IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v227y2021ics036054422100709x.html
   My bibliography  Save this article

Optimal coordination strategy for multiple distributed energy systems considering supply, demand, and price uncertainties

Author

Listed:
  • Li, Longxi
  • Cao, Xilin
  • Wang, Peng

Abstract

Facing a significant increase in connected distributed energy systems, the optimal coordination strategy among multiple distributed energy systems is vitally important to explore. In this paper, an energy management system is introduced and operated by an energy service company, which is responsible for managing the interaction of multiple distributed energy systems. To optimize the day-ahead scheduling of the distributed energy systems, a coordination scheme with a bilevel framework is proposed. The energy interaction between the energy management system and distributed energy systems contains electricity and heat, which is a Stackelberg problem. Two types of internal price schemes, namely, real-time pricing and time-of-use pricing, are discussed. Moreover, the uncertainties of renewable energy resources, energy demand, and energy prices are considered within both upper- and lower-level problems. The problem is formulated as a nonlinear bilevel robust optimization model and transformed into a single-level mixed-integer linear problem. Numerical cases illustrate how the energy management system coordinates with distributed energy systems and show the effectiveness of the coordination strategy such that all participators benefit from the proposed strategy and create a win-win situation. The model and results can serve as references for the business managers of companies that provide energy services for building clusters.

