IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v229y2021ics0360544221008860.html
   My bibliography  Save this article

A novel operation strategy based on black hole algorithm to optimize combined cooling, heating, and power-ground source heat pump system

Author

Listed:
  • Deng, Yan
  • Liu, Yicai
  • Zeng, Rong
  • Wang, Qianxu
  • Li, Zheng
  • Zhang, Yu
  • Liang, Heng

Abstract

To improve the efficiency of a combined cooling, heating, and power-ground source heat pump system (CCHP-GSHP), ground source heat pump cooling and heating start factors are proposed. The start factors can control the GSHP cooling and heating start load rates. Moreover, they can reduce the operating time of GSHP with a low coefficient of performance (COP) and increase the operating time with a high COP during the absorption refrigeration. A following electric load with start factors (FEL-SF) is presented as a novel operation strategy for guiding the system operation, and is compared with a traditional FEL. In the FEL-SF model, the rated capacity of the power generation unit, seasonal start factors, and seasonal GSHP energy ratios are established as decision variables. The system’s optimal objective is providing an optimal comprehensive performance in regards to energy, the environment, and the economy. The black hole (BH) algorithm is used to solve the optimization problem. A hotel building is selected as an example for analysis. The research results show that the FEL-SF operation strategy has better performance (the comprehensive performance reaches 4.0%) throughout the year. The effect of the FEL-SF strategy is superior for each index in each season. In addition, the setting of the GSHP start factors is suitable for most regions with different climates.

