IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i9p5322-d804485.html
   My bibliography  Save this article

Tri-Level Integrated Optimization Design Method of a CCHP Microgrid with Composite Energy Storage

Author

Listed:
  • Yi Yan

    (Shandong Key Laboratory of Intelligent Buildings Technology, School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China)

  • Xuerui Wang

    (Shandong Key Laboratory of Intelligent Buildings Technology, School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China)

  • Ke Li

    (School of Control Science and Engineering, Shandong University, Jingshi Road 17923, Jinan 250061, China)

  • Xiaopeng Kang

    (School of Control Science and Engineering, Shandong University, Jingshi Road 17923, Jinan 250061, China)

  • Weizheng Kong

    (State Grid Energy Research Institute Co., Ltd., Binhe 18#, Beiqijia, Changping District, Beijing 102209, China)

  • Hongcai Dai

    (State Grid Energy Research Institute Co., Ltd., Binhe 18#, Beiqijia, Changping District, Beijing 102209, China)

Abstract

Combined cooling, heating, and power (CCHP) microgrids are important means of solving the energy crisis and environmental problems. Multidimensional composite energy storage systems (CESSs) are vital to promoting the absorption of distributed renewable energy using CCHP microgrids and improving the level of energy cascade utilization. In this context, this paper proposes a multi-energy coupling structure that includes a multidimensional CESS with a compressed air energy storage (CAES) connected to a CCHP microgrid. Dividing design and operation causes some problems, such as low operating efficiency and difficult energy matching of CESSs. To solve the existing problems, an integrated design method is proposed that considers the capacity configuration of the equipment and the optimal operation of the system on a multi-timescale. The optimization result of the capacity configuration level is used as the constraint of the operational control level, and the equipment output plan of the operational control level is used as the optimized operation strategy and parameters of the system. The C-NSGA-II algorithm is adopted at the capacity configuration level and day-ahead scheduling level. Rolling optimization is solved using the PSO algorithm. The final result that satisfied the output design was obtained after several iterations. The average daily cost and CO 2 emission reduction rate ( CO 2 ERR) of capacity configuration levels are $2241 and 45.02%. The best CO 2 ERRs of day-ahead scheduling optimization levels are 39.9% and 45.9% in summer and winter, where the operating cost saving rate (OCSR) are 30.5% and 38.3% separately. Examples show that the integrated design method presented in this paper has significant advantages in enhancing energy-grade matching and improving the economy and environmental protection of the system.