Suggested Citation

  • Li, Longxi & Cao, Xilin & Wang, Peng, 2021. "Optimal coordination strategy for multiple distributed energy systems considering supply, demand, and price uncertainties," Energy, Elsevier, vol. 227(C).
    • Handle: RePEc:eee:energy:v:227:y:2021:i:c:s036054422100709x
    DOI: 10.1016/j.energy.2021.120460
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422100709X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.120460?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. Bui, Van-Hai & Hussain, Akhtar & Im, Yong-Hoon & Kim, Hak-Man, 2019. "An internal trading strategy for optimal energy management of combined cooling, heat and power in building microgrids," Applied Energy, Elsevier, vol. 239(C), pages 536-548.
    2. Jalali, Mehdi & Zare, Kazem & Seyedi, Heresh, 2017. "Strategic decision-making of distribution network operator with multi-microgrids considering demand response program," Energy, Elsevier, vol. 141(C), pages 1059-1071.
    3. Won-Poong Lee & Jin-Young Choi & Dong-Jun Won, 2017. "Coordination Strategy for Optimal Scheduling of Multiple Microgrids Based on Hierarchical System," Energies, MDPI, vol. 10(9), pages 1-18, September.
    4. Balouka, Noemie & Cohen, Izack, 2021. "A robust optimization approach for the multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 291(2), pages 457-470.
    5. Mehleri, E.D. & Sarimveis, H. & Markatos, N.C. & Papageorgiou, L.G., 2013. "Optimal design and operation of distributed energy systems: Application to Greek residential sector," Renewable Energy, Elsevier, vol. 51(C), pages 331-342.
    6. Jakubovskis, Aldis, 2017. "Strategic facility location, capacity acquisition, and technology choice decisions under demand uncertainty: Robust vs. non-robust optimization approaches," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1095-1104.
    7. 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.
    8. 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.
    9. Gazijahani, Farhad Samadi & Salehi, Javad, 2018. "Reliability constrained two-stage optimization of multiple renewable-based microgrids incorporating critical energy peak pricing demand response program using robust optimization approach," Energy, Elsevier, vol. 161(C), pages 999-1015.
    10. Wang, Luhao & Li, Qiqiang & Ding, Ran & Sun, Mingshun & Wang, Guirong, 2017. "Integrated scheduling of energy supply and demand in microgrids under uncertainty: A robust multi-objective optimization approach," Energy, Elsevier, vol. 130(C), pages 1-14.
    11. Nan Zhou & Nina Khanna & Wei Feng & Jing Ke & Mark Levine, 2018. "Scenarios of energy efficiency and CO2 emissions reduction potential in the buildings sector in China to year 2050," Nature Energy, Nature, vol. 3(11), pages 978-984, November.
    12. Manfren, Massimiliano & Caputo, Paola & Costa, Gaia, 2011. "Paradigm shift in urban energy systems through distributed generation: Methods and models," Applied Energy, Elsevier, vol. 88(4), pages 1032-1048, April.
    13. Xu, Xiandong & Jia, Hongjie & Wang, Dan & Yu, David C. & Chiang, Hsiao-Dong, 2015. "Hierarchical energy management system for multi-source multi-product microgrids," Renewable Energy, Elsevier, vol. 78(C), pages 621-630.
    14. Aharon Ben-Tal & Boaz Golany & Arkadi Nemirovski & Jean-Philippe Vial, 2005. "Retailer-Supplier Flexible Commitments Contracts: A Robust Optimization Approach," Manufacturing & Service Operations Management, INFORMS, vol. 7(3), pages 248-271, February.
    15. Li, Peng & Wang, Zixuan & Yang, Weihong & Liu, Haitao & Yin, Yunxing & Wang, Jiahao & Guo, Tianyu, 2021. "Hierarchically partitioned coordinated operation of distributed integrated energy system based on a master-slave game," Energy, Elsevier, vol. 214(C).
    16. Zhou, Xiaoqian & Ai, Qian & Yousif, Muhammad, 2019. "Two kinds of decentralized robust economic dispatch framework combined distribution network and multi-microgrids," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    17. Wolsink, Maarten, 2020. "Distributed energy systems as common goods: Socio-political acceptance of renewables in intelligent microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    18. Gabriel, Steven A. & Leuthold, Florian U., 2010. "Solving discretely-constrained MPEC problems with applications in electric power markets," Energy Economics, Elsevier, vol. 32(1), pages 3-14, January.
    19. von Appen, J. & Braun, M., 2018. "Strategic decision making of distribution network operators and investors in residential photovoltaic battery storage systems," Applied Energy, Elsevier, vol. 230(C), pages 540-550.
    20. van Ackooij, Wim & De Boeck, Jérôme & Detienne, Boris & Pan, Stefania & Poss, Michael, 2018. "Optimizing power generation in the presence of micro-grids," European Journal of Operational Research, Elsevier, vol. 271(2), pages 450-461.
    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. Yuan, Guanxiu & Gao, Yan & Ye, Bei, 2021. "Optimal dispatching strategy and real-time pricing for multi-regional integrated energy systems based on demand response," Renewable Energy, Elsevier, vol. 179(C), pages 1424-1446.
    2. Wang, Hao-ran & Feng, Tian-tian & Xiong, Wei, 2022. "How can the dynamic game be integrated into blockchain-based distributed energy resources multi-agent transactions for decision-making?," Energy, Elsevier, vol. 254(PB).
    3. Nawaz, Arshad & Zhou, Min & Wu, Jing & Long, Chengnian, 2022. "A comprehensive review on energy management, demand response, and coordination schemes utilization in multi-microgrids network," Applied Energy, Elsevier, vol. 323(C).
