Abstract:
As eco-friendly vehicles, such as electric vehicles (EVs) and hydrogen vehicles (HVs), become more popular, the heavy charging loads due to EV charging stations (EVCSs) a...Show MoreMetadata
Abstract:
As eco-friendly vehicles, such as electric vehicles (EVs) and hydrogen vehicles (HVs), become more popular, the heavy charging loads due to EV charging stations (EVCSs) and HV charging stations (HVCSs) cause additional challenges in the main grid. In response, the idea of renewable energy source-assisted charging stations, which can be used as cost-effective EV and HV charging stations (EHVCSs), has attracted attention. This paper proposes a framework for the stochastic optimal operation of EHVCSs to reduce the amount of power they need to purchase from the main grid and to maximize their revenues through means such as charging fees and hydrogen energy portfolio standard (HPS) sales. To enhance the profitability of HEVCS, the EHVCS can sell hydrogen into the HPS market by generating power through fuel cells installed in HVCSs. The optimization problem is formulated as a nonlinear programming problem given the nature of AC power flow constraints, which is non-convex. Therefore, the problem is transformed into a convex problem by convexifying the problem using second-order conic programming relaxation.
Published in: 2023 IEEE Power & Energy Society General Meeting (PESGM)
Date of Conference: 16-20 July 2023
Date Added to IEEE Xplore: 25 September 2023
ISBN Information: