IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v236y2021ics0360544221016662.html
   My bibliography  Save this article

An interval scheduling method for the CCHP system containing renewable energy sources based on model predictive control

Author

Listed:
  • Ma, Deyin
  • Zhang, Lizhi
  • Sun, Bo

Abstract

Scheduling strategies are crucial for combined cooling, heating, and power-containing renewable energy source (RES-CCHP) systems to realize cost-effective operation. However, the prediction error generated by renewable energy sources (RES) and load leads to mismatch between the scheduling plan and actual demand. To address this problem, an interval scheduling method is proposed for the RES-CCHP system based on the model predictive control method. A genetic algorithm to optimize a back propagation (GA-BP) neural network combined with historical and weather data is used to predict the multistep RES and load to improve prediction accuracy. An interval optimization model (cost optimization) is then constructed based on RES and load prediction data to achieve an output consistent with the actual situation. Finally, feedback correction is used to compensate the RES and load prediction data online. The prediction error and interval are reduced, thereby improving the performance of the interval optimization method in achieving an optimal solution. This research is applicable to living spaces such as residential areas, schools, and hospitals. In this study, a hospital was considered as a case study to verify the effectiveness of the proposed method. A comparison of the results of the proposed method with those obtained in the following electrical load and following thermal load modes in a typical summer day revealed a cost reduction of 16.21% and 16.92%, respectively. The proposed method can improve the prediction accuracy of the RES and load of the RES-CCHP system and help decision makers to develop reasonable operation schemes and maximize profits.

Suggested Citation

  • Ma, Deyin & Zhang, Lizhi & Sun, Bo, 2021. "An interval scheduling method for the CCHP system containing renewable energy sources based on model predictive control," Energy, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:energy:v:236:y:2021:i:c:s0360544221016662
    DOI: 10.1016/j.energy.2021.121418
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221016662
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.121418?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. Gu, Jihao & Wang, Jin & Qi, Chengying & Min, Chunhua & Sundén, Bengt, 2018. "Medium-term heat load prediction for an existing residential building based on a wireless on-off control system," Energy, Elsevier, vol. 152(C), pages 709-718.
    3. Yu, Feng & Xu, Xiaozhong, 2014. "A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network," Applied Energy, Elsevier, vol. 134(C), pages 102-113.
    4. 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.
    5. Facci, Andrea Luigi & Andreassi, Luca & Ubertini, Stefano, 2014. "Optimization of CHCP (combined heat power and cooling) systems operation strategy using dynamic programming," Energy, Elsevier, vol. 66(C), pages 387-400.
    6. 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.
    7. Zhang, Lizhi & Kuang, Jiyuan & Sun, Bo & Li, Fan & Zhang, Chenghui, 2020. "A two-stage operation optimization method of integrated energy systems with demand response and energy storage," Energy, Elsevier, vol. 208(C).
    8. Su, Yongxin & Zhou, Yao & Tan, Mao, 2020. "An interval optimization strategy of household multi-energy system considering tolerance degree and integrated demand response," Applied Energy, Elsevier, vol. 260(C).
    9. Fang, Fang & Wei, Le & Liu, Jizhen & Zhang, Jianhua & Hou, Guolian, 2012. "Complementary configuration and operation of a CCHP-ORC system," Energy, Elsevier, vol. 46(1), pages 211-220.
    10. Jiyuan Kuang & Chenghui Zhang & Fan Li & Bo Sun, 2018. "Dynamic Optimization of Combined Cooling, Heating, and Power Systems with Energy Storage Units," Energies, MDPI, vol. 11(9), pages 1-16, August.
    11. Zheng Liu & Xin Liu & Kan Wang & Zhongwei Liang & José A.F.O. Correia & Abílio M.P. De Jesus, 2019. "GA-BP Neural Network-Based Strain Prediction in Full-Scale Static Testing of Wind Turbine Blades," Energies, MDPI, vol. 12(6), pages 1-15, March.
    12. Xiaofeng Dong & Chao Quan & Tong Jiang, 2018. "Optimal Planning of Integrated Energy Systems Based on Coupled CCHP," Energies, MDPI, vol. 11(10), pages 1-27, October.
    13. 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).
    14. 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.
    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. Zhou, Yuan & Wang, Jiangjiang & Wei, Changqi & Li, Yuxin, 2024. "A novel two-stage multi-objective dispatch model for a distributed hybrid CCHP system considering source-load fluctuations mitigation," Energy, Elsevier, vol. 300(C).
    2. Yang, Xiaohui & Wang, Xiaopeng & Leng, Zhengyang & Deng, Yeheng & Deng, Fuwei & Zhang, Zhonglian & Yang, Li & Liu, Xiaoping, 2023. "An optimized scheduling strategy combining robust optimization and rolling optimization to solve the uncertainty of RES-CCHP MG," Renewable Energy, Elsevier, vol. 211(C), pages 307-325.
    3. Zhang, Xuehan & Son, Yongju & Cheong, Taesu & Choi, Sungyun, 2022. "Affine-arithmetic-based microgrid interval optimization considering uncertainty and battery energy storage system degradation," Energy, Elsevier, vol. 242(C).
    4. Malte Stienecker & Anne Hagemeier, 2023. "Developing Feedforward Neural Networks as Benchmark for Load Forecasting: Methodology Presentation and Application to Hospital Heat Load Forecasting," Energies, MDPI, vol. 16(4), pages 1-22, February.
    5. Lu, Na & Wang, Guangyan & Su, Chengguo & Ren, Zaimin & Peng, Xiaoyue & Sui, Quan, 2024. "Medium- and long-term interval optimal scheduling of cascade hydropower-photovoltaic complementary systems considering multiple uncertainties," Applied Energy, Elsevier, vol. 353(PA).
    6. Karaaslan, Abdulkerim & Gezen, Mesliha, 2022. "The evaluation of renewable energy resources in Turkey by integer multi-objective selection problem with interval coefficient," Renewable Energy, Elsevier, vol. 182(C), pages 842-854.

