Introduction Recently, the large-scale installation of renewable energy is required to prevent global warming problem. Especially, the production cost of solar cell has drastically decreased recently. To install large-scale unstable power sources on renewable energy, the management of the gap between electricity demand and supply is a key issue. Thus, large-scale energy storage technologies have to progress to compensate the gap. As an energy storage, chemical energy of hydrogen is a promising candidate. Particularly in urban area, both “global hydrogen” and “local hydrogen” are required to supply sufficient energy to their huge energy demand. “Global hydrogen” is produced from low-cost primary energy globally and is transported for demand with a certain cost. “Local hydrogen” is produced by distributed energy system and is directly supplied without transportation. In the paper, we proposed a cost-competitive distributed energy system with the “local hydrogen” energy storage system. We analyzed the variation of total system cost by installing electrolysis cell (EC), fuel cell (FC) and secondary battery to compensate the gap due to electricity supply from large-scale solar cells (SC). We also proposed the appropriate SC arrangement for a middle size of distributed energy system. Method We evaluated the total system cost on the basis of real data from smart energy control system “Ene-Swallow”, developed by our research group, which manages the megawatt-scale distributed power sources in Tokyo Institute of Technology, Tokyo. The system has 1400 kW-SC, 100 kW-FC, 70 kW-gas engine and 100 kWh-lithium ion battery to manage the 10000 kW-scale electricity demand, which is suitable as a model for a middle-scale society with distributed power sources. The 650 kW-SC, which is almost half of total capacity of SC, is installed on the building (shown in Fig1) located in Tokyo. This building nearly achieves electricity self-sufficiency by the SC, 100 kW-FC and 70kW-gas engine. The building is covered with the “envelope of solar cells” (445 kW at the south wall, 40 kW at the west wall and 165 kW on the roof), where the maximum altitude in winter solstice is 31°. Global solar radiation in summer and winter are 15 MJ/m2 and 8 MJ/m2, respectively. Average temperature in summer and winter are 25°C and 5°C, respectively. In the location, the SCs on the building generates maximum electric power in winter because about 68% of SCs is installed at the south walls. The SC arrangement of the building has much smaller seasonal variation than typical arrangement on the roof to get better matching with the larger energy demands in winter. We constructed the energy system model to analyze the distributed energy system with electrochemical hydrogen energy storage and large-scale SC. In our model, the energy system with SC, alkaline EC, solid oxide FC, compressor, hydrogen tank and battery was assumed. Three hourly data from Apr/1/2016 to Mar/31/2017 were used (power generation from 750 kW-SC on the roofs, 650kW-SC on the building and electricity demand in the area). Based on these data, imaginary set of SC installation was assumed, where total amount of power generation from SC is equivalent to the electricity demand. Fig2 shows the energy flow in the model. In the daytime, the surplus electricity supplied from SC was assumed to be used for the production of hydrogen or battery charge. If the capacity of each device is not sufficient, the surplus electricity was assumed to be curtailed because it is hard to sell it in the future scenario with “large amount of solar energy”. In the night, the electricity to satisfy the demand was assumed to be generated by battery or FC. When the electricity supply is not enough, electricity was assumed to be purchased from an electrical grid. We carried out the energy balance simulation in the model by setting the capacities and technological parameters of devices. Finally, we analyzed the total system cost on the basis of the simulation. The analysis was carried out with the three cases of technology parameters of devices: (1) current (2015), (2) reduced SC price and (3) reduced all device prices (Table1). Result From the series of analysis, the total system cost can be reduced by installing the appropriate-scale hydrogen energy storage in the future. To achieve self-sufficiency ratio 100%, on the other hand, hydrogen tank cost drastically increased because its capacity got larger to absorb seasonal variation in power generation from SC. Controlling seasonal variation through SC arrangement can reduce the hydrogen tank cost. The cost-competitive system was proposed with the combination of hydrogen energy storage and SC arrangement. Figure 1