IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v309y2024ics0360544224028639.html
   My bibliography  Save this article

Design and optimal scheduling of forecasting-based campus multi-energy complementary energy system

Author

Listed:
  • Dong, Weichao
  • Sun, Hexu
  • Li, Zheng
  • Yang, Huifang

Abstract

This study presents a complete campus multi-energy complementary energy system (MCES), including an accurate forecasting model, efficient MCES model, and effective multi-objective optimal scheduling strategy to better utilize renewable energy. A hybrid forecasting model, including multi-scale mathematical morphological decomposition, a bidirectional long short-term memory network, and subsequences to the original sequence (S2O) manner based on the rolling approach (RA), is utilized to forecast renewable energy variations. RA continuously updates input datasets to improve forecasting accuracy. Decomposition and forecasting modules are employed in an S2O manner to reduce the number of required modules and forecasting cost. The volatility of renewable energy is mitigated by supplementing energy sources with storage. During operation, the conversion times of different energies are reduced by reasonably planning the energy supply sequence based on different loads on the demand side, increasing the energy utilization rate. The proposed multi-objective optimal scheduling strategy includes a stacked multilevel-denoising autoencoder, non-dominated sorting genetic algorithm-II, and deep reinforcement learning (DRL) for surrogate-model building, Pareto frontier establishment, and optimal solution selection. This is the first study to use DRL to select the final optimal solution. A performance comparison confirms the proposed model effectively decreases costs and pollution while increasing thermal comfort.

