Multi-objective Spatiotemporal Optimization of Transportation and Power Management by using Multiple Electric Vehicles in Nanogrid Networks

For achieving a low-carbon society and providing stable energy supply to local areas, we propose a distributed energy system in which multiple small grids are installed in a distributed manner in an area. Multiple electric vehicles located in the area are used as mobile batteries for power leveling between grids and used as regional transportation. To construct this system, it is necessary to provide practical solutions in accordance with the needs in various areas by adjusting the balance between optimization of power management and transportation, which are in a trade-off relationship, while dealing with uncertainties such as climate change and time-varying transportation demand in a short time. In this paper, we propose a multi-objective spatiotemporal optimization algorithm for solving the above problem. We compared the performance of the proposed algorithm with a vehicle-routing-problem solver of Google OR-Tools, demonstrating that the transportation rate increased by 13% and sum of power excess and shortage in grids decreased by 87%. The proposed algorithm can also adjust the balance between optimizations of transportation and electricity-management, suggesting that it can be applied in various areas.