IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v84y2015icp759-773.html
   My bibliography  Save this article

A collaborative operation decision model for distributed building clusters

Author

Listed:
  • Dai, Rui
  • Hu, Mengqi
  • Yang, Dong
  • Chen, Yang

Abstract

In the context of smart grid, the building can freely connect with other buildings to form clusters which are termed as building clusters to share energy. However, less study is conducted to develop optimal operation strategy for building clusters and evaluate the performance of building clusters in terms of different measures under different operation modes. Therefore, this research proposes a collaborative decision model to study the energy exchange among building clusters where the buildings share a combined cooling, heating and power system, thermal storage, and battery, and each building aims to minimize its energy cost, carbon emission or primary energy consumption. A collaborative decision framework is proposed to obtain Pareto operation decisions for the building clusters. We compare the performance of the collaborative strategy with the non-cooperative strategy where no energy sharing among the buildings. It is demonstrated that the collaborative strategy can significantly reduce energy cost, carbon emission and primary energy consumption under both grid connected and disconnected operation modes. The collaborative strategy under dynamic pricing plan is more cost effective than the strategy under flat pricing plan, which indicates that the collaborative strategy can motive buildings to more efficiently utilize the shared energy under dynamic pricing plan.

Suggested Citation

  • Dai, Rui & Hu, Mengqi & Yang, Dong & Chen, Yang, 2015. "A collaborative operation decision model for distributed building clusters," Energy, Elsevier, vol. 84(C), pages 759-773.
  • Handle: RePEc:eee:energy:v:84:y:2015:i:c:p:759-773
    DOI: 10.1016/j.energy.2015.03.042
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544215003369
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2015.03.042?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. Wu, J.Y. & Wang, J.L. & Li, S. & Wang, R.Z., 2014. "Experimental and simulative investigation of a micro-CCHP (micro combined cooling, heating and power) system with thermal management controller," Energy, Elsevier, vol. 68(C), pages 444-453.
    2. Lee, Wen-Shing & Chen, Yi -Ting & Wu, Ting-Hau, 2009. "Optimization for ice-storage air-conditioning system using particle swarm algorithm," Applied Energy, Elsevier, vol. 86(9), pages 1589-1595, September.
    3. Hu, Mengqi & Cho, Heejin, 2014. "A probability constrained multi-objective optimization model for CCHP system operation decision support," Applied Energy, Elsevier, vol. 116(C), pages 230-242.
    4. Hu, Mengqi & Weir, Jeffery D. & Wu, Teresa, 2012. "Decentralized operation strategies for an integrated building energy system using a memetic algorithm," European Journal of Operational Research, Elsevier, vol. 217(1), pages 185-197.
    5. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2013. "Economic and environmental optimization model for the design and the operation of a combined heat and power distributed generation system in an urban area," Energy, Elsevier, vol. 55(C), pages 1014-1024.
    6. Manolakos, D & Papadakis, G & Papantonis, D & Kyritsis, S, 2001. "A simulation-optimisation programme for designing hybrid energy systems for supplying electricity and fresh water through desalination to remote areas," Energy, Elsevier, vol. 26(7), pages 679-704.
    7. Bianchi, M. & De Pascale, A. & Melino, F., 2013. "Performance analysis of an integrated CHP system with thermal and Electric Energy Storage for residential application," Applied Energy, Elsevier, vol. 112(C), pages 928-938.
    8. 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.
    9. Maraver, Daniel & Sin, Ana & Sebastián, Fernando & Royo, Javier, 2013. "Environmental assessment of CCHP (combined cooling heating and power) systems based on biomass combustion in comparison to conventional generation," Energy, Elsevier, vol. 57(C), pages 17-23.