Suggested Citation

  • Dong, Weichao & Sun, Hexu & Li, Zheng & Yang, Huifang, 2024. "Design and optimal scheduling of forecasting-based campus multi-energy complementary energy system," Energy, Elsevier, vol. 309(C).
  • Handle: RePEc:eee:energy:v:309:y:2024:i:c:s0360544224028639
    DOI: 10.1016/j.energy.2024.133088
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224028639
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2024.133088?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. Wang, Gang & Zhang, Zhen & Lin, Jianqing, 2024. "Multi-energy complementary power systems based on solar energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    2. 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).
    3. Lu, Qing & Liu, Minzhe, 2024. "A multi-criteria compromise ranking decision-making approach for analysis and evaluation of community-integrated energy service system," Energy, Elsevier, vol. 306(C).
    4. Han, Zepeng & Han, Wei & Ye, Yiyin & Sui, Jun, 2024. "Multi-objective sustainability optimization of a solar-based integrated energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 202(C).
    5. Chung, Jun Yeob & Park, Myeong Hyeon & Hong, Seong Ho & Baek, Jaehyun & Han, Changho & Lee, Sewon & Kang, Yong Tae & Kim, Yongchan, 2023. "Comparative performance evaluation of multi-objective optimized desiccant wheels coated with MIL-100 (Fe) and silica gel composite," Energy, Elsevier, vol. 283(C).
    6. Hu, Yahui & Guo, Yingshi & Fu, Rui, 2023. "A novel wind speed forecasting combined model using variational mode decomposition, sparse auto-encoder and optimized fuzzy cognitive mapping network," Energy, Elsevier, vol. 278(PA).
    7. Hu, Huanling & Wang, Lin & Zhang, Dabin & Ling, Liwen, 2023. "Rolling decomposition method in fusion with echo state network for wind speed forecasting," Renewable Energy, Elsevier, vol. 216(C).
    8. Kuriqi, Alban & Pinheiro, António N. & Sordo-Ward, Alvaro & Bejarano, María D. & Garrote, Luis, 2021. "Ecological impacts of run-of-river hydropower plants—Current status and future prospects on the brink of energy transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(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. Amir Shahcheraghian & Adrian Ilinca, 2024. "Advanced Machine Learning Techniques for Energy Consumption Analysis and Optimization at UBC Campus: Correlations with Meteorological Variables," Energies, MDPI, vol. 17(18), pages 1-22, September.
    2. Wang, Yibo & Lin, Ze & Wang, Bowen & Liu, Chuang & Cai, Guowei & Liu, Hongdan & Ge, Junxiong, 2025. "Two-stage day-ahead and intraday low-carbon dispatch method based on enhancing the peak-load regulation capability of cogeneration units with a novel multi-stage Tesla valve thermal storage device," Energy, Elsevier, vol. 316(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. Cai, Chenhao & Zhang, Leyao & Zhou, Jianguo, 2024. "DMPR: A novel wind speed forecasting model based on optimized decomposition, multi-objective feature selection, and patch-based RNN," Energy, Elsevier, vol. 310(C).
    2. Migo-Sumagang, Maria Victoria & Tan, Raymond R. & Aviso, Kathleen B., 2023. "A multi-period model for optimizing negative emission technology portfolios with economic and carbon value discount rates," Energy, Elsevier, vol. 275(C).
    3. Yuan, Peng & Pu, Yuran & Liu, Chang, 2021. "Improving electricity supply reliability in China: Cost and incentive regulation," Energy, Elsevier, vol. 237(C).
    4. Bai, Yun & Deng, Shuyun & Pu, Ziqiang & Li, Chuan, 2024. "Carbon price forecasting using leaky integrator echo state networks with the framework of decomposition-reconstruction-integration," Energy, Elsevier, vol. 305(C).
    5. Yang, Yi & Yuan, Zhuqing & Yang, Shengnan, 2022. "Difference in the drivers of industrial carbon emission costs determines the diverse policies in middle-income regions: A case of northwestern China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    6. Assareh, Ehsanolah & Hoseinzadeh, Siamak & Agarwal, Saurabh & keykhah, Mohammad & Agarwal, Neha & Heydari, Azim & Astiaso Garcia, Davide, 2025. "Assessment of a wind energy installation for powering a residential building in Rome, Italy: Incorporating wind turbines, compressed air energy storage, and a compression chiller based on a machine le," Energy, Elsevier, vol. 320(C).
    7. Li, Yanbin & Hu, Weikun & Zhang, Feng & Li, Yun, 2025. "Multi-objective collaborative operation optimization of park-level integrated energy system clusters considering green power forecasting and trading," Energy, Elsevier, vol. 319(C).
    8. Dzido, Aleksandra & Wołowicz, Marcin & Krawczyk, Piotr, 2022. "Transcritical carbon dioxide cycle as a way to improve the efficiency of a Liquid Air Energy Storage system," Renewable Energy, Elsevier, vol. 196(C), pages 1385-1391.
    9. Yushi Wang & Beining Hu & Xianhai Meng & Runjin Xiao, 2024. "A Comprehensive Review on Technologies for Achieving Zero-Energy Buildings," Sustainability, MDPI, vol. 16(24), pages 1-26, December.
    10. Zhang, Tairan & Sobhani, Behrouz, 2023. "Optimal economic programming of an energy hub in the power system while taking into account the uncertainty of renewable resources, risk-taking and electric vehicles using a developed routing method," Energy, Elsevier, vol. 271(C).
    11. Zhang, Beiyuan & Wang, Jianru & Li, Zhicheng & Gao, Tongtong & Zhang, Weijun & Xu, Chao & Ju, Xing, 2025. "Optimal configuration scheme for multi-hybrid energy storage system containing ground source heat pumps and hydrogen-doped gas turbine," Energy, Elsevier, vol. 321(C).
    12. Paweł Tomczyk & Mirosław Wiatkowski, 2021. "The Effects of Hydropower Plants on the Physicochemical Parameters of the Bystrzyca River in Poland," Energies, MDPI, vol. 14(8), pages 1-29, April.
    13. Alsaleh, Mohd & Abdul-Rahim, A.S., 2022. "The pathway toward pollution mitigation in EU28 region: Does hydropower growth make a difference?," Renewable Energy, Elsevier, vol. 185(C), pages 291-301.
    14. Zhang, Haipeng & Wang, Jianzhou & Qian, Yuansheng & Li, Qiwei, 2024. "Point and interval wind speed forecasting of multivariate time series based on dual-layer LSTM," Energy, Elsevier, vol. 294(C).
    15. Zhao, Zhenyu & Xu, Hanting & Bao, Geriletu, 2025. "Study on energy resource-project mode-load demand chain flexibility adaptation of park-level integrated energy systems," Energy, Elsevier, vol. 320(C).
    16. Morteza Nazari-Heris & Atefeh Tamaskani Esfehankalateh & Pouya Ifaei, 2023. "Hybrid Energy Systems for Buildings: A Techno-Economic-Enviro Systematic Review," Energies, MDPI, vol. 16(12), pages 1-15, June.
    17. Ren, Xiaoxiao & Wang, Jinshi & Yang, Sifan & Zhao, Quanbin & Jia, Yifan & Ou, Kejie & Hu, Guangtao & Yan, Junjie, 2025. "A novel multi-objective Stackelberg game model for multi-energy dynamic pricing and flexible scheduling in distributed multi-energy system," Energy, Elsevier, vol. 325(C).
    18. Jelena Cvijović & Vladimir Obradović & Marija Todorović, 2021. "Stakeholder Management and Project Sustainability—A Throw of the Dice," Sustainability, MDPI, vol. 13(17), pages 1-22, August.
    19. Adam Sulich & Letycja Sołoducho-Pelc, 2021. "Renewable Energy Producers’ Strategies in the Visegrád Group Countries," Energies, MDPI, vol. 14(11), pages 1-21, May.
    20. Qian, Long & Xu, Xiaolin & Sun, Ying & Zhou, Yunjie, 2022. "Carbon emission reduction effects of eco-industrial park policy in China," Energy, Elsevier, vol. 261(PB).

    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:309:y:2024:i:c:s0360544224028639. 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.