IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v169y2019icp750-761.html
   My bibliography  Save this article

Distributed energy system for sustainability transition: A comprehensive assessment under uncertainties based on interval multi-criteria decision making method by coupling interval DEMATEL and interval VIKOR

Author

Listed:
  • Wang, Zhenfeng
  • Xu, Guangyin
  • Wang, Heng
  • Ren, Jingzheng

Abstract

Distributed energy system (DES) has been recognized as a promising solution for energy security improvement and emissions mitigation all over the world. However, there are usually various DES configurations with different performances, and it is usually difficult for the decision-makers to select the most sustainable DES solution among multiple choices. This study aims to develop a comprehensive a framework for sustainability prioritization of distributed energy systems under data uncertainties. An interval multi-criteria decision making method which can address data uncertainties was developed by combining the interval Decision Making Trail and Evaluation Laboratory (DEMATEL) and the interval VIKOR method. Four distributed energy systems including gas turbine system, fuel cell system, photovoltaic system, and internal combustion engine system were studied by the proposed method, and photovoltaic system has been recognized as the most sustainable scenario, following by fuel cell system, gas turbine system, and internal combustion engine system in the descending order. In order to investigate the effects of the weights on the final sustainability ranking of the four distributed energy systems, sensitivity analysis was carried out, and the results reveal that the weights of the criteria have significant impacts on the sustainability rankings of these four distributed energy systems.