    4. Ma, Huan & Sun, Qinghan & Chen, Qun & Zhao, Tian & He, Kelun, 2023. "Exergy-based flexibility cost indicator and spatio-temporal coordination principle of distributed multi-energy systems," Energy, Elsevier, vol. 267(C).
    5. Deng, Zhipeng & Wang, Xuezheng & Dong, Bing, 2023. "Quantum computing for future real-time building HVAC controls," Applied Energy, Elsevier, vol. 334(C).
    6. Dong, Xiangxiang & Wu, Jiang & Xu, Zhanbo & Liu, Kun & Guan, Xiaohong, 2022. "Optimal coordination of hydrogen-based integrated energy systems with combination of hydrogen and water storage," Applied Energy, Elsevier, vol. 308(C).
    7. Dong, Zihang & Zhang, Xi & Strbac, Goran, 2021. "Evaluation of benefits through coordinated control of numerous thermal energy storage in highly electrified heat systems," Energy, Elsevier, vol. 237(C).
    8. Yin, WanJun & Ming, ZhengFeng & Wen, Tao, 2021. "Scheduling strategy of electric vehicle charging considering different requirements of grid and users," Energy, Elsevier, vol. 232(C).
    9. Zhou, Kaile & Chu, Yibo & Hu, Rong, 2023. "Energy supply-demand interaction model integrating uncertainty forecasting and peer-to-peer energy trading," Energy, Elsevier, vol. 285(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. Longxi Li, 2020. "Optimal Coordination Strategies for Load Service Entity and Community Energy Systems Based on Centralized and Decentralized Approaches," Energies, MDPI, vol. 13(12), pages 1-22, June.
    2. Maarten Wolsink, 2020. "Framing in Renewable Energy Policies: A Glossary," Energies, MDPI, vol. 13(11), pages 1-31, June.
    3. Li, Ruonan & Mahalec, Vladimir, 2022. "Integrated design and operation of energy systems for residential buildings, commercial buildings, and light industries," Applied Energy, Elsevier, vol. 305(C).
    4. Wouters, Carmen & Fraga, Eric S. & James, Adrian M., 2015. "An energy integrated, multi-microgrid, MILP (mixed-integer linear programming) approach for residential distributed energy system planning – A South Australian case-study," Energy, Elsevier, vol. 85(C), pages 30-44.
    5. Omu, Akomeno & Choudhary, Ruchi & Boies, Adam, 2013. "Distributed energy resource system optimisation using mixed integer linear programming," Energy Policy, Elsevier, vol. 61(C), pages 249-266.
    6. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    7. Kang, Jing & Wang, Shengwei & Yan, Chengchu, 2019. "A new distributed energy system configuration for cooling dominated districts and the performance assessment based on real site measurements," Renewable Energy, Elsevier, vol. 131(C), pages 390-403.
    8. Hosseinnia, Hamed & Modarresi, Javad & Nazarpour, Daryoush, 2020. "Optimal eco-emission scheduling of distribution network operator and distributed generator owner under employing demand response program," Energy, Elsevier, vol. 191(C).
    9. Ren, Fukang & Lin, Xiaozhen & Wei, Ziqing & Zhai, Xiaoqiang & Yang, Jianrong, 2022. "A novel planning method for design and dispatch of hybrid energy systems," Applied Energy, Elsevier, vol. 321(C).
    10. Xu, Bin & Luo, Yuemei & Xu, Renjing & Chen, Jianbao, 2021. "Exploring the driving forces of distributed energy resources in China: Using a semiparametric regression model," Energy, Elsevier, vol. 236(C).
    11. Li, Ruonan & Mhaskar, Prashant & Mahalec, Vladimir, 2021. "Integration of energy systems for buildings and light industrial plants," Energy, Elsevier, vol. 233(C).
    12. Tostado-Véliz, Marcos & Hasanien, Hany M. & Jordehi, Ahmad Rezaee & Turky, Rania A. & Jurado, Francisco, 2023. "Risk-averse optimal participation of a DR-intensive microgrid in competitive clusters considering response fatigue," Applied Energy, Elsevier, vol. 339(C).
    13. Yifang Tang & Zhiqiang Liu & Lan Li, 2019. "Performance Comparison of a Distributed Energy System under Different Control Strategies with a Conventional Energy System," Energies, MDPI, vol. 12(24), pages 1-17, December.
    14. Di Somma, M. & Yan, B. & Bianco, N. & Graditi, G. & Luh, P.B. & Mongibello, L. & Naso, V., 2017. "Multi-objective design optimization of distributed energy systems through cost and exergy assessments," Applied Energy, Elsevier, vol. 204(C), pages 1299-1316.
    15. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    16. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2022. "A review on the integration and optimization of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    17. Tostado-Véliz, Marcos & Hasanien, Hany M. & Rezaee Jordehi, Ahmad & Turky, Rania A. & Gómez-González, Manuel & Jurado, Francisco, 2023. "An Interval-based privacy – Aware optimization framework for electricity price setting in isolated microgrid clusters," Applied Energy, Elsevier, vol. 340(C).
    18. Pina, Eduardo A. & Lozano, Miguel A. & Serra, Luis M., 2021. "Assessing the influence of legal constraints on the integration of renewable energy technologies in polygeneration systems for buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    19. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimization framework for distributed energy systems with integrated electrical grid constraints," Applied Energy, Elsevier, vol. 171(C), pages 296-313.
    20. Liu, Liuchen & Cui, Guomin & Chen, Jiaxing & Huang, Xiaohuang & Li, Di, 2022. "Two-stage superstructure model for optimization of distributed energy systems (DES) part I: Model development and verification," Energy, Elsevier, vol. 245(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:227:y:2021:i:c:s036054422100709x. 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.