Inter-regional and inter-sectoral considerations are important for more effective use of renewable energies. We have developed an input-output table for a next generation energy system (IONGES) that includes new sectors related to renewable energies. In this study, we expand the national IONGES to include the inter-regional table. The inter-regional IONGES has two sets of extended tables: extended renewable energy sectors for 2005 (Ex2005, actual data of 2005) and extended renewable energy sectors for 2030 (Ex2030, hypothetical data for 2030). More than half of renewable energy potential is located in eastern Japan. The potential of residential solar power is large in regions that have metropolitan areas. Some renewable energies induce more output and create more jobs than conventional electricity, but at the same time such renewable energies are more expensive than conventional electricity. When we evaluate the effects of introducing renewable energies in each region, we must consider both types of effects. We calculated the induced production in every sector of every region based on one million JPY of consumption in each region. Comparing the induced electricity (which is interpreted as the electricity fee embodied in consumption) of Ex2030 and that of Ex2005, the inducements are largely decreased in those regions where the composition ratio of wind power is high. We calculated the supposed CO2 reductions attributed to a decline in conventional electricity induced by consumption. It seems that the effective use of residential solar power in metropolitan areas and the effective use of locality-specific renewable energies in rural areas are important for CO2 reductions. We calculated cost-push effects following the abolition of FIT. There are significant effects on regions where the composition ratio of solar power is high. Analyses using inter-regional input-output tables will be a useful analytical tool for effective use of renewable energy facilities that have already been installed, as well as for future designs of smart energy systems.
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