Suggested Citation

  • Wang, Zhenfeng & Xu, Guangyin & Wang, Heng & Ren, Jingzheng, 2019. "Distributed energy system for sustainability transition: A comprehensive assessment under uncertainties based on interval multi-criteria decision making method by coupling interval DEMATEL and interva," Energy, Elsevier, vol. 169(C), pages 750-761.
  • Handle: RePEc:eee:energy:v:169:y:2019:i:c:p:750-761
    DOI: 10.1016/j.energy.2018.12.105
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421832471X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2018.12.105?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. Chicco, Gianfranco & Mancarella, Pierluigi, 2009. "Distributed multi-generation: A comprehensive view," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(3), pages 535-551, April.
    2. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "Optimal design of distributed energy resource systems coupled with energy distribution networks," Energy, Elsevier, vol. 85(C), pages 433-448.
    3. Zhou, Zhe & Zhang, Jianyun & Liu, Pei & Li, Zheng & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "A two-stage stochastic programming model for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 103(C), pages 135-144.
    4. Ren, Hongbo & Gao, Weijun, 2010. "A MILP model for integrated plan and evaluation of distributed energy systems," Applied Energy, Elsevier, vol. 87(3), pages 1001-1014, March.
    5. Ren, Hongbo & Gao, Weijun & Zhou, Weisheng & Nakagami, Ken'ichi, 2009. "Multi-criteria evaluation for the optimal adoption of distributed residential energy systems in Japan," Energy Policy, Elsevier, vol. 37(12), pages 5484-5493, December.
    6. Falke, Tobias & Krengel, Stefan & Meinerzhagen, Ann-Kathrin & Schnettler, Armin, 2016. "Multi-objective optimization and simulation model for the design of distributed energy systems," Applied Energy, Elsevier, vol. 184(C), pages 1508-1516.
    7. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Comparison of alternative decision-making criteria in a two-stage stochastic program for the design of distributed energy systems under uncertainty," Energy, Elsevier, vol. 156(C), pages 709-724.
    8. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    9. Sengupta, Atanu & Pal, Tapan Kumar, 2000. "On comparing interval numbers," European Journal of Operational Research, Elsevier, vol. 127(1), pages 28-43, November.
    10. Mehleri, E.D. & Sarimveis, H. & Markatos, N.C. & Papageorgiou, L.G., 2013. "Optimal design and operation of distributed energy systems: Application to Greek residential sector," Renewable Energy, Elsevier, vol. 51(C), pages 331-342.
    11. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2007. "Extended VIKOR method in comparison with outranking methods," European Journal of Operational Research, Elsevier, vol. 178(2), pages 514-529, April.
    12. Bai, Chunguang & Sarkis, Joseph, 2013. "A grey-based DEMATEL model for evaluating business process management critical success factors," International Journal of Production Economics, Elsevier, vol. 146(1), pages 281-292.
    13. Ren, Jingzheng & Liang, Hanwei & Dong, Liang & Gao, Zhiqiu & He, Chang & Pan, Ming & Sun, Lu, 2017. "Sustainable development of sewage sludge-to-energy in China: Barriers identification and technologies prioritization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 384-396.
    14. Wang, Yang & Kuckelkorn, Jens & Li, Daoliang & Du, Jiangtao, 2018. "Evaluation on distributed renewable energy system integrated with a Passive House building using a new energy performance index," Energy, Elsevier, vol. 161(C), pages 81-89.
    15. Liu, Hu-Chen & You, Jian-Xin & Lu, Chao & Chen, Yi-Zeng, 2015. "Evaluating health-care waste treatment technologies using a hybrid multi-criteria decision making model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 932-942.
    16. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Shi, Guo-Hua & Zhang, Xu-Tao, 2008. "A fuzzy multi-criteria decision-making model for trigeneration system," Energy Policy, Elsevier, vol. 36(10), pages 3823-3832, October.
    17. Mehigan, L. & Deane, J.P. & Gallachóir, B.P.Ó. & Bertsch, V., 2018. "A review of the role of distributed generation (DG) in future electricity systems," Energy, Elsevier, vol. 163(C), pages 822-836.
    18. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    19. Kaya, Tolga & Kahraman, Cengiz, 2010. "Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul," Energy, Elsevier, vol. 35(6), pages 2517-2527.
    20. Papadopoulos, Agis & Karagiannidis, Avraam, 2008. "Application of the multi-criteria analysis method Electre III for the optimisation of decentralised energy systems," Omega, Elsevier, vol. 36(5), pages 766-776, October.
    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. Elkadeem, M.R. & Younes, Ali & Sharshir, Swellam W. & Campana, Pietro Elia & Wang, Shaorong, 2021. "Sustainable siting and design optimization of hybrid renewable energy system: A geospatial multi-criteria analysis," Applied Energy, Elsevier, vol. 295(C).
    2. Zheng, Guozhong & Wang, Xiao, 2020. "The comprehensive evaluation of renewable energy system schemes in tourist resorts based on VIKOR method," Energy, Elsevier, vol. 193(C).
    3. Wu, Yunna & Liao, Mingjuan & Hu, Mengyao & Lin, Jiawei & Zhou, Jianli & Zhang, Buyuan & Xu, Chuanbo, 2020. "A decision framework of low-speed wind farm projects in hilly areas based on DEMATEL-entropy-TODIM method from the sustainability perspective: A case in China," Energy, Elsevier, vol. 213(C).
