Optimization of Scooter-sharing Services Using a Solar-charging Based Real-Time Shareability Network

Despite the recent implementation of policies that promote penetration of renewable energy, the sustainable development of cities still presents many challenges. Most recently, shared electric scooters have been deployed as a sustainable transportation solution. Compared to vehicles powered by internal combustion engines, scooters require only a fraction of energy for transportation and represent an alternative that can mitigate congestion and reduce total emissions. However, scooters have limited battery capacity and require frequent charging which is often performed manually, increasing costs and questioning the viability of shared scooters systems. A possible way to tackle these problems is by installing solar charging platforms at scooter stations, which can extend the cruising distance continuously during the riding gaps and avoid the difficulty in bridging with the power grid. In this paper, we create a real-time scooter shareability network that maximizes the opportunities for sharing and minimizes the total trip distance, constrained by the size of the fleet and by real-time estimation of battery life. Hourly electricity generated by photovoltaic modules installed at scooter stations is then computed through an accurate three-dimensional model of solar irradiation in cities, and the origin-destination matrix of scooter-sharing trips nearby the stations is spatially clustered for solar charging. The study performed over four weeks of scooter-sharing trips in the city-state of Singapore suggests that we only need 24%-67% of the fleet size to support almost all the real trips with almost 98% reduction of charging-driven trips when PV modules of 1-3 m2 with a transition efficiency of 20% are deployed at each station. The studied system also supports over 90% of the demands for at least 3 consecutive days with minimal solar irradiation, hinting to the resilience of the proposed system also in other cities across the world with more variation in daily sunshine.