Risk-based scheduling of an off-grid hybrid electricity/hydrogen/gas/ refueling station powered by renewable energy

Xiao Xu, Weihao Hu, Wen Liu, Daojuan Wang, Qi Huang, Rui Huang, Zhe Chen

Research output: Contribution to journalJournal articlepeer-review


Making full use of renewable energy to supply clean energy for transportation sector can effectively reduce environmental pollution and realize the sustainable development. A hybrid electricity/hydrogen/gas/refueling station (EHGRS) powered by renewable energy in an off-grid region is proposed. It supplies electricity for electric vehicles (EVs), and hydrogen for hydrogen fuel cell vehicles (HFCVs) and produces natural gas for natural gas vehicles (NGVs) simultaneously. A hybrid stochastic/information gap decision theory (IGDT) optimization method is employed for the scheduling problem of the hybrid EHGRS in an uncertain environment. The uncertainties of wind and photovoltaic (PV) power is modelled via scenarios, while the uncertainties of the demands of EVs, HFCVs and NGVs, depending on human behavior, are formulated with a bi-level IGDT method without knowing the accurate distribution information. The work aims to find the maximum expected profits of the hybrid EHGRS. Two different scheduling strategies, i.e. risk-averse and risk-seeker, with two contradictory attitudes under the uncertain demands are proposed. Results indicate that 1) The proposed hybrid EHGRS can simultaneously provide different fuels to EVs, HFCVs and NGVs. 2) Under the same condition, the profit for the risk-averse scheduling is decreased and the risk-seeker scheduling is increased, compared to the results obtained by the pure stochastic optimization.
Original languageEnglish
JournalJournal of Cleaner Production
Publication statusPublished - 2021


  • Information gap decision theory
  • Stochastic optimization
  • risk-averse and risk-seeker
  • SchedulingRenewable energy
  • Hybrid electricity/hydrogen/gas/ refueling station


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