IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v329y2023ics0306261922014842.html
   My bibliography  Save this article

A non-dominated sorting genetic approach using elite crossover for the combined cooling, heating, and power system with three energy storages

Author

Listed:
  • Zou, Dexuan
  • Gong, Dunwei
  • Ouyang, Haibin

Abstract

In this paper, the cooling, thermal and electrical energy storages are integrated into the combined cooling, heating, and power (CCHP) system to improve its energy utilization efficiency. Eight scenarios with or without electrical energy storage (EES) are investigated for the CCHP system. Furthermore, a non-dominated sorting genetic approach using elite crossover is presented for the eight scenarios. The elite crossover enables the individuals with non-domination rank 1 to converge towards the Pareto front of each scenario, and the other crossover helps the individuals with larger ranks to search in wide regions. In addition, an elimination strategy is used to exclude the individuals in crowded regions, which is beneficial for obtaining diversified solutions for each scenario instead of similar ones. For the four scenarios where selling electricity to grid is allowed, their energy, economy and environment function values are higher than those of the separate production scenarios, and the two scenarios with EES are 1.5997% and 2.6495%, respectively, higher than the two scenarios without EES. For the four scenarios where selling electricity to grid is forbidden, the two scenarios with EES can provide feasible solutions while the others fail. The two scenarios with EES achieve 72.1202% and 80.5804% total growths, respectively, for the separate production scenarios.

