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The purpose of this paper is to make quantitative analysis on the effect of demand side optimization, especially on the reduction of CO2 emission realized by optimizing charging and discharging schedule of battery electric vehicles (BEVs), or by optimized Vehicle-to-Grid (V2G) operations. BEV optimization model is incorporated into the existing electricity supply-demand model to study how the introduction of BEVs make differences on a power system operation, composition of power generation and CO2 emission on the power supply side. Three cases of BEV operation are studied, 1) dumb charging without optimization, 2) optimization of charging, 3) optimization of charging and discharging with Vehicle-to-Grid operations. Analysis is also made on how de-carbonization of the supply side will make differences by studying the case of 2035 and 2040 in addition to 2030, the target year of Japan’s new national energy plan.

This paper reports the development of the road traffic simulator to analyze the effectiveness of the rapid charge station (ST). We employ Digital Map 2500 (Spatial Data Framework) as the basic database for the map model in the traffic simulator. The EV behavior is defined based on the traffic database of Road Traffic Census. The road map model in this traffic simulation corresponds to the road map of 10 cities, where the area and population are 2600 km₂ and about three million people, respectively. We found the 17 STs are enough to keep the averaged travel length for a household vehicle in Japan. This result suggests the area responsible for a ST is about 150 km₂ per ST (i.e. one ST in the area of about 12 km square).