IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v140y2017ip1p11-17.html
   My bibliography  Save this article

Decision-making of compressed natural gas station siting for public transportation: Integration of multi-objective optimization, fuzzy evaluating, and radar charting

Author

Listed:
  • Li, Shunxi
  • Su, Bowen
  • St-Pierre, David L.
  • Sui, Pang-Chieh
  • Zhang, Guofang
  • Xiao, Jinsheng

Abstract

Application of compressed natural gas in public transportation has attracted environmental and social attentions worldwide for natural gas' low air pollutants emission, low cost, and availability. Constructing a suitable compressed natural gas network for public transportation in a city has thus become an important topic for the theory and practice of applying the compressed natural gas, which is considered as a key measure to solve the energy crisis and city congestion. The present paper proposed an integrated decision-making process of compressed natural gas siting for public transportation based on the method of multi-objective optimization, fuzzy evaluating, and radar charting. Multi-objective optimization is used to find the initial feasible solution under the city's requirement in economic, availability, safety and so on. Fuzzy evaluation then provides the criteria of decision-making. Radar charting presents a clear vision of all the candidate solutions for decision-making based on the different feature of the city condition. To illustrate the proposed process, the present paper takes the city of Wuhan, China as the case study.

Suggested Citation

  • Li, Shunxi & Su, Bowen & St-Pierre, David L. & Sui, Pang-Chieh & Zhang, Guofang & Xiao, Jinsheng, 2017. "Decision-making of compressed natural gas station siting for public transportation: Integration of multi-objective optimization, fuzzy evaluating, and radar charting," Energy, Elsevier, vol. 140(P1), pages 11-17.
    • Handle: RePEc:eee:energy:v:140:y:2017:i:p1:p:11-17
    DOI: 10.1016/j.energy.2017.08.041
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217314196
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.08.041?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cui, Yunfei & Geng, Zhiqiang & Zhu, Qunxiong & Han, Yongming, 2017. "Review: Multi-objective optimization methods and application in energy saving," Energy, Elsevier, vol. 125(C), pages 681-704.
    2. Zhang, Qi & Li, Zhan & Wang, Ge & Li, Hailong, 2016. "Study on the impacts of natural gas supply cost on gas flow and infrastructure deployment in China," Applied Energy, Elsevier, vol. 162(C), pages 1385-1398.
    3. Schwartz, Yair & Raslan, Rokia & Mumovic, Dejan, 2016. "Implementing multi objective genetic algorithm for life cycle carbon footprint and life cycle cost minimisation: A building refurbishment case study," Energy, Elsevier, vol. 97(C), pages 58-68.
    4. Govindan, Kannan & Jepsen, Martin Brandt, 2016. "ELECTRE: A comprehensive literature review on methodologies and applications," European Journal of Operational Research, Elsevier, vol. 250(1), pages 1-29.
    5. Lim, Seow & Kuby, Michael, 2010. "Heuristic algorithms for siting alternative-fuel stations using the Flow-Refueling Location Model," European Journal of Operational Research, Elsevier, vol. 204(1), pages 51-61, July.
    6. Hensher, David A. & King, Jenny, 2001. "Parking demand and responsiveness to supply, pricing and location in the Sydney central business district," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(3), pages 177-196, March.
    7. Innal, Fares & Dutuit, Yves & Chebila, Mourad, 2015. "Safety and operational integrity evaluation and design optimization of safety instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 32-50.
    8. Huiru Zhao & Sen Guo, 2014. "Selecting Green Supplier of Thermal Power Equipment by Using a Hybrid MCDM Method for Sustainability," Sustainability, MDPI, vol. 6(1), pages 1-19, January.
    9. Arbex, Renato Oliveira & da Cunha, Claudio Barbieri, 2015. "Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 355-376.
    10. Guo, Sen & Zhao, Huiru, 2015. "Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective," Applied Energy, Elsevier, vol. 158(C), pages 390-402.
    11. Szoplik, Jolanta, 2016. "Improving the natural gas transporting based on the steady state simulation results," Energy, Elsevier, vol. 109(C), pages 105-116.
    12. Panapakidis, Ioannis P. & Dagoumas, Athanasios S., 2017. "Day-ahead natural gas demand forecasting based on the combination of wavelet transform and ANFIS/genetic algorithm/neural network model," Energy, Elsevier, vol. 118(C), pages 231-245.
    13. Khan, Muhammad Imran & Yasmin, Tabassum & Shakoor, Abdul, 2015. "Technical overview of compressed natural gas (CNG) as a transportation fuel," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 785-797.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Amy Richter & Kelvin Tsun Wai Ng & Bahareh Fallah, 2019. "Bibliometric and text mining approaches to evaluate landfill design standards," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 1027-1049, March.
