Multi-Period Optimization of the Refuelling Infrastructure for Alternative Fuel Vehicles

Alternative fuel vehicles (AFV) are gaining increasing attention as a mean to reduce greenhouse gas (GHG) emissions. One of the most critical barriers to the widespread adoption of AFVs is the lack of sufficient refuelling infrastructure. Although it is expected, that an adequate number of alternative fuel stations (AFS) will eventually be constructed, due to the high resource intensity of infrastructure development, an optimal step-by-step construction plan is needed. For such a plan to be actionable, it is necessary, that the underlying model considers realistic station sizes and budgetary limitations. This bachelor thesis addresses this issue by introducing a new formulation of the flow-refuelling location model, that combines multi-periodicity and node capacity restrictions (MP-NC FRLM). For this purpose, the models of Capar and Kluschke have been extended, and the pre-generation process of sets and variables has been improved. The thesis furthermore adapts and applies the two evaluation concepts Value of the Multi-Period Solution (VMPS) and Value of Multi-Period Planning (VMPP) to assess the model's relative additional benefit over static counterparts. Besides, several hypotheses about potential drivers of the two evaluation concepts VMPS and VMPP have been made within the scope of a numerical experiment, to help central planners identify situations, where the additional complexity of a dynamic model would be worthwhile. While the MP-NC FRLM has proven to provide additional benefit over static counterparts, it comes at the cost of a higher solving time. The main contributor to the higher solving is hereby the incorporation of a time module.