Suggested Citation

  • Deng, Yan & Liu, Yicai & Zeng, Rong & Wang, Qianxu & Li, Zheng & Zhang, Yu & Liang, Heng, 2021. "A novel operation strategy based on black hole algorithm to optimize combined cooling, heating, and power-ground source heat pump system," Energy, Elsevier, vol. 229(C).
  • Handle: RePEc:eee:energy:v:229:y:2021:i:c:s0360544221008860
    DOI: 10.1016/j.energy.2021.120637
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221008860
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2021.120637?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. 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.
    2. 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.
    3. Knizley, Alta A. & Mago, Pedro J. & Smith, Amanda D., 2014. "Evaluation of the performance of combined cooling, heating, and power systems with dual power generation units," Energy Policy, Elsevier, vol. 66(C), pages 654-665.
    4. Yang, H. & Cui, P. & Fang, Z., 2010. "Vertical-borehole ground-coupled heat pumps: A review of models and systems," Applied Energy, Elsevier, vol. 87(1), pages 16-27, January.
    5. 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.
    6. 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.
    7. 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.
    8. Soheyli, Saman & Shafiei Mayam, Mohamad Hossein & Mehrjoo, Mehri, 2016. "Modeling a novel CCHP system including solar and wind renewable energy resources and sizing by a CC-MOPSO algorithm," Applied Energy, Elsevier, vol. 184(C), pages 375-395.
    9. Ershadi, Hamed & Karimipour, Arash, 2018. "Present a multi-criteria modeling and optimization (energy, economic and environmental) approach of industrial combined cooling heating and power (CCHP) generation systems using the genetic algorithm,," Energy, Elsevier, vol. 149(C), pages 286-295.
    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. Liu, Zhijian & Fan, Guangyao & Sun, Dekang & Wu, Di & Guo, Jiacheng & Zhang, Shicong & Yang, Xinyan & Lin, Xianping & Ai, Lei, 2022. "A novel distributed energy system combining hybrid energy storage and a multi-objective optimization method for nearly zero-energy communities and buildings," Energy, Elsevier, vol. 239(PE).
    2. 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).
    3. Mahmoud, Montaser & Alkhedher, Mohammad & Ramadan, Mohamad & Naher, Sumsun & Pullen, Keith, 2022. "An investigation on organic Rankine cycle incorporating a ground-cooled condenser: Working fluid selection and regeneration," Energy, Elsevier, vol. 249(C).
    4. Chen, Minghao & Xie, Zhiyuan & Sun, Yi & Zheng, Shunlin, 2023. "The predictive management in campus heating system based on deep reinforcement learning and probabilistic heat demands forecasting," Applied Energy, Elsevier, vol. 350(C).
    5. Zhu, Xiaochen & Fuli, Wang, 2023. "Energy savings bottleneck diagnosis and optimization decision method for industrial auxiliary system based on energy efficiency gap analysis," Energy, Elsevier, vol. 263(PE).
    6. Deng, Yan & Zeng, Rong & Liu, Yicai, 2022. "A novel off-design model to optimize combined cooling, heating and power system with hybrid chillers for different operation strategies," Energy, Elsevier, vol. 239(PB).
    7. Chen, Ke & Pan, Ming, 2021. "Operation optimization of combined cooling, heating, and power superstructure system for satisfying demand fluctuation," Energy, Elsevier, vol. 237(C).
    8. Jie, Pengfei & Li, Zhe & Ren, Yanli & Wei, Fengjun, 2023. "Economy-energy-environment optimization of biomass gasification CCHP system integrated with ground source heat pump," Energy, Elsevier, vol. 277(C).
    9. You, Tian & Wang, Fang, 2023. "Green ground source heat pump using various low-global-warming-potential refrigerants: Thermal imbalance and long-term performance," Renewable Energy, Elsevier, vol. 210(C), pages 159-173.
    10. Jin, Baohong, 2023. "Impact of renewable energy penetration in power systems on the optimization and operation of regional distributed energy systems," Energy, Elsevier, vol. 273(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. Deng, Yan & Zeng, Rong & Liu, Yicai, 2022. "A novel off-design model to optimize combined cooling, heating and power system with hybrid chillers for different operation strategies," Energy, Elsevier, vol. 239(PB).
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. Wang, Jiangjiang & Lu, Yanchao & Yang, Ying & Mao, Tianzhi, 2016. "Thermodynamic performance analysis and optimization of a solar-assisted combined cooling, heating and power system," Energy, Elsevier, vol. 115(P1), pages 49-59.
    7. Gao, Lei & Hwang, Yunho & Cao, Tao, 2019. "An overview of optimization technologies applied in combined cooling, heating and power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    8. 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.
    9. Wang, Jiangjiang & Yang, Ying & Mao, Tianzhi & Sui, Jun & Jin, Hongguang, 2015. "Life cycle assessment (LCA) optimization of solar-assisted hybrid CCHP system," Applied Energy, Elsevier, vol. 146(C), pages 38-52.
    10. Song, Zhihui & Liu, Tao & Lin, Qizhao, 2020. "Multi-objective optimization of a solar hybrid CCHP system based on different operation modes," Energy, Elsevier, vol. 206(C).
    11. Wencong Huang & Yufang Chang & Youxin Yuan, 2019. "Complementary Configuration and Optimal Energy Flow of CCHP-ORC Systems Using a Matrix Modeling Approach," Complexity, Hindawi, vol. 2019, pages 1-15, April.
    12. Putna, Ondřej & Janošťák, František & Šomplák, Radovan & Pavlas, Martin, 2018. "Demand modelling in district heating systems within the conceptual design of a waste-to-energy plant," Energy, Elsevier, vol. 163(C), pages 1125-1139.
    13. Li, Ruonan & Mahalec, Vladimir, 2022. "Integrated design and operation of energy systems for residential buildings, commercial buildings, and light industries," Applied Energy, Elsevier, vol. 305(C).
    14. Piacentino, Antonio & Barbaro, Chiara & Cardona, Fabio & Gallea, Roberto & Cardona, Ennio, 2013. "A comprehensive tool for efficient design and operation of polygeneration-based energy μgrids serving a cluster of buildings. Part I: Description of the method," Applied Energy, Elsevier, vol. 111(C), pages 1204-1221.
    15. Jie, Pengfei & Yan, Fuchun & Li, Jing & Zhang, Yumei & Wen, Zhimei, 2019. "Optimizing the insulation thickness of walls of existing buildings with CHP-based district heating systems," Energy, Elsevier, vol. 189(C).
    16. 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).
    17. Jin, Baohong, 2023. "Impact of renewable energy penetration in power systems on the optimization and operation of regional distributed energy systems," Energy, Elsevier, vol. 273(C).
    18. 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.
    19. Barber, Kyle A. & Krarti, Moncef, 2022. "A review of optimization based tools for design and control of building energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    20. Ma, Weiwu & Fang, Song & Liu, Gang & Zhou, Ruoyu, 2017. "Modeling of district load forecasting for distributed energy system," Applied Energy, Elsevier, vol. 204(C), pages 181-205.

    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:229:y:2021:i:c:s0360544221008860. 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.