    4. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    5. Yuan, Jiahang & Luo, Xinggang & Li, Yun & Hu, Xiaoqing & Chen, Wenchong & Zhang, Yue, 2022. "Multi criteria decision-making for distributed energy system based on multi-source heterogeneous data," Energy, Elsevier, vol. 239(PD).
    6. Fouladvand, Javanshir, 2022. "Behavioural attributes towards collective energy security in thermal energy communities: Environmental-friendly behaviour matters," Energy, Elsevier, vol. 261(PB).
    7. Huy, Phung Dang & Ramachandaramurthy, Vigna K. & Yong, Jia Ying & Tan, Kang Miao & Ekanayake, Janaka B., 2020. "Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage," Energy, Elsevier, vol. 195(C).
    8. Wanyu Wang & Haochen Li & Xueliang Hou & Qian Zhang & Songfeng Tian, 2021. "Multi-Criteria Evaluation of Distributed Energy System Based on Order Relation-Anti-Entropy Weight Method," Energies, MDPI, vol. 14(1), pages 1-16, January.
    9. Ghenai, Chaouki & Albawab, Mona & Bettayeb, Maamar, 2020. "Sustainability indicators for renewable energy systems using multi-criteria decision-making model and extended SWARA/ARAS hybrid method," Renewable Energy, Elsevier, vol. 146(C), pages 580-597.
    10. Lu, Zhiming & Gao, Yan & Xu, Chuanbo, 2021. "Evaluation of energy management system for regional integrated energy system under interval type-2 hesitant fuzzy environment," Energy, Elsevier, vol. 222(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. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2017. "Decarbonizing the electricity grid: The impact on urban energy systems, distribution grids and district heating potential," Applied Energy, Elsevier, vol. 191(C), pages 125-140.
    2. Zhigang Duan & Yamin Yan & Xiaohan Yan & Qi Liao & Wan Zhang & Yongtu Liang & Tianqi Xia, 2017. "An MILP Method for Design of Distributed Energy Resource System Considering Stochastic Energy Supply and Demand," Energies, MDPI, vol. 11(1), pages 1-23, December.
    3. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    4. Di Somma, M. & Yan, B. & Bianco, N. & Graditi, G. & Luh, P.B. & Mongibello, L. & Naso, V., 2017. "Multi-objective design optimization of distributed energy systems through cost and exergy assessments," Applied Energy, Elsevier, vol. 204(C), pages 1299-1316.
    5. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2016. "DESOD: a mathematical programming tool to optimally design a distributed energy system," Energy, Elsevier, vol. 100(C), pages 298-309.
    6. Yuan, Jiahang & Luo, Xinggang & Li, Yun & Hu, Xiaoqing & Chen, Wenchong & Zhang, Yue, 2022. "Multi criteria decision-making for distributed energy system based on multi-source heterogeneous data," Energy, Elsevier, vol. 239(PD).
    7. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimization framework for distributed energy systems with integrated electrical grid constraints," Applied Energy, Elsevier, vol. 171(C), pages 296-313.
    8. Han, Jie & Ouyang, Leixin & Xu, Yuzhen & Zeng, Rong & Kang, Shushuo & Zhang, Guoqiang, 2016. "Current status of distributed energy system in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 288-297.
    9. Urban, Kristof L. & Scheller, Fabian & Bruckner, Thomas, 2021. "Suitability assessment of models in the industrial energy system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    10. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimising urban energy systems: Simultaneous system sizing, operation and district heating network layout," Energy, Elsevier, vol. 116(P1), pages 619-636.
    11. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    12. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing, 2016. "Multi-objective optimization of a distributed energy network integrated with heating interchange," Energy, Elsevier, vol. 109(C), pages 353-364.
    13. Li, Longxi & Mu, Hailin & Li, Nan & Li, Miao, 2016. "Economic and environmental optimization for distributed energy resource systems coupled with district energy networks," Energy, Elsevier, vol. 109(C), pages 947-960.
    14. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Weng, Peifen & Ren, Jianxing, 2018. "Design and operation optimization of organic Rankine cycle coupled trigeneration systems," Energy, Elsevier, vol. 142(C), pages 666-677.
    15. Akbari, Kaveh & Jolai, Fariborz & Ghaderi, Seyed Farid, 2016. "Optimal design of distributed energy system in a neighborhood under uncertainty," Energy, Elsevier, vol. 116(P1), pages 567-582.
    16. Da Li & Shijie Zhang & Yunhan Xiao, 2020. "Interval Optimization-Based Optimal Design of Distributed Energy Resource Systems under Uncertainties," Energies, MDPI, vol. 13(13), pages 1-18, July.
    17. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "An MILP (mixed integer linear programming) model for optimal design of district-scale distributed energy resource systems," Energy, Elsevier, vol. 90(P2), pages 1901-1915.
    18. Karmellos, M. & Georgiou, P.N. & Mavrotas, G., 2019. "A comparison of methods for the optimal design of Distributed Energy Systems under uncertainty," Energy, Elsevier, vol. 178(C), pages 318-333.
    19. Fichera, Alberto & Frasca, Mattia & Volpe, Rosaria, 2017. "Complex networks for the integration of distributed energy systems in urban areas," Applied Energy, Elsevier, vol. 193(C), pages 336-345.
    20. Gao, Jiajia & Kang, Jing & Zhang, Chong & Gang, Wenjie, 2018. "Energy performance and operation characteristics of distributed energy systems with district cooling systems in subtropical areas under different control strategies," Energy, Elsevier, vol. 153(C), pages 849-860.

    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:169:y:2019:i:c:p:750-761. 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.