IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v344y2026ics0360544226002665.html

Energy-economic-environmental analysis and multi-objective optimization of district heating and cooling system with long-term and short-term thermal storage

Author

Listed:
  • Ren, Yucheng
  • Xiao, Yimin
  • Ren, Zhili

Abstract

District heating and cooling (DHC) systems are widely applied because of remarkable economic efficiency and significant energy-saving potential. To address the issues of low utilization of seasonal pit thermal energy storage, a novel DHC system integrating long-term and short-term thermal storage is proposed. The NSGA-II algorithm and TOPSIS method are employed for equipment capacity optimization and sensitivity analysis, aiming to reduce both life-cycle costs (LCC) and annual CO2 emissions. In addition, a comprehensive evaluation of system performance and applicability is performed from energy, economic, and environmental perspectives across four building types and ten typical cities. The results indicate that, compared with the baseline system, COP of the proposed system increases by 63.89 %, while its LCC, levelized cost of energy, and annual CO2 emissions decrease by 49.91 %, 51.56 %, and 68.71 % respectively, with an investment payback period of only 2.73 years. The systems are most suitable for hospitals, followed by hotels, markets, and offices. The systems in cold and severe cold regions with abundant solar radiation achieve better performance than those in hot summer-cold winter regions with limited solar resources. The novel DHC systems enhance the comprehensive performance, providing a technical pathway for the low-carbon transition of regional energy systems.

Suggested Citation

  • Ren, Yucheng & Xiao, Yimin & Ren, Zhili, 2026. "Energy-economic-environmental analysis and multi-objective optimization of district heating and cooling system with long-term and short-term thermal storage," Energy, Elsevier, vol. 344(C).
  • Handle: RePEc:eee:energy:v:344:y:2026:i:c:s0360544226002665
    DOI: 10.1016/j.energy.2026.140164
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544226002665
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2026.140164?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Haoran & Huang, Yixiang & Tian, Shaochen & Huang, Lei & Li, Shangao & Wang, Qinbao & Su, Xing, 2025. "Operational performance of heat pump desiccant wheel system in low humidity industrial environment: On-site measurements and model based optimization," Energy, Elsevier, vol. 322(C).
    2. Li, Ainong & Huang, Kailiang & Feng, Guihui & Zhang, Lei & Fang, Xianshi & Xie, Hailun & Li, Xiaoxu & Meng, Xianghua, 2025. "Performance of a new discharging scheme for water pit thermal energy storage system integrated heat pump," Energy, Elsevier, vol. 326(C).
    3. Hu, Zhiru & Li, Tianshuang & Zhang, Yuxin & Tao, Yao & Tu, Jiyuan & Yang, Qizhi & Wang, Yong & Yang, Lizhong & Romagnoli, Alessandro, 2024. "Experimental investigation on the performance of a borehole thermal energy storage system based on similarity and symmetry," Energy, Elsevier, vol. 313(C).
    4. Liu, Yanfeng & Zhao, Yiting & Chen, Yaowen & Wang, Dengjia & Li, Yong & Yuan, Xipeng, 2022. "Design optimization of the solar heating system for office buildings based on life cycle cost in Qinghai-Tibet plateau of China," Energy, Elsevier, vol. 246(C).
    5. Zheng, Nan & Wang, Qiushi & Ding, Xingqi & Wang, Xiaomeng & Zhang, Hanfei & Duan, Liqiang & Desideri, Umberto, 2025. "Proactive energy storage operation strategy and optimization of a solar polystorage and polygeneration system based on day-ahead load forecasting," Applied Energy, Elsevier, vol. 381(C).
    6. Wang, Weichen & Sun, Jingchao & Yan, Su & Yuan, Yuxing & Xiao, Tianshun & Chen, Baoqi & Du, Tao & Na, Hongming, 2025. "Multi-objective optimization analysis of on-demand design in multi-source heating system for low carbon development," Energy, Elsevier, vol. 324(C).
    7. Yao, Shuai & Wu, Jianzhong & Qadrdan, Meysam, 2024. "A state-of-the-art analysis and perspectives on the 4th/5th generation district heating and cooling systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 202(C).
    8. Zhan, Chenxuan & Xu, Yi & Fan, Jianhua & Gao, Meng & Kong, Weiqiang & Wu, Jiani & Wang, Dengjia & Tian, Zhiyong, 2025. "Validation and optimization of a solar heating plant with a large-scale heat pump," Energy, Elsevier, vol. 319(C).
    9. Sreenath, S. & Kirs, Tanel & Kirs, Kristian & Volkova, Anna, 2024. "Photovoltaic-powered seasonal snow storage-assisted district cooling system: Site suitability analysis and performance assessment," Energy, Elsevier, vol. 312(C).
    10. Malcher, Xenia & Tenorio-Rodriguez, Francis Catherine & Finkbeiner, Matthias & Gonzalez-Salazar, Miguel, 2025. "Decarbonization of district heating: A systematic review of carbon footprint and key mitigation strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 215(C).
    11. Yan, Chengchu & Shi, Wenxing & Li, Xianting & Zhao, Yang, 2016. "Optimal design and application of a compound cold storage system combining seasonal ice storage and chilled water storage," Applied Energy, Elsevier, vol. 171(C), pages 1-11.
    12. Elomari, Youssef & Mateu, Carles & Marín-Genescà, M. & Boer, Dieter, 2024. "A data-driven framework for designing a renewable energy community based on the integration of machine learning model with life cycle assessment and life cycle cost parameters," Applied Energy, Elsevier, vol. 358(C).
    13. Calise, F. & Cappiello, F.L. & Cimmino, L. & Cuomo, F.P. & Vicidomini, M., 2025. "A 5th generation district heating cooling network integrated with a phase change material thermal energy storage: A dynamic thermoeconomic analysis," Applied Energy, Elsevier, vol. 389(C).
    14. Sifnaios, Ioannis & Sneum, Daniel Møller & Jensen, Adam R. & Fan, Jianhua & Bramstoft, Rasmus, 2023. "The impact of large-scale thermal energy storage in the energy system," Applied Energy, Elsevier, vol. 349(C).
    15. Mei, Fei & Zhang, Jiatang & Lu, Jixiang & Lu, Jinjun & Jiang, Yuhan & Gu, Jiaqi & Yu, Kun & Gan, Lei, 2021. "Stochastic optimal operation model for a distributed integrated energy system based on multiple-scenario simulations," Energy, Elsevier, vol. 219(C).
    16. Jia, Xin & Chen, Hu & Yang, Yingxia & Xu, Ce & Duanmu, Lin & Wang, Zhichao, 2025. "Research on integrative optimization operation of seawater heat pump, photovoltaic, and cross-seasonal heat storage systems," Renewable Energy, Elsevier, vol. 246(C).
    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. Wei, Jiaxing & Huang, Kailiang & Ding, Chenjun & Feng, Guohui & Tang, Runze & Li, Xiaoxu & Xie, Hailun, 2025. "Operational performance and application potential of a seasonal ice storage cylinder cooling system in cold climate based on experimental investigation and deep learning," Energy, Elsevier, vol. 331(C).
    2. Rosendal, M. & Janin, J. & Heggarty, T. & Pisinger, D. & Bramstoft, R. & Münster, M., 2025. "The benefits and challenges of soft-linking investment and operational energy system models," Applied Energy, Elsevier, vol. 385(C).
    3. Barth, Florian & Schüppler, Simon & Menberg, Kathrin & Blum, Philipp, 2023. "Estimating cooling capacities from aerial images using convolutional neural networks," Applied Energy, Elsevier, vol. 349(C).
    4. Mingshan Mo & Xinrui Xiong & Yunlong Wu & Zuyao Yu, 2023. "Deep-Reinforcement-Learning-Based Low-Carbon Economic Dispatch for Community-Integrated Energy System under Multiple Uncertainties," Energies, MDPI, vol. 16(22), pages 1-18, November.
    5. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    6. Casella, Virginia & Ferro, Giulio & Parodi, Luca & Robba, Michela, 2025. "Maximizing shared benefits in renewable energy communities: A Bilevel optimization model," Applied Energy, Elsevier, vol. 386(C).
    7. Cao, Wenqiang & Yu, Junqi & Ru, Chengyi & Wang, Meng & Wang, Ke, 2025. "A two-stage distributionally robust optimization operation scheduling model for solar PT-PV systems based on integrated load consumption prediction," Energy, Elsevier, vol. 332(C).
    8. Wu, Tianyu & Han, Fengwu & Zhao, Yunlong & Yu, Zishuo, 2025. "A decarbonization-oriented and uncertainty-aware energy management strategy for multi-district integrated energy systems with fair peer-to-peer trading," Energy, Elsevier, vol. 323(C).
    9. Li-Peng Shao & Jia-Jia Chen & Lu-Wen Pan & Zi-Juan Yang, 2022. "A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions," Mathematics, MDPI, vol. 10(23), pages 1-20, November.
    10. Chen, Boyu & Che, Yanbo & Qadrdan, Meysam & Takcı, Mehmet Türker & Zhou, Yue, 2025. "Low‑carbon coordinated operation of data centers and district heating network with heating recovery," Applied Energy, Elsevier, vol. 398(C).
    11. Koumparakis, Christos & Kountouris, Ioannis & Bramstoft, Rasmus, 2025. "Utilization of excess heat in future Power-to-X energy hubs through sector-coupling," Applied Energy, Elsevier, vol. 377(PA).
    12. Serra, Adrià & Ortiz, Alberto & Cortés, Pau Joan & Canals, Vincent, 2025. "Explainable district heating load forecasting by means of a reservoir computing deep learning architecture," Energy, Elsevier, vol. 318(C).
    13. Wunvisa Tipasri & Amnart Suksri & Karthikeyan Velmurugan & Tanakorn Wongwuttanasatian, 2022. "Energy Management for an Air Conditioning System Using a Storage Device to Reduce the On-Peak Power Consumption," Energies, MDPI, vol. 15(23), pages 1-19, November.
    14. Zhao, Zhuang & Wu, Jiahui & Wang, Bo & Wang, Rui, 2025. "Research on source-load uncertainty optimal scheduling based on a hybrid robust multi-interval optimization method," Renewable Energy, Elsevier, vol. 251(C).
    15. Li, Manfeng & Wang, Mengmeng & Shi, Ping & Zhou, Guofeng & Lu, Yiji, 2025. "Techno-economic-environmental assessment and optimization of multi-energy complementary systems under dynamic building loads," Energy, Elsevier, vol. 338(C).
    16. Pei Cai & Youxue Jiang & He Wang & Liangyu Wu & Peng Cao & Yulong Zhang & Feng Yao, 2020. "Numerical Simulation on the Influence of the Longitudinal Fins on the Enhancement of a Shell-and-Tube Ice Storage Device," Sustainability, MDPI, vol. 12(6), pages 1-14, March.
    17. Yang, Xiaohui & Wang, Xiaopeng & Deng, Yeheng & Mei, Linghao & Deng, Fuwei & Zhang, Zhonglian, 2023. "Integrated energy system scheduling model based on non-complete interval multi-objective fuzzy optimization," Renewable Energy, Elsevier, vol. 218(C).
    18. Lédée, François & Crawford, Curran & Evins, Ralph, 2025. "Improved surrogate modeling for multi-energy system design: Model architecture, sampling and scaling choices," Applied Energy, Elsevier, vol. 390(C).
    19. Jingyu Shi & Ran Xu & Dongfang Li & Tao Zhu & Nanyu Fan & Zhanghua Hong & Guohua Wang & Yong Han & Xing Zhu, 2025. "Multi-Criteria Optimization and Techno-Economic Assessment of a Wind–Solar–Hydrogen Hybrid System for a Plateau Tourist City Using HOMER and Shannon Entropy-EDAS Models," Energies, MDPI, vol. 18(15), pages 1-26, August.
    20. El Kassar, Razan & Al Takash, Ahmad & El Rassy, Elissa & Hammoud, Mohammad & Py, Xavier, 2026. "Evaluating the sustainability of pv technologies and their cooling systems: a life cycle assessment review," Applied Energy, Elsevier, vol. 404(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:344:y:2026:i:c:s0360544226002665. 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.