Suggested Citation

  • Yi Yan & Xuerui Wang & Ke Li & Xiaopeng Kang & Weizheng Kong & Hongcai Dai, 2022. "Tri-Level Integrated Optimization Design Method of a CCHP Microgrid with Composite Energy Storage," Sustainability, MDPI, vol. 14(9), pages 1-29, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5322-:d:804485
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/9/5322/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/9/5322/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bartolini, Andrea & Carducci, Francesco & Muñoz, Carlos Boigues & Comodi, Gabriele, 2020. "Energy storage and multi energy systems in local energy communities with high renewable energy penetration," Renewable Energy, Elsevier, vol. 159(C), pages 595-609.
    2. Balsamo, Flavio & Capasso, Clemente & Lauria, Davide & Veneri, Ottorino, 2020. "Optimal design and energy management of hybrid storage systems for marine propulsion applications," Applied Energy, Elsevier, vol. 278(C).
    3. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhai, Zhiqiang (John), 2011. "Performance comparison of combined cooling heating and power system in different operation modes," Applied Energy, Elsevier, vol. 88(12), pages 4621-4631.
    4. 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.
    5. Zhang, Yi & Xu, Yujie & Guo, Huan & Zhang, Xinjing & Guo, Cong & Chen, Haisheng, 2018. "A hybrid energy storage system with optimized operating strategy for mitigating wind power fluctuations," Renewable Energy, Elsevier, vol. 125(C), pages 121-132.
    6. Sun, Lingling & Qiu, Jing & Han, Xiao & Yin, Xia & Dong, Zhao Yang, 2020. "Capacity and energy sharing platform with hybrid energy storage system: An example of hospitality industry," Applied Energy, Elsevier, vol. 280(C).
    7. He, Yi & Guo, Su & Zhou, Jianxu & Ye, Jilei & Huang, Jing & Zheng, Kun & Du, Xinru, 2022. "Multi-objective planning-operation co-optimization of renewable energy system with hybrid energy storages," Renewable Energy, Elsevier, vol. 184(C), pages 776-790.
    8. Yan, Yi & Zhang, Chenghui & Li, Ke & Wang, Zhen, 2018. "An integrated design for hybrid combined cooling, heating and power system with compressed air energy storage," Applied Energy, Elsevier, vol. 210(C), pages 1151-1166.
    9. Chao Ma & Sen Dong & Jijian Lian & Xiulan Pang, 2019. "Multi-Objective Sizing of Hybrid Energy Storage System for Large-Scale Photovoltaic Power Generation System," Sustainability, MDPI, vol. 11(19), pages 1-15, October.
    10. Kazagic, Anes & Merzic, Ajla & Redzic, Elma & Tresnjo, Dino, 2019. "Optimization of modular district heating solution based on CHP and RES - Demonstration case of the Municipality of Visoko," Energy, Elsevier, vol. 181(C), pages 56-65.
    11. 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.
    12. Houssainy, Sammy & Janbozorgi, Mohammad & Ip, Peggy & Kavehpour, Pirouz, 2018. "Thermodynamic analysis of a high temperature hybrid compressed air energy storage (HTH-CAES) system," Renewable Energy, Elsevier, vol. 115(C), pages 1043-1054.
    13. Zhang, Yuan & Yang, Ke & Li, Xuemei & Xu, Jianzhong, 2013. "The thermodynamic effect of air storage chamber model on Advanced Adiabatic Compressed Air Energy Storage System," Renewable Energy, Elsevier, vol. 57(C), pages 469-478.
    14. Zhou, Shenghui & He, Yang & Chen, Haisheng & Xu, Yujie & Deng, Jianqiang, 2020. "Performance analysis of a novel adiabatic compressed air energy system with ejectors enhanced charging process," Energy, Elsevier, vol. 205(C).
    15. Zhang, Yuan & Yang, Ke & Li, Xuemei & Xu, Jianzhong, 2013. "The thermodynamic effect of thermal energy storage on compressed air energy storage system," Renewable Energy, Elsevier, vol. 50(C), pages 227-235.
    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. Guo, Jiacheng & Liu, Zhijian & Wu, Xuan & Wu, Di & Zhang, Shicong & Yang, Xinyan & Ge, Hua & Zhang, Peiwen, 2022. "Two-layer co-optimization method for a distributed energy system combining multiple energy storages," Applied Energy, Elsevier, vol. 322(C).
    2. Li, Peng & Hu, Qingya & Han, Zhonghe & Wang, Changxin & Wang, Runxia & Han, Xu & Wang, Yongzhen, 2022. "Thermodynamic analysis and multi-objective optimization of a trigenerative system based on compressed air energy storage under different working media and heating storage media," Energy, Elsevier, vol. 239(PD).
