Abstract
This paper proposes a new formula to estimate the electricity demand from battery-swapping stations (BSSs) at peak hours, combining parameters of the number of battery-swapping electric scooters (NBSES) and the number of scooters served per BSS. It also presents a novel decision-support analysis for assessing future impact on energy system with an increasing NBSES in Taiwan. The VaR (Value at Risk) values and Monte Carlo method are combined to assess key variables of NBSES and potential benefits. This study finds that the probability for the percentage of operating reserve (OR), R, beyond 6.0 percent is only 86.3% in the past four years. When NBSES reaches 1.28 million, the probability for R beyond 6.0 percent is down to 69.0% and R is 2.9% (95%CI) without considering the storage ability of BSSs. However, R could be higher than 6.0% (95%CI) if considering the storage ability of BSSs.
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