    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. Fan Li & Jingxi Su & Bo Sun, 2023. "An Optimal Scheduling Method for an Integrated Energy System Based on an Improved k-Means Clustering Algorithm," Energies, MDPI, vol. 16(9), pages 1-22, April.
    2. Hong-Hai Niu & Yang Zhao & Shang-Shang Wei & Yi-Guo Li, 2021. "A Variable Performance Parameters Temperature–Flowrate Scheduling Model for Integrated Energy Systems," Energies, MDPI, vol. 14(17), pages 1-25, August.
    3. 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.
    4. 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).
    5. 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.
    6. Zhao, Xin & Zheng, Wenyu & Hou, Zhihua & Chen, Heng & Xu, Gang & Liu, Wenyi & Chen, Honggang, 2022. "Economic dispatch of multi-energy system considering seasonal variation based on hybrid operation strategy," Energy, Elsevier, vol. 238(PA).
    7. 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).
    8. Afzali, Sayyed Faridoddin & Mahalec, Vladimir, 2018. "Novel performance curves to determine optimal operation of CCHP systems," Applied Energy, Elsevier, vol. 226(C), pages 1009-1036.
    9. Zhang, Lizhi & Kuang, Jiyuan & Sun, Bo & Li, Fan & Zhang, Chenghui, 2020. "A two-stage operation optimization method of integrated energy systems with demand response and energy storage," Energy, Elsevier, vol. 208(C).
    10. 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.
    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. Chen, Ke & Pan, Ming, 2021. "Operation optimization of combined cooling, heating, and power superstructure system for satisfying demand fluctuation," Energy, Elsevier, vol. 237(C).
    13. Jiyuan Kuang & Chenghui Zhang & Fan Li & Bo Sun, 2018. "Dynamic Optimization of Combined Cooling, Heating, and Power Systems with Energy Storage Units," Energies, MDPI, vol. 11(9), pages 1-16, August.
    14. 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).
    15. 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.
    16. Ghavami, Morteza & Gholizadeh, Mohammad & Deymi-Dashtebayaz, Mahdi, 2023. "Parametric study and optimization analysis of a multi-generation system using waste heat in natural gas refinery- an energy and exergoeconomic analysis," Energy, Elsevier, vol. 272(C).
    17. Kang, Ligai & Yang, Junhong & An, Qingsong & Deng, Shuai & Zhao, Jun & Wang, Hui & Li, Zelin, 2017. "Effects of load following operational strategy on CCHP system with an auxiliary ground source heat pump considering carbon tax and electricity feed in tariff," Applied Energy, Elsevier, vol. 194(C), pages 454-466.
    18. Zhang, Han & Han, Zhonghe & Wu, Di & Li, Peng & Li, Peng, 2023. "Energy optimization and performance analysis of a novel integrated energy system coupled with solar thermal unit and preheated organic cycle under extended following electric load strategy," Energy, Elsevier, vol. 272(C).
    19. 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.
    20. 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).

    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:236:y:2021:i:c:s0360544221016662. 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.