.70 (Hokkaido): 2) Long-term price elasticities vary from -0.25 (Tokyo) to -0.83 (Kansai and Kyushu): 3) Although price elasticity increased after the earthquake, the increase is small and the change has not been sustained.

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