Power, Control, and Data Processing Systems

Power, Control, and Data Processing Systems

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

Document Type : Original Research

Authors
Mohsen Bahmani
Sina Ahhmadi
Mehrdad Setayesh Nazar
Department of Electrical Engineering Shahid Beheshti University Tehran, Iran
10.30511/pcdp.2026.2084569.1063
Abstract
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 16.6%, 16.59%, and 22.5%, decreased operational costs by 10.2%, 7%, and 9.3%, and lowered environmental costs by 3%, 1.5%, and 4.48% across different seasons.
Keywords
Integrated energy system
Fuel cell electric vehicle
Uncertainty
Demand response
Subjects
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Power, Control, and Data Processing Systems
Volume 3, Issue 2
Spring 2026
Pages 35-45

  • Receive Date 04 February 2026
  • Revise Date 12 May 2026
  • Accept Date 12 May 2026
  • First Publish Date 12 May 2026
  • Publish Date 01 June 2026