    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. Yan, Yi & Zhang, Chenghui & Li, Ke & Wang, Zhen, 2018. "An integrated design for hybrid combined cooling, heating and power system with compressed air energy storage," Applied Energy, Elsevier, vol. 210(C), pages 1151-1166.
    5. 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).
    6. Karellas, S. & Tzouganatos, N., 2014. "Comparison of the performance of compressed-air and hydrogen energy storage systems: Karpathos island case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 865-882.
    7. Liu, Jin-Long & Wang, Jian-Hua, 2015. "Thermodynamic analysis of a novel tri-generation system based on compressed air energy storage and pneumatic motor," Energy, Elsevier, vol. 91(C), pages 420-429.
    8. Fu, Hailun & He, Qing & Song, Jintao & Shi, Xinping & Hao, Yinping & Du, Dongmei & Liu, Wenyi, 2021. "Thermodynamic of a novel advanced adiabatic compressed air energy storage system with variable pressure ratio coupled organic rankine cycle," Energy, Elsevier, vol. 227(C).
    9. Wang, Lu & Gu, Wei & Wu, Zhi & Qiu, Haifeng & Pan, Guangsheng, 2020. "Non-cooperative game-based multilateral contract transactions in power-heating integrated systems," Applied Energy, Elsevier, vol. 268(C).
    10. Liu, Zhan & Yang, Xuqing & Liu, Xu & Wang, Wenbin & Yang, Xiaohu, 2021. "Evaluation of a trigeneration system based on adiabatic compressed air energy storage and absorption heat pump: Thermodynamic analysis," Applied Energy, Elsevier, vol. 300(C).
    11. Zhou, Qian & Du, Dongmei & Lu, Chang & He, Qing & Liu, Wenyi, 2019. "A review of thermal energy storage in compressed air energy storage system," Energy, Elsevier, vol. 188(C).
    12. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2021. "Integrating renewables into stand-alone hybrid systems meeting electric, heating, and cooling loads: A case study," Renewable Energy, Elsevier, vol. 180(C), pages 1222-1236.
    13. Rouindej, Kamyar & Samadani, Ehsan & Fraser, Roydon A., 2020. "A comprehensive data-driven study of electrical power grid and its implications for the design, performance, and operational requirements of adiabatic compressed air energy storage systems," Applied Energy, Elsevier, vol. 257(C).
    14. Liu, Zhan & Liu, Xu & Yang, Shanju & Hooman, Kamel & Yang, Xiaohu, 2021. "Assessment evaluation of a trigeneration system incorporated with an underwater compressed air energy storage," Applied Energy, Elsevier, vol. 303(C).
    15. Dib, Ghady & Haberschill, Philippe & Rullière, Romuald & Perroit, Quentin & Davies, Simon & Revellin, Rémi, 2020. "Thermodynamic simulation of a micro advanced adiabatic compressed air energy storage for building application," Applied Energy, Elsevier, vol. 260(C).
    16. Huang, Hongxu & Liang, Rui & Lv, Chaoxian & Lu, Mengtian & Gong, Dunwei & Yin, Shulin, 2021. "Two-stage robust stochastic scheduling for energy recovery in coal mine integrated energy system," Applied Energy, Elsevier, vol. 290(C).
    17. Ghersi, Djamal Eddine & Amoura, Meriem & Loubar, Khaled & Desideri, Umberto & Tazerout, Mohand, 2021. "Multi-objective optimization of CCHP system with hybrid chiller under new electric load following operation strategy," Energy, Elsevier, vol. 219(C).
    18. Liu, Qingshan & Liu, Yingwen & Liu, Hongjiang & He, Zhilong & Xue, Xiaodai, 2022. "Comprehensive assessment and performance enhancement of compressed air energy storage: thermodynamic effect of ambient temperature," Renewable Energy, Elsevier, vol. 196(C), pages 84-98.
    19. Zhao, Xinyu & Yang, Sheng & Liu, Zhanjun & Wang, Deqiang & Du, Zengzhi & Ren, Jingzheng, 2024. "Optimization and exergoeconomic analysis of a solar-powered ORC-VCR-CCHP system based on a ternary refrigerant selection model," Energy, Elsevier, vol. 290(C).
    20. Roos, P. & Haselbacher, A., 2022. "Analytical modeling of advanced adiabatic compressed air energy storage: Literature review and new models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(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:gam:jsusta:v:14:y:2022:i:9:p:5322-:d:804485. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.