    10. Bischi, Aldo & Taccari, Leonardo & Martelli, Emanuele & Amaldi, Edoardo & Manzolini, Giampaolo & Silva, Paolo & Campanari, Stefano & Macchi, Ennio, 2014. "A detailed MILP optimization model for combined cooling, heat and power system operation planning," Energy, Elsevier, vol. 74(C), pages 12-26.
    11. Wu, Jing-yi & Wang, Jia-long & Li, Sheng, 2012. "Multi-objective optimal operation strategy study of micro-CCHP system," Energy, Elsevier, vol. 48(1), pages 472-483.
    12. Jones, D. F. & Mirrazavi, S. K. & Tamiz, M., 2002. "Multi-objective meta-heuristics: An overview of the current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 137(1), pages 1-9, February.
    13. Ebrahimi, Masood & Keshavarz, Ali, 2013. "Sizing the prime mover of a residential micro-combined cooling heating and power (CCHP) system by multi-criteria sizing method for different climates," Energy, Elsevier, vol. 54(C), pages 291-301.
    14. Cho, Heejin & Mago, Pedro J. & Luck, Rogelio & Chamra, Louay M., 2009. "Evaluation of CCHP systems performance based on operational cost, primary energy consumption, and carbon dioxide emission by utilizing an optimal operation scheme," Applied Energy, Elsevier, vol. 86(12), pages 2540-2549, December.
    15. Xu, Jianzhong & Sui, Jun & Li, Bingyu & Yang, Minlin, 2010. "Research, development and the prospect of combined cooling, heating, and power systems," Energy, Elsevier, vol. 35(11), pages 4361-4367.
    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. Chen, Yang & Hu, Mengqi, 2016. "Balancing collective and individual interests in transactive energy management of interconnected micro-grid clusters," Energy, Elsevier, vol. 109(C), pages 1075-1085.
    2. Gomez-Herrera, Juan A. & Anjos, Miguel F., 2018. "Optimal collaborative demand-response planner for smart residential buildings," Energy, Elsevier, vol. 161(C), pages 370-380.
    3. Hoarau, Quentin & Perez, Yannick, 2018. "Interactions between electric mobility and photovoltaic generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 510-522.
    4. Kuang, Yanqing & Chen, Yang & Hu, Mengqi & Yang, Dong, 2017. "Influence analysis of driver behavior and building category on economic performance of electric vehicle to grid and building integration," Applied Energy, Elsevier, vol. 207(C), pages 427-437.
    5. Alqahtani, Mohammed & Hu, Mengqi, 2022. "Dynamic energy scheduling and routing of multiple electric vehicles using deep reinforcement learning," Energy, Elsevier, vol. 244(PA).
    6. Walker, Shalika & Labeodan, Timilehin & Boxem, Gert & Maassen, Wim & Zeiler, Wim, 2018. "An assessment methodology of sustainable energy transition scenarios for realizing energy neutral neighborhoods," Applied Energy, Elsevier, vol. 228(C), pages 2346-2360.
    7. Ding, Yan & Wang, Qiaochu & Tian, Zhe & Lyu, Yacong & Li, Feng & Yan, Zhe & Xia, Xi, 2023. "A graph-theory-based dynamic programming planning method for distributed energy system planning: Campus area as a case study," Applied Energy, Elsevier, vol. 329(C).
    8. Xiaolin Chu & Yuntian Ge & Xue Zhou & Lin Li & Dong Yang, 2020. "Modeling and Analysis of Electric Vehicle-Power Grid-Manufacturing Facility (EPM) Energy Sharing System under Time-of-Use Electricity Tariff," Sustainability, MDPI, vol. 12(12), pages 1-27, June.
    9. Li, Miao & Mu, Hailin & Li, Nan & Ma, Baoyu, 2016. "Optimal design and operation strategy for integrated evaluation of CCHP (combined cooling heating and power) system," Energy, Elsevier, vol. 99(C), pages 202-220.
    10. Ji, Ling & Huang, Guohe & Xie, Yulei & Zhou, Yong & Zhou, Jifang, 2018. "Robust cost-risk tradeoff for day-ahead schedule optimization in residential microgrid system under worst-case conditional value-at-risk consideration," Energy, Elsevier, vol. 153(C), pages 324-337.
    11. Alqahtani, Mohammed & Hu, Mengqi, 2020. "Integrated energy scheduling and routing for a network of mobile prosumers," Energy, Elsevier, vol. 200(C).
    12. Xiaolin Chu & Dong Yang & Jia Li, 2019. "Sustainability Assessment of Combined Cooling, Heating, and Power Systems under Carbon Emission Regulations," Sustainability, MDPI, vol. 11(21), pages 1-17, October.

