Green Certificate-Driven Photovoltaic Promotion in Distribution Networks Hosting Hydrogen Fueling Stations for Future Sustainable Transportation: A Risk-Adjusted Dominance Analysis

Xiaoqiang GUO, Xiao LI, F. Adil Hussein Mohammed, Farhan A. Alenizi, Kasim Kadhim Alasedi, Karrar Shareef Mohsen, Ali Alsaalamy, Walid El-Shafai, Khusniddin Fakhriddinovich Uktamov, Abolfazl Mehbodniya, Ali Bostani

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1 Scopus citations

Abstract

The growing number of hydrogen vehicles (HVs) has necessitated the development of hydrogen fueling stations (HFSs) to meet the hydrogen demand. This development will target environmental concerns related to electricity generation as HFSs consume power to convert electricity into hydrogen. This study focuses on the optimal risk-aware scheduling problem of a distributed network highly penetrated with photovoltaic (PV) resources. The model addresses the optimal operation of HFs under time-of-use, demand response, and multi-market mechanisms with an expanded role for PV generation under the green certificate (GCT) approach. This brings further environmental and economic benefits, as there is a growing global emphasis on the shift to a low-carbon economy. However, the uncertainties arising from PV operation, HVs’ demand, electricity load, and market prices, potentially affect the decision-maker's ability under the risky conditions. Though second-order stochastic dominance (STD) is implemented for risk management. Results show that applying the GCT method increases 5% (from 0.52 to 0.61 MW) of renewable generation and reduces 23% (300 kg) of CO2 emissions. As the conservativity of decision-makers enhances, 10% of further operation costs are imposed on the system. Results indicate that next to curbing CO2 emissions, the flexibility and robustness of the system can be improved.

Original languageEnglish
Article number104911
JournalSustainable Cities and Society
Volume99
DOIs
StatePublished - Dec 2023

Keywords

  • Demand response program
  • Green certificate
  • Hydrogen fueling station
  • Hydrogen vehicle
  • second-order stochastic dominance

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