Optimal Operation of Electricity and Hydrogen Integrated System with Fuel Cell Electric Vehicles and Uncertainties

The growth in renewable energies (REs) has created new challenges for balancing supply and demand, and for managing uncertainty in power systems. Integrated energy systems (IESs) based on hydrogen are a promising solution for increasing network resilience. This paper provides a daily optimization framework for electricity and hydrogen integrated system, which fuel cell electric vehicles (FCEV) not only as a consumer, but also as mobile storage resources. For accurate uncertainty modeling, a scenario generation method based on the Copula function has been used to maintain the correlation between random variables (solar radiation, wind speed, load, and energy price). Further, to reduce the computational burden, the scenarios have been reduced with the K-means optimization algorithm. The problem is formulated as mixed integer linear programming (MILP) to simultaneously minimize operating costs and environmental pollution. The numerical results show that implementing demand response reduced the peak-to-valley difference by ۱۶.۶%, ۱۶.۵۹%, and ۲۲.۵%, decreased operational costs by ۱۰.۲%, ۷%, and ۹.۳%, and lowered environmental costs by ۳%, ۱.۵%, and ۴.۴۸% across different seasons.

کلیدواژه ها:

Integrated Energy System ، Fuel cell electric vehicle ، Uncertainty ، Demand Response