    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, 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.
    2. Ju, Liwei & Tan, Zhongfu & Li, Huanhuan & Tan, Qingkun & Yu, Xiaobao & Song, Xiaohua, 2016. "Multi-objective operation optimization and evaluation model for CCHP and renewable energy based hybrid energy system driven by distributed energy resources in China," Energy, Elsevier, vol. 111(C), pages 322-340.
    3. Li, Miao & Mu, Hailin & Li, Nan & Ma, Baoyu, 2016. "Optimal design and operation strategy for integrated evaluation of CCHP (combined cooling heating and power) system," Energy, Elsevier, vol. 99(C), pages 202-220.
    4. Chen, Yang & Hu, Mengqi, 2016. "Balancing collective and individual interests in transactive energy management of interconnected micro-grid clusters," Energy, Elsevier, vol. 109(C), pages 1075-1085.
    5. Cho, Heejin & Smith, Amanda D. & Mago, Pedro, 2014. "Combined cooling, heating and power: A review of performance improvement and optimization," Applied Energy, Elsevier, vol. 136(C), pages 168-185.
    6. Zhu, Xu & Yang, Jun & Pan, Xueli & Li, Gaojunjie & Rao, Yingqing, 2020. "Regional integrated energy system energy management in an industrial park considering energy stepped utilization," Energy, Elsevier, vol. 201(C).
    7. Li, Minzhi & Jiang, Xi Zhuo & Zheng, Danxing & Zeng, Guangbiao & Shi, Lin, 2016. "Thermodynamic boundaries of energy saving in conventional CCHP (Combined Cooling, Heating and Power) systems," Energy, Elsevier, vol. 94(C), pages 243-249.
    8. Tian, Zhe & Niu, Jide & Lu, Yakai & He, Shunming & Tian, Xue, 2016. "The improvement of a simulation model for a distributed CCHP system and its influence on optimal operation cost and strategy," Applied Energy, Elsevier, vol. 165(C), pages 430-444.
    9. Wang, Jialong & Wu, Jingyin & Wang, Hongbin, 2015. "Experimental investigation of a dual-source powered absorption chiller based on gas engine waste heat and solar thermal energy," Energy, Elsevier, vol. 88(C), pages 680-689.
    10. Zhu, Xingyi & Zhan, Xiangyan & Liang, Hao & Zheng, Xuyue & Qiu, Yuwei & Lin, Jian & Chen, Jincan & Meng, Chao & Zhao, Yingru, 2020. "The optimal design and operation strategy of renewable energy-CCHP coupled system applied in five building objects," Renewable Energy, Elsevier, vol. 146(C), pages 2700-2715.
    11. Dorotić, Hrvoje & Pukšec, Tomislav & Duić, Neven, 2019. "Multi-objective optimization of district heating and cooling systems for a one-year time horizon," Energy, Elsevier, vol. 169(C), pages 319-328.
    12. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
    13. Hu, Mengqi, 2015. "A data-driven feed-forward decision framework for building clusters operation under uncertainty," Applied Energy, Elsevier, vol. 141(C), pages 229-237.
    14. 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.
    15. Li, Longxi & Mu, Hailin & Li, Nan & Li, Miao, 2016. "Economic and environmental optimization for distributed energy resource systems coupled with district energy networks," Energy, Elsevier, vol. 109(C), pages 947-960.
    16. Lizhi Zhang & Fan Li & Bo Sun & Chenghui Zhang, 2019. "Integrated Optimization Design of Combined Cooling, Heating, and Power System Coupled with Solar and Biomass Energy," Energies, MDPI, vol. 12(4), pages 1-21, February.
    17. Wang, Zefeng & Han, Wei & Zhang, Na & Liu, Meng & Jin, Hongguang, 2017. "Effect of an alternative operating strategy for gas turbine on a combined cooling heating and power system," Applied Energy, Elsevier, vol. 205(C), pages 163-172.
    18. 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.
    19. 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).
    20. Wang, Jiang-Jiang & Fu, Chao & Yang, Kun & Zhang, Xu-Tao & Shi, Guo-hua & Zhai, John, 2013. "Reliability and availability analysis of redundant BCHP (building cooling, heating and power) system," Energy, Elsevier, vol. 61(C), pages 531-540.

    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:84:y:2015:i:c:p:759-773. 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.