IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v197y2020ics0360544220304205.html
   My bibliography  Save this article

Multi-objective optimization and selection of hybrid combined cooling, heating and power systems considering operational flexibility

Author

Listed:
  • Wang, Jiangjiang
  • Liu, Yi
  • Ren, Fukang
  • Lu, Shuaikang

Abstract

This paper proposes a multi-objective optimization model integrated with operational flexibility to optimize a hybrid combined cooling, heating and power (CCHP) system. The operational flexibility of the hybrid CCHP system is proposed and expressed by the combined indicators to show the capacity to resist performance degradation because of externally variable conditions to increase energy saving and cost saving, to reduce carbon dioxide emissions, and to enhance renewability, the ability to adjust heat and electricity, and the grid integration level. A Pareto frontier of solutions considering a larger operational flexibility with less performance degradation is obtained in genetic algorithm. The use of a multi-criteria decision making method combined with an entropy weighting method is employed to quantitatively evaluate the composite sustainability index of the Pareto schemes and choose the optimal hybrid CCHP option with the best integrated performance. The results of a case study that considers operational flexibility and optimization indicated that the potential adjustable ability was increased by 438.9%, and the grid integration level and net interaction with the grid were decreased by 3.6%. However, the increase in flexibility reduces the energetic, economic and environmental benefits achieved by the CCHP system by 5.1%, 56.4% and 3.0%, respectively.

Suggested Citation

  • Wang, Jiangjiang & Liu, Yi & Ren, Fukang & Lu, Shuaikang, 2020. "Multi-objective optimization and selection of hybrid combined cooling, heating and power systems considering operational flexibility," Energy, Elsevier, vol. 197(C).
    • Handle: RePEc:eee:energy:v:197:y:2020:i:c:s0360544220304205
    DOI: 10.1016/j.energy.2020.117313
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220304205
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.117313?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. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa, 2010. "Optimization of capacity and operation for CCHP system by genetic algorithm," Applied Energy, Elsevier, vol. 87(4), pages 1325-1335, April.
    2. Ju, Liwei & Tan, Zhongfu & Li, Huanhuan & Tan, Qingkun & Yu, Xiaobao & Song, Xiaohua, 2016. "Multi-objective operation optimization and evaluation model for CCHP and renewable energy based hybrid energy system driven by distributed energy resources in China," Energy, Elsevier, vol. 111(C), pages 322-340.
    3. Perera, A.T.D. & Nik, Vahid M. & Mauree, Dasaraden & Scartezzini, Jean-Louis, 2017. "Electrical hubs: An effective way to integrate non-dispatchable renewable energy sources with minimum impact to the grid," Applied Energy, Elsevier, vol. 190(C), pages 232-248.
    4. Perera, A.T.D. & Nik, Vahid M. & Wickramasinghe, P.U. & Scartezzini, Jean-Louis, 2019. "Redefining energy system flexibility for distributed energy system design," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    5. Ma, Weiwu & Fang, Song & Liu, Gang, 2017. "Hybrid optimization method and seasonal operation strategy for distributed energy system integrating CCHP, photovoltaic and ground source heat pump," Energy, Elsevier, vol. 141(C), pages 1439-1455.
    6. Bai, Zhang & Liu, Qibin & Gong, Liang & Lei, Jing, 2019. "Application of a mid-/low-temperature solar thermochemical technology in the distributed energy system with cooling, heating and power production," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    7. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah, 2015. "An efficient scenario-based stochastic programming for optimal planning of combined heat, power, and hydrogen production of molten carbonate fuel cell power plants," Energy, Elsevier, vol. 83(C), pages 734-748.
    8. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhao, Jun-Hong, 2009. "Review on multi-criteria decision analysis aid in sustainable energy decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2263-2278, December.
    9. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2018. "Effect of load following strategies, hardware, and thermal load distribution on stand-alone hybrid CCHP systems," Applied Energy, Elsevier, vol. 220(C), pages 735-753.
    10. Zhang, Na & Wang, Zefeng & Lior, Noam & Han, Wei, 2018. "Advancement of distributed energy methods by a novel high efficiency solar-assisted combined cooling, heating and power system," Applied Energy, Elsevier, vol. 219(C), pages 179-186.
    11. Wang, Jiangjiang & Chen, Yuzhu & Dou, Chao & Gao, Yuefen & Zhao, Zheng, 2018. "Adjustable performance analysis of combined cooling heating and power system integrated with ground source heat pump," Energy, Elsevier, vol. 163(C), pages 475-489.
    12. Cho, Heejin & Smith, Amanda D. & Mago, Pedro, 2014. "Combined cooling, heating and power: A review of performance improvement and optimization," Applied Energy, Elsevier, vol. 136(C), pages 168-185.
    13. Liu, Mingxi & Shi, Yang & Fang, Fang, 2012. "A new operation strategy for CCHP systems with hybrid chillers," Applied Energy, Elsevier, vol. 95(C), pages 164-173.
    14. Wang, Jiangjiang & Zhai, Zhiqiang (John) & Jing, Youyin & Zhang, Chunfa, 2010. "Particle swarm optimization for redundant building cooling heating and power system," Applied Energy, Elsevier, vol. 87(12), pages 3668-3679, December.
    15. Wang, Jiangjiang & Lu, Zherui & Li, Meng & Lior, Noam & Li, Weihua, 2019. "Energy, exergy, exergoeconomic and environmental (4E) analysis of a distributed generation solar-assisted CCHP (combined cooling, heating and power) gas turbine system," Energy, Elsevier, vol. 175(C), pages 1246-1258.
    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. Alizadeh, M.I. & Parsa Moghaddam, M. & Amjady, N. & Siano, P. & Sheikh-El-Eslami, M.K., 2016. "Flexibility in future power systems with high renewable penetration: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1186-1193.
    18. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    19. Chen, Yuzhu & Wang, Jiangjiang & Ma, Chaofan & Gao, Yuefen, 2019. "Thermo-ecological cost assessment and optimization for a hybrid combined cooling, heating and power system coupled with compound parabolic concentrated-photovoltaic thermal solar collectors," Energy, Elsevier, vol. 176(C), pages 479-492.
    20. Wang, Jiangjiang & Chen, Yuzhu & Lior, Noam & Li, Weihua, 2019. "Energy, exergy and environmental analysis of a hybrid combined cooling heating and power system integrated with compound parabolic concentrated-photovoltaic thermal solar collectors," Energy, Elsevier, vol. 185(C), pages 463-476.
    21. Jing, You-Yin & Bai, He & Wang, Jiang-Jiang, 2012. "A fuzzy multi-criteria decision-making model for CCHP systems driven by different energy sources," Energy Policy, Elsevier, vol. 42(C), pages 286-296.
    Full references (including those not matched with items on IDEAS)

    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. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2022. "A review on the integration and optimization of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    2. Wang, Jiangjiang & Han, Zepeng & Guan, Zhimin, 2020. "Hybrid solar-assisted combined cooling, heating, and power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    3. Wang, Jiangjiang & Chen, Yuzhu & Lior, Noam & Li, Weihua, 2019. "Energy, exergy and environmental analysis of a hybrid combined cooling heating and power system integrated with compound parabolic concentrated-photovoltaic thermal solar collectors," Energy, Elsevier, vol. 185(C), pages 463-476.
    4. Ren, Fukang & Lin, Xiaozhen & Wei, Ziqing & Zhai, Xiaoqiang & Yang, Jianrong, 2022. "A novel planning method for design and dispatch of hybrid energy systems," Applied Energy, Elsevier, vol. 321(C).
    5. Jradi, M. & Riffat, S., 2014. "Tri-generation systems: Energy policies, prime movers, cooling technologies, configurations and operation strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 396-415.
    6. Yang, Sheng & Liu, Beilin & Li, Xiaolong & Liu, Zhiqiang & Liu, Yue & Xie, Nan & Ren, Jingzheng, 2023. "Flexibility index for a distributed energy system design optimization," Renewable Energy, Elsevier, vol. 219(P1).
    7. Tian, Zhe & Li, Xiaoyuan & Niu, Jide & Zhou, Ruoyu & Li, Feng, 2024. "Enhancing operation flexibility of distributed energy systems: A flexible multi-objective optimization planning method considering long-term and temporary objectives," Energy, Elsevier, vol. 288(C).
    8. Han, Zepeng & Wang, Jiangjiang & Cui, Zhiheng & Lu, Chunyan & Qi, Xiaoling, 2021. "Multi-objective optimization and exergoeconomic analysis for a novel full-spectrum solar-assisted methanol combined cooling, heating, and power system," Energy, Elsevier, vol. 237(C).
    9. Wang, Jiangjiang & Zhou, Yuan & Lior, Noam & Zhang, Guoqing, 2021. "Quantitative sustainability evaluations of hybrid combined cooling, heating, and power schemes integrated with solar technologies," Energy, Elsevier, vol. 231(C).
    10. Lizhi Zhang & Fan Li & Bo Sun & Chenghui Zhang, 2019. "Integrated Optimization Design of Combined Cooling, Heating, and Power System Coupled with Solar and Biomass Energy," Energies, MDPI, vol. 12(4), pages 1-21, February.
    11. 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.
    12. Wei, Dajun & Chen, Alian & Sun, Bo & Zhang, Chenghui, 2016. "Multi-objective optimal operation and energy coupling analysis of combined cooling and heating system," Energy, Elsevier, vol. 98(C), pages 296-307.
    13. Tian, Zhe & Niu, Jide & Lu, Yakai & He, Shunming & Tian, Xue, 2016. "The improvement of a simulation model for a distributed CCHP system and its influence on optimal operation cost and strategy," Applied Energy, Elsevier, vol. 165(C), pages 430-444.
    14. Chen, Yuzhu & Hua, Huilian & Wang, Jun & Lund, Peter D., 2021. "Thermodynamic performance analysis and modified thermo-ecological cost optimization of a hybrid district heating system considering energy levels," Energy, Elsevier, vol. 224(C).
    15. Hu, Mengqi & Cho, Heejin, 2014. "A probability constrained multi-objective optimization model for CCHP system operation decision support," Applied Energy, Elsevier, vol. 116(C), pages 230-242.
    16. Liu, Mingxi & Shi, Yang & Fang, Fang, 2014. "Combined cooling, heating and power systems: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 1-22.
    17. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    18. Afzali, Sayyed Faridoddin & Mahalec, Vladimir, 2017. "Optimal design, operation and analytical criteria for determining optimal operating modes of a CCHP with fired HRSG, boiler, electric chiller and absorption chiller," Energy, Elsevier, vol. 139(C), pages 1052-1065.
    19. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2021. "Multi-objective optimization and evaluation of hybrid CCHP systems for different building types," Energy, Elsevier, vol. 215(PA).
    20. Guozheng Li & Rui Wang & Tao Zhang & Mengjun Ming, 2018. "Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g," Energies, MDPI, vol. 11(4), pages 1-26, March.

    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:197:y:2020:i:c:s0360544220304205. 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.