IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v297y2021ics0306261921005523.html
   My bibliography  Save this article

Coordinated operation and expansion planning for multiple microgrids and active distribution networks under uncertainties

Author

Listed:
  • Pinto, Rafael S.
  • Unsihuay-Vila, Clodomiro
  • Tabarro, Fabricio H.

Abstract

Power systems have incorporated many new technologies in recent years and the introduction of energy storage systems and demand response provides additional challenges for their operation and expansion planning. Current distribution networks are complex active networks where many technologies are included, which must be considered and properly represented in expansion planning models. Thus, this paper proposes a robust model to solve the coordinated operation and expansion planning of active distribution networks with multiple microgrids, distributed energy resources (DERs), demand response, and N-1 generation contingency. The objective is to determine the best expansion planning proposals and the optimal daily operation (24-hour representation) for the DERs under the worst realization of uncertainties, using a contingency-constrained approach. Besides, the load is represented by non-controllable, controllable, and deferrable portions. The model is formulated as a tri-level problem that is solved using a two-stage robust optimization approach. The proposed method is illustrated using a modified version of the IEEE 123-bus test system. The results show that the coordinated operation and expansion planning decreases the total cost of the problem and provides more consistent results for demand response and DERs coordination. Simulations show a reduction of 13.8% in the total cost if the daily operation and demand response are represented, and the inclusion of contingencies provides a reduction of 70% in the EENS (expected energy not served) reliability index for the case study.

