Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
In terms of electric ship energy requirement in navigation, the ship charging station location is especially important. In this paper, a multi-period ship charging station location optimization model is pro-posed to make location decision in overall, from initial possible station sites chosen to the capacity determination for the final location sites. In the first phase, from the perspective of external environment, find out all possible ship charging station candidate sites through the feasible analyze. In the second phase, taking the ship charging demands into consideration, the final ship charging station sites can be selected among the candidate sites based on backup coverage model. In the last phase, regarding the cost of construction and service capability for different grade as the main factor in capacity determination, the optimal capacity of each final ship charging station are determined by means of optimization method. Finally, an example of Yanqi lake in China is used to verify the validity of the proposed methodology. The reasonable location of charging station could ensure the electric energy supply and avoid congestion caused by ship charging gathering. The model can be easily generalized to other problems regarding facility allocation based on user demand.
Rocznik
Tom
Strony
323--327
Opis fizyczny
Bibliogr. 11 poz., rys., tab.
Twórcy
autor
- Intelligent Transportation System Research Center(ITSC) ,Wuhan University of Technology, Wuhan, China
- National Engineering Research Center for Water Transport Safety(WTSC), Wuhan, China
autor
- Intelligent Transportation System Research Center(ITSC) ,Wuhan University of Technology, Wuhan, China
- National Engineering Research Center for Water Transport Safety(WTSC), Wuhan, China
autor
- Intelligent Transportation System Research Center(ITSC) ,Wuhan University of Technology, Wuhan, China
- National Engineering Research Center for Water Transport Safety(WTSC), Wuhan, China
Bibliografia
- [1] Hogan K, ReVelle C. Concepts and applications of backup coverage. Management Science 1986;32:1434–44
- [2] Araz C, Selim H, Ozkarahan I. A fuzzy multi‐objective covering‐based vehicle location model for emergency services[J]. Computers & Operations Research, 2007, 34(3):705‐726.
- [3] Zhu Z H, Gao Z Y, Zheng J F, et al. Charging station location problem of plug‐in electric vehicles[J]. Journal of Transport Geography, 2016, 52:11‐22.
- [4] Xiang Y, Liu J, Li R, et al. Economic planning of electric vehicle charging stations considering traffic constraints and load profile templates[J]. Applied Energy, 2016, 178:647‐659.
- [5] Liu Zhipeng, Wen Fushuan, Xue Yusheng, et al. The Optimal Location and Constant Capacity of Electric Vehicle Charging Station [J]. Automation of Electric Power Systems, 2012, 36(3):54‐59.
- [6] Hamaide B, Albers H J, Busby G. Backup coverage models in nature reserve site selection with spatial spread risk heterogeneity[J]. Socio‐Economic Planning Sciences, 2014, 48(2):158‐167.
- [7] Cruz‐Zambrano M, Corchero C, Igualada‐Gonzalez L, et al. Optimal location of fast charging stations in Barcelona: A flow‐capturing approach[C]// International Conference on the European Energy Market. IEEE, 2013:1‐6.
- [8] Yang S, Wu M, Yao X, et al. Load Modeling and Identification Based on Ant Colony Algorithms for EV Charging Stations[J]. IEEE Transactions on Power Systems, 2015, 30(4):1997‐2003.
- [9] Wang Sunwei,Zhou Ronggui,Zhang Gaoqiang,Li Wei,et al.A Method of optimizing the locations of Flooding Emergency Resource Stations: Journal of Transport Information & Safety, 2015.33(5):119‐127.
- [10] Zhang J, Yan X, Zhang D,Haugen S,Yang X. “Safety management performance assessment for Maritime Safety Administration (MSA) by using generalized belief rule base methodology”[J]. Safety Science, 2014, 63(4):157‐167.
- [11] Fu S, Yan X, Zhang D,C Li,E Zio. Framework for the quantitative assessment of the risk of leakage from LNG‐fueled vessels by an event tree‐CFD[J]. Journal of Loss Prevention in the Process Industries, 2016, 43,pp.42–52.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-aa350977-130c-4fb1-85a6-6b2a92772a4e