IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v314y2022ics0306261922002999.html
   My bibliography  Save this article

Optimal scheduling of an active distribution system considering distributed energy resources, demand response aggregators and electrical energy storage

Author

Listed:
  • Zakernezhad, Hamid
  • Setayesh Nazar, Mehrdad
  • Shafie-khah, Miadreza
  • Catalão, João P.S.

Abstract

This paper presents a two-level optimization model for the optimal scheduling of an active distribution system in day-ahead and real-time market horizons. The distribution system operator transacts energy and ancillary services with the electricity market, plug-in hybrid electric vehicle parking lot aggregators, and demand response aggregators. Further, the active distribution system can utilize a switching procedure for its zonal tie-line switches to mitigate the effects of contingencies. The main contribution of this paper is that the proposed framework simultaneously models the arbitrage strategