Sizing Optimization of a Charging Station Based on the Multi-scale Current Profile and Particle Swarm Optimization: Application to Power-assisted Bikes

The development of power-assisted bikes (ebike) is of growing interest because of their economic and environmental advantages. The present work deals with the sizing optimization of a charging station for ebike based on particle swarm optimization. It is based on the consumption profile of ebike batteries, solar and wind power, installation, replacement and maintenance costs of components. In a first step, the consumption profile of the ebike batteries is determined using the second order non-linear electrothermal model. Then, the solar and wind data over one year are used to determine the availability of energy at the implementation site of the charging station. Finally, the cost is defined as an objective function, taking into account the constraints on the number of solar photovoltaic panels, the number of wind turbines, the number of storage batteries and the annual charging demand. The context of a charging station to be implemented in the Polytech Annecy campus in France is studied. The results show that the particle swarm optimization allows a cost reduction of around 56.04% compared to a sizing without optimization.