Suggested Citation

  • Zou, Dexuan & Gong, Dunwei & Ouyang, Haibin, 2023. "A non-dominated sorting genetic approach using elite crossover for the combined cooling, heating, and power system with three energy storages," Applied Energy, Elsevier, vol. 329(C).
    • Handle: RePEc:eee:appene:v:329:y:2023:i:c:s0306261922014842
    DOI: 10.1016/j.apenergy.2022.120227
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922014842
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.120227?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. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Cui, Hantao & Li, Xiaojing, 2017. "Optimal dispatch strategy for integrated energy systems with CCHP and wind power," Applied Energy, Elsevier, vol. 192(C), pages 408-419.
    2. Aghaei, Ali Tavakkol & Saray, Rahim Khoshbakhti, 2021. "Optimization of a combined cooling, heating, and power (CCHP) system with a gas turbine prime mover: A case study in the dairy industry," Energy, Elsevier, vol. 229(C).
    3. Chen, Jie & Huang, Shoujun & Shahabi, Laleh, 2021. "Economic and environmental operation of power systems including combined cooling, heating, power and energy storage resources using developed multi-objective grey wolf algorithm," Applied Energy, Elsevier, vol. 298(C).
    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. Cao, Yan & Habibi, Hamed & Zoghi, Mohammad & Raise, Amir, 2021. "Waste heat recovery of a combined regenerative gas turbine - recompression supercritical CO2 Brayton cycle driven by a hybrid solar-biomass heat source for multi-generation purpose: 4E analysis and pa," Energy, Elsevier, vol. 236(C).
    6. Gu, Wei & Lu, Shuai & Wu, Zhi & Zhang, Xuesong & Zhou, Jinhui & Zhao, Bo & Wang, Jun, 2017. "Residential CCHP microgrid with load aggregator: Operation mode, pricing strategy, and optimal dispatch," Applied Energy, Elsevier, vol. 205(C), pages 173-186.
    7. Wang, Jiangjiang & Sui, Jun & Jin, Hongguang, 2015. "An improved operation strategy of combined cooling heating and power system following electrical load," Energy, Elsevier, vol. 85(C), pages 654-666.
    8. Jie, Pengfei & Zhao, Wanyue & Yan, Fuchun & Man, Xiaoxin & Liu, Chunhua, 2022. "Economic, energetic and environmental optimization of hybrid biomass gasification-based combined cooling, heating and power system based on an improved operating strategy," Energy, Elsevier, vol. 240(C).
    9. Zhao, Huiru & Li, Bingkang & Lu, Hao & Wang, Xuejie & Li, Hongze & Guo, Sen & Xue, Wanlei & Wang, Yuwei, 2022. "Economy-environment-energy performance evaluation of CCHP microgrid system: A hybrid multi-criteria decision-making method," Energy, Elsevier, vol. 240(C).
    10. Li, Fan & Sun, Bo & Zhang, Chenghui & Liu, Che, 2019. "A hybrid optimization-based scheduling strategy for combined cooling, heating, and power system with thermal energy storage," Energy, Elsevier, vol. 188(C).
    11. Huang, Z.F. & Soh, K.Y. & Wan, Y.D. & Islam, M.R. & Chua, K.J., 2022. "Assessment of an intermediate working medium and cold energy storage (IWM-CES) system for LNG cold energy utilization under real regasification case," Energy, Elsevier, vol. 253(C).
    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. Zhang, Jianyun & Liu, Pei & Zhou, Zhe & Ma, Linwei & Li, Zheng & Ni, Weidou, 2014. "A mixed-integer nonlinear programming approach to the optimal design of heat network in a polygeneration energy system," Applied Energy, Elsevier, vol. 114(C), pages 146-154.
    14. Li, Yaohong & Tian, Ran & Wei, Mingshan, 2022. "Operation strategy for interactive CCHP system based on energy complementary characteristics of diverse operation strategies," Applied Energy, Elsevier, vol. 310(C).
    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. He, Wei & Yin, Ershuai & Zhou, Fan & Zhao, Yang & Hu, Dinghua & Li, Jiaqi & Li, Qiang, 2024. "Integrated manifold microchannels and near-junction cooling for enhanced thermal management in 3D heterogeneous packaging technology," Energy, Elsevier, vol. 305(C).
    2. Neshat, Mehdi & Sergiienko, Nataliia Y. & Nezhad, Meysam Majidi & da Silva, Leandro S.P. & Amini, Erfan & Marsooli, Reza & Astiaso Garcia, Davide & Mirjalili, Seyedali, 2024. "Enhancing the performance of hybrid wave-wind energy systems through a fast and adaptive chaotic multi-objective swarm optimisation method," Applied Energy, Elsevier, vol. 362(C).
    3. Ren, Xin-Yu & Li, Ling-Ling & Ji, Bing-Xiang & Liu, Jia-Qi, 2024. "Design and analysis of solar hybrid combined cooling, heating and power system: A bi-level optimization model," Energy, Elsevier, vol. 292(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. Xiao Gong & Fan Li & Bo Sun & Dong Liu, 2020. "Collaborative Optimization of Multi-Energy Complementary Combined Cooling, Heating, and Power Systems Considering Schedulable Loads," Energies, MDPI, vol. 13(4), pages 1-17, February.
    2. Yang, Yu & Liu, Zhiqiang & Xie, Nan & Wang, Jiaqiang & Cui, Yanping & Agbodjan, Yawovi Souley, 2023. "Multi-criteria optimization of multi-energy complementary systems considering reliability, economic and environmental effects," Energy, Elsevier, vol. 269(C).
    3. Jia, Bin & Li, Fan & Sun, Bo, 2024. "Knowledge-network-embedded deep reinforcement learning: An innovative way to high-efficiently develop an energy management strategy for the integrated energy system with renewable energy sources and m," Energy, Elsevier, vol. 301(C).
    4. Li, Fan & Sun, Bo & Zhang, Chenghui & Zhang, Lizhi, 2018. "Operation optimization for combined cooling, heating, and power system with condensation heat recovery," Applied Energy, Elsevier, vol. 230(C), pages 305-316.
    5. 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).
    6. Chen, Jie & Huang, Shoujun & Shahabi, Laleh, 2021. "Economic and environmental operation of power systems including combined cooling, heating, power and energy storage resources using developed multi-objective grey wolf algorithm," Applied Energy, Elsevier, vol. 298(C).
    7. 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.
    8. Yuan, Yu & Bai, Zhang & Zhou, Shengdong & Zheng, Bo & Hu, Wenxin, 2022. "Potential of applying the thermochemical recuperation in combined cooling, heating and power generation: Flexible demand response characteristics," Applied Energy, Elsevier, vol. 325(C).
    9. Wu, Chenyu & Gu, Wei & Xu, Yinliang & Jiang, Ping & Lu, Shuai & Zhao, Bo, 2018. "Bi-level optimization model for integrated energy system considering the thermal comfort of heat customers," Applied Energy, Elsevier, vol. 232(C), pages 607-616.
    10. Mu, Chenlu & Ding, Tao & Qu, Ming & Zhou, Quan & Li, Fangxing & Shahidehpour, Mohammad, 2020. "Decentralized optimization operation for the multiple integrated energy systems with energy cascade utilization," Applied Energy, Elsevier, vol. 280(C).
    11. Xin Zhao & Yanqi Chen & Gang Xu & Heng Chen, 2022. "Economic Assessment of Operation Strategies on Park-Level Integrated Energy System Coupled with Biogas: A Case Study in a Sewage Treatment Plant," Energies, MDPI, vol. 16(1), pages 1-21, December.
    12. Ai, Tianchao & Chen, Hongwei & Zhong, Fanghao & Jia, Jiandong & Song, Yangfan, 2023. "Multi-objective optimization of a novel CCHP system with organic flash cycle based on different operating strategies," Energy, Elsevier, vol. 276(C).
    13. Mu, Yunfei & Chen, Wanqing & Yu, Xiaodan & Jia, Hongjie & Hou, Kai & Wang, Congshan & Meng, Xianjun, 2020. "A double-layer planning method for integrated community energy systems with varying energy conversion efficiencies," Applied Energy, Elsevier, vol. 279(C).
    14. Li, Yiming & Liu, Che & Zhang, Lizhi & Sun, Bo, 2021. "A partition optimization design method for a regional integrated energy system based on a clustering algorithm," Energy, Elsevier, vol. 219(C).
    15. Liu, Fang & Mo, Qiu & Yang, Yongwen & Li, Pai & Wang, Shuai & Xu, Yanping, 2022. "A nonlinear model-based dynamic optimal scheduling of a grid-connected integrated energy system," Energy, Elsevier, vol. 243(C).
    16. Wang, Jiangjiang & Xie, Xinqi & Lu, Yanchao & Liu, Boxiang & Li, Xiaojing, 2018. "Thermodynamic performance analysis and comparison of a combined cooling heating and power system integrated with two types of thermal energy storage," Applied Energy, Elsevier, vol. 219(C), pages 114-122.
    17. 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).
    18. Hu, Xiao & Zhang, Heng & Chen, Dongwen & Li, Yong & Wang, Li & Zhang, Feng & Cheng, Haozhong, 2020. "Multi-objective planning for integrated energy systems considering both exergy efficiency and economy," Energy, Elsevier, vol. 197(C).
    19. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Cui, Hantao & Li, Xiaojing, 2017. "Optimal dispatch strategy for integrated energy systems with CCHP and wind power," Applied Energy, Elsevier, vol. 192(C), pages 408-419.
    20. Song, Xiaoling & Wang, Yudong & Zhang, Zhe & Shen, Charles & Peña-Mora, Feniosky, 2021. "Economic-environmental equilibrium-based bi-level dispatch strategy towards integrated electricity and natural gas systems," Applied Energy, Elsevier, vol. 281(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:appene:v:329:y:2023:i:c:s0306261922014842. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.