Hydrogen station location optimization based on multiple data sources. (27th March 2020)
- Record Type:
- Journal Article
- Title:
- Hydrogen station location optimization based on multiple data sources. (27th March 2020)
- Main Title:
- Hydrogen station location optimization based on multiple data sources
- Authors:
- Lin, Rongheng
Ye, Zezhou
Guo, Ziyan
Wu, Budan - Abstract:
- Abstract: 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,Abstract: 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. Highlights: Multiple data sources are used for hydrogen station location optimization. Data includes stations network, GIS and economy data from Beijing. The results provide hydrogen station planning solution for Beijing. This research has social significance and economic benefits for hydrogen economics. … (more)
- Is Part Of:
- International journal of hydrogen energy. Volume 45:Number 17(2020)
- Journal:
- International journal of hydrogen energy
- Issue:
- Volume 45:Number 17(2020)
- Issue Display:
- Volume 45, Issue 17 (2020)
- Year:
- 2020
- Volume:
- 45
- Issue:
- 17
- Issue Sort Value:
- 2020-0045-0017-0000
- Page Start:
- 10270
- Page End:
- 10279
- Publication Date:
- 2020-03-27
- Subjects:
- Hydrogen -- Station location -- Data sources -- Optimization
Hydrogen as fuel -- Periodicals
Hydrogène (Combustible) -- Périodiques
Hydrogen as fuel
Periodicals
665.81 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03603199 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ijhydene.2019.10.069 ↗
- Languages:
- English
- ISSNs:
- 0360-3199
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.290000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13488.xml