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Multi-objective and multi-period hydrogen refueling station location problem
Affiliation:1. Laboratoire de Génie Chimique, UMR 5503 CNRS/INP/UPS, Université de Toulouse, Toulouse, France;2. Departamento de Sistemas, Universidad Autónoma Metropolitana Azcapotzalco, Mexico City, Mexico;1. Laboratory for Urban Complexity and Sustainability, University of Nottingham, Nottingham NG7 2RB, United Kingdom;2. Kent Business School, University of Kent, Canterbury, Kent CT2 7PE, United Kingdom;3. Southampton Business School, University of Southampton, Southampton SO17 1BJ, United Kingdom
Abstract:Creating a distribution network and establishing refueling stations arises as an important problem in order to meet the refueling needs of hydrogen fuel cell vehicles. In this study, a multi-objective and multi-period hydrogen refueling station location problem that can take into account long-term planning decisions is proposed. Firstly, single objective mathematical models are proposed for the problem by addressing the cost, risk and population convergence objectives. Afterwards, a goal programming model is proposed and the results that will arise when three objectives are taken into consideration at the same time are examined. A risk analysis approach applied for each location alternative is considered in order to handle risk concerns about the hydrogen refueling station settlement. A case study is conducted in Adana, one of the crowded cities in Turkey, to determine the long-term location network plan. Covered population, operational risk and earthquake risks are used as input of the risk analysis method. The case study results show that the goal programming model covers the area with 77 hydrogen refueling stations by different types and capacities during the years from 2020 to 2030. In addition, a computational study is carried out with different alternative scenarios (different number of consumption nodes and all parameters in the model). The computational study results show that the highest deviations from the optimal solution on the model are observed in the distances between consumption nodes and targeted service area parameters which affect about 50% of absolute deviations on average. According to results, the proposed approach selects the station location suitable for the expected changes over the years.
Keywords:Hydrogen refueling station location  Multi-period set-covering problem  Goal programming approach  Risk-based settlements
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