Hydrogen station location optimization based on multiple data sources

摘要

A hydrogen station is one that fills or stores the hydrogen, which is critical to the commercial development of hydrogen energy and fuel cell vehicle industry. Therefore, its location planning becomes an important issue. Similar to the electric vehicle (EV) charging station's planning, several factors are considered including the location, the demand of the fuel, the driving distance, etc. In this paper, multiple data sources are applied to the site selection model, including the existing petrol-refueling station network data, geographic information system (GIS) data, population data and regional economic data. Based on the operation of the genetic algorithm, combined with the idea of the greedy algorithm and the annealing algorithm, we propose a multi-algorithm hybrid solution, which not only can avoid local optimal, but also can converge quickly. On the basis of the site selection scheme of the hydrogen station in California, we have optimized the location scheme in Beijing. Finally, we present the feasibility proposals for hydrogen station location in Beijing, including the appropriate number of hydrogen stations in different regions, the reasonable coverage distance of hydrogen stations, etc. Due to the huge development prospects for hydrogen energy and the urgent need to reduce the construction cost of hydrogen stations in China, this research can quickly optimize the location of the hydrogen station and further explore potential mathematical relationships, which has certain social significance and economic benefits. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.