    2. Zhou, Jianli & Wu, Yunna & Tao, Yao & Gao, Jianwei & Zhong, Zhiming & Xu, Chuanbo, 2021. "Geographic information big data-driven two-stage optimization model for location decision of hydrogen refueling stations: An empirical study in China," Energy, Elsevier, vol. 225(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Jun & Guo, Fang & Zhang, Min, 2017. "Optimal planning of swapping/charging station network with customer satisfaction," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 174-197.
    2. Csiszár, Csaba & Csonka, Bálint & Földes, Dávid & Wirth, Ervin & Lovas, Tamás, 2020. "Location optimisation method for fast-charging stations along national roads," Journal of Transport Geography, Elsevier, vol. 88(C).
    3. Ravnik, J. & Hriberšek, M., 2019. "A method for natural gas forecasting and preliminary allocation based on unique standard natural gas consumption profiles," Energy, Elsevier, vol. 180(C), pages 149-162.
    4. Han, Dandan & E, Jiaqiang & Deng, Yuanwang & Chen, Jingwei & Leng, Erwei & Liao, Gaoliang & Zhao, Xiaohuan & Feng, Changling & Zhang, Feng, 2021. "A review of studies using hydrocarbon adsorption material for reducing hydrocarbon emissions from cold start of gasoline engine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    5. Yandong He & Xu Wang & Yun Lin & Fuli Zhou, 2016. "Optimal Partner Combination for Joint Distribution Alliance using Integrated Fuzzy EW-AHP and TOPSIS for Online Shopping," Sustainability, MDPI, vol. 8(4), pages 1-18, April.
    6. Finke, Jonas & Bertsch, Valentin, 2023. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," Applied Energy, Elsevier, vol. 332(C).
    7. Girma T. Chala & Abd Rashid Abd Aziz & Ftwi Y. Hagos, 2018. "Natural Gas Engine Technologies: Challenges and Energy Sustainability Issue," Energies, MDPI, vol. 11(11), pages 1-44, October.
    8. Peipei You & Sen Guo & Haoran Zhao & Huiru Zhao, 2017. "Operation Performance Evaluation of Power Grid Enterprise Using a Hybrid BWM-TOPSIS Method," Sustainability, MDPI, vol. 9(12), pages 1-15, December.
    9. Rey, Anthony & Zmeureanu, Radu, 2018. "Multi-objective optimization framework for the selection of configuration and equipment sizing of solar thermal combisystems," Energy, Elsevier, vol. 145(C), pages 182-194.
    10. Mousavi, M. & Gitinavard, H. & Mousavi, S.M., 2017. "A soft computing based-modified ELECTRE model for renewable energy policy selection with unknown information," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 774-787.
    11. Xie, Yunkun & Li, Yangyang & Zhao, Zhichao & Dong, Hao & Wang, Shuqian & Liu, Jingping & Guan, Jinhuan & Duan, Xiongbo, 2020. "Microsimulation of electric vehicle energy consumption and driving range," Applied Energy, Elsevier, vol. 267(C).
    12. Sharafian, Amir & Talebian, Hoda & Blomerus, Paul & Herrera, Omar & Mérida, Walter, 2017. "A review of liquefied natural gas refueling station designs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 503-513.
    13. Eduardo Fernández & José Rui Figueira & Jorge Navarro, 2023. "A theoretical look at ordinal classification methods based on comparing actions with limiting boundaries between adjacent classes," Annals of Operations Research, Springer, vol. 325(2), pages 819-843, June.
    14. You, Junyu & Ampomah, William & Sun, Qian, 2020. "Co-optimizing water-alternating-carbon dioxide injection projects using a machine learning assisted computational framework," Applied Energy, Elsevier, vol. 279(C).
    15. Ioannis Falkonakis & Saeid Lotfian & Baran Yeter, 2024. "Multi-Criteria Decision Analysis of an Innovative Additive Manufacturing Technique for Onboard Maintenance," Sustainability, MDPI, vol. 16(9), pages 1-18, April.
    16. Rao, Congjun & Zhang, Yue & Wen, Jianghui & Xiao, Xinping & Goh, Mark, 2023. "Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model," Energy, Elsevier, vol. 263(PC).
    17. Nock, Destenie & Baker, Erin, 2019. "Holistic multi-criteria decision analysis evaluation of sustainable electric generation portfolios: New England case study," Applied Energy, Elsevier, vol. 242(C), pages 655-673.
    18. Zhang, Meng & Guo, Huan & Sun, Ming & Liu, Sifeng & Forrest, Jeffrey, 2022. "A novel flexible grey multivariable model and its application in forecasting energy consumption in China," Energy, Elsevier, vol. 239(PE).
    19. Changyu Zhou & Guohe Huang & Jiapei Chen, 2019. "A Type-2 Fuzzy Chance-Constrained Fractional Integrated Modeling Method for Energy System Management of Uncertainties and Risks," Energies, MDPI, vol. 12(13), pages 1-21, June.
    20. Farrokhifar, Meisam & Nie, Yinghui & Pozo, David, 2020. "Energy systems planning: A survey on models for integrated power and natural gas networks coordination," Applied Energy, Elsevier, vol. 262(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:140:y:2017:i:p1:p:11-17. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.