A pricing-based location model for deploying a hydrogen fueling station network. (21st September 2020) - Thiel, Daniel
Abstract: We propose an innovative two-step Pricing-Based Location strategy for the rollout of new hydrogen fueling stations. A first model maximizes the profit of a new station with a price p ∗ which corresponds to a design capacity supplying a given market share ( n ∗ customers). According to these findings and with the objective of deploying an extensive network, a second model searches for a suitable location as remote as possible from existing competitors, but as close as possible to just n ∗ demand locations. This problem is solved by an agent-based model integrating the Particle Swarm Optimization metaheuristic and a Geographic Information System representing the geospatial distribution of customer demand. We apply this model to the city of Paris by locating additional stations across the city one by one to supply a growing captive fleet of taxis and other transport operators in the future. Highlights: Location of new hydrogen fueling stations in Paris from 2020. Agent-based model integrating particle swarm optimization and GIS. A price optimizing behavior lead to the hydrogen station network being re-organized. The model searches for a station location to supply an optimal market share.