Suggested Citation

  • Pinto, Rafael S. & Unsihuay-Vila, Clodomiro & Tabarro, Fabricio H., 2021. "Coordinated operation and expansion planning for multiple microgrids and active distribution networks under uncertainties," Applied Energy, Elsevier, vol. 297(C).
    • Handle: RePEc:eee:appene:v:297:y:2021:i:c:s0306261921005523
    DOI: 10.1016/j.apenergy.2021.117108
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921005523
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.117108?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. Varasteh, Farid & Nazar, Mehrdad Setayesh & Heidari, Alireza & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Distributed energy resource and network expansion planning of a CCHP based active microgrid considering demand response programs," Energy, Elsevier, vol. 172(C), pages 79-105.
    2. Wu, Zhi & Liu, Pengxiang & Gu, Wei & Huang, He & Han, Jun, 2018. "A bi-level planning approach for hybrid AC-DC distribution system considering N-1 security criterion," Applied Energy, Elsevier, vol. 230(C), pages 417-428.
    3. Paliwal, Priyanka & Patidar, N.P. & Nema, R.K., 2014. "Planning of grid integrated distributed generators: A review of technology, objectives and techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 557-570.
    4. Hemmati, Reza & Saboori, Hedayat & Siano, Pierluigi, 2017. "Coordinated short-term scheduling and long-term expansion planning in microgrids incorporating renewable energy resources and energy storage systems," Energy, Elsevier, vol. 134(C), pages 699-708.
    5. Qiu, Haifeng & You, Fengqi, 2020. "Decentralized-distributed robust electric power scheduling for multi-microgrid systems," Applied Energy, Elsevier, vol. 269(C).
    6. Zakernezhad, Hamid & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Multi-level optimization framework for resilient distribution system expansion planning with distributed energy resources," Energy, Elsevier, vol. 214(C).
    7. Lu, Xinhui & Liu, Zhaoxi & Ma, Li & Wang, Lingfeng & Zhou, Kaile & Yang, Shanlin, 2020. "A robust optimization approach for coordinated operation of multiple energy hubs," Energy, Elsevier, vol. 197(C).
    8. Chen, J.J. & Qi, B.X. & Rong, Z.K. & Peng, K. & Zhao, Y.L. & Zhang, X.H., 2021. "Multi-energy coordinated microgrid scheduling with integrated demand response for flexibility improvement," Energy, Elsevier, vol. 217(C).
    9. Zhao, Bo & Ren, Junzhi & Chen, Jian & Lin, Da & Qin, Ruwen, 2020. "Tri-level robust planning-operation co-optimization of distributed energy storage in distribution networks with high PV penetration," Applied Energy, Elsevier, vol. 279(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. Liu, Hong & Cao, Yuchen & Ge, Shaoyun & Xu, Zhengyang & Gu, Chenghong & He, Xingtang, 2022. "Load carrying capability of regional electricity-heat energy systems: Definitions, characteristics, and optimal value evaluation," Applied Energy, Elsevier, vol. 310(C).
    2. Tabandeh, Abbas & Hossain, M.J. & Li, Li, 2022. "Integrated multi-stage and multi-zone distribution network expansion planning with renewable energy sources and hydrogen refuelling stations for fuel cell vehicles," Applied Energy, Elsevier, vol. 319(C).
    3. Zhu, Junpeng & Huang, Yong & Lu, Shuai & Shen, Mengya & Yuan, Yue, 2024. "Incorporating local uncertainty management into distribution system planning: An adaptive robust optimization approach," Applied Energy, Elsevier, vol. 363(C).
    4. Zhu, Xingxu & Hou, Xiangchen & Li, Junhui & Yan, Gangui & Li, Cuiping & Wang, Dongbo, 2023. "Distributed online prediction optimization algorithm for distributed energy resources considering the multi-periods optimal operation," Applied Energy, Elsevier, vol. 348(C).
    5. Rahim, Sahar & Wang, Zhen & Ju, Ping, 2022. "Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review," Applied Energy, Elsevier, vol. 319(C).
    6. Rafael A. Núñez-Rodríguez & Clodomiro Unsihuay-Vila & Johnny Posada & Omar Pinzón-Ardila, 2024. "Data-Driven Distributionally Robust Optimization for Day-Ahead Operation Planning of a Smart Transformer-Based Meshed Hybrid AC/DC Microgrid Considering the Optimal Reactive Power Dispatch," Energies, MDPI, vol. 17(16), pages 1-25, August.
    7. Shahid Nawaz Khan & Syed Ali Abbas Kazmi & Abdullah Altamimi & Zafar A. Khan & Mohammed A. Alghassab, 2022. "Smart Distribution Mechanisms—Part I: From the Perspectives of Planning," Sustainability, MDPI, vol. 14(23), pages 1-109, December.
    8. Rastgou, Abdollah, 2024. "Distribution network expansion planning: An updated review of current methods and new challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    9. Qiu, Yibin & Li, Qi & Wang, Tianhong & Yin, Liangzhen & Chen, Weirong & Liu, Hong, 2022. "Optimal planning of Cross-regional hydrogen energy storage systems considering the uncertainty," Applied Energy, Elsevier, vol. 326(C).
    10. Xiang, Yue & Dai, Jiakun & Xue, Ping & Liu, Junyong, 2023. "Autonomous topology planning for distribution network expansion: A learning-based decoupled optimization method," Applied Energy, Elsevier, vol. 348(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. Nazar, Mehrdad Setayesh & Jafarpour, Pourya & Shafie-khah, Miadreza & Catalão, João P.S., 2024. "Optimal planning of self-healing multi-carriers energy systems considering integration of smart buildings and parking lots energy resources," Energy, Elsevier, vol. 286(C).
    2. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    3. Gao, Yang & Ai, Qian & He, Xing & Fan, Songli, 2023. "Coordination for regional integrated energy system through target cascade optimization," Energy, Elsevier, vol. 276(C).
    4. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "A review of co-optimization approaches for operational and planning problems in the energy sector," Applied Energy, Elsevier, vol. 304(C).
    5. Mukhopadhyay, Bineeta & Das, Debapriya, 2021. "Optimal multi-objective expansion planning of a droop-regulated islanded microgrid," Energy, Elsevier, vol. 218(C).
    6. Qiu, Haifeng & Gu, Wei & Liu, Pengxiang & Sun, Qirun & Wu, Zhi & Lu, Xi, 2022. "Application of two-stage robust optimization theory in power system scheduling under uncertainties: A review and perspective," Energy, Elsevier, vol. 251(C).
    7. Wang, Zhengchao & Perera, A.T.D., 2020. "Integrated platform to design robust energy internet," Applied Energy, Elsevier, vol. 269(C).
    8. A.S. Jameel Hassan & Umar Marikkar & G.W. Kasun Prabhath & Aranee Balachandran & W.G. Chaminda Bandara & Parakrama B. Ekanayake & Roshan I. Godaliyadda & Janaka B. Ekanayake, 2021. "A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration," Energies, MDPI, vol. 14(20), pages 1-24, October.
    9. Ahmadi, Seyed Ehsan & Sadeghi, Delnia & Marzband, Mousa & Abusorrah, Abdullah & Sedraoui, Khaled, 2022. "Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies," Energy, Elsevier, vol. 245(C).
    10. Soheil Mohseni & Alan C. Brent & Daniel Burmester, 2020. "Community Resilience-Oriented Optimal Micro-Grid Capacity Expansion Planning: The Case of Totarabank Eco-Village, New Zealand," Energies, MDPI, vol. 13(15), pages 1-29, August.
    11. Li, Ling-Ling & Ji, Bing-Xiang & Liu, Guan-Chen & Yuan, Jian-Ping & Tseng, Shuan-Wei & Lim, Ming K. & Tseng, Ming-Lang, 2024. "Grid-connected multi-microgrid system operational scheduling optimization: A hierarchical improved marine predators algorithm," Energy, Elsevier, vol. 294(C).
    12. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs," Energy, Elsevier, vol. 190(C).
    13. Armioun, Majid & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Siano, Pierluigi, 2023. "Optimal scheduling of CCHP-based resilient energy distribution system considering active microgrids' multi-carrier energy transactions," Applied Energy, Elsevier, vol. 350(C).
    14. Wang, B. & Liu, L. & Huang, G.H. & Li, W. & Xie, Y.L., 2018. "Effects of carbon and environmental tax on power mix planning - A case study of Hebei Province, China," Energy, Elsevier, vol. 143(C), pages 645-657.
    15. Xiong, Kang & Hu, Weihao & Cao, Di & Li, Sichen & Zhang, Guozhou & Liu, Wen & Huang, Qi & Chen, Zhe, 2023. "Coordinated energy management strategy for multi-energy hub with thermo-electrochemical effect based power-to-ammonia: A multi-agent deep reinforcement learning enabled approach," Renewable Energy, Elsevier, vol. 214(C), pages 216-232.
    16. Mahyar Lasemi Imeni & Mohammad Sadegh Ghazizadeh & Mohammad Ali Lasemi & Zhenyu Yang, 2023. "Optimal Scheduling of a Hydrogen-Based Energy Hub Considering a Stochastic Multi-Attribute Decision-Making Approach," Energies, MDPI, vol. 16(2), pages 1-23, January.
    17. Katsanevakis, Markos & Stewart, Rodney A. & Lu, Junwei, 2017. "Aggregated applications and benefits of energy storage systems with application-specific control methods: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 719-741.
    18. Yang, Chengying & Wu, Zhixin & Li, Xuetao & Fars, Ashk, 2024. "Risk-constrained stochastic scheduling for energy hub: Integrating renewables, demand response, and electric vehicles," Energy, Elsevier, vol. 288(C).
    19. Ghahramani, Mehrdad & Nazari-Heris, Morteza & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2019. "Energy and reserve management of a smart distribution system by incorporating responsive-loads /battery/wind turbines considering uncertain parameters," Energy, Elsevier, vol. 183(C), pages 205-219.
    20. Seyfi, Mohammad & Mehdinejad, Mehdi & Mohammadi-Ivatloo, Behnam & Shayanfar, Heidarali, 2022. "Deep learning-based scheduling of virtual energy hubs with plug-in hybrid compressed natural gas-electric vehicles," Applied Energy, Elsevier, vol. 321(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:appene:v:297:y:2021:i:c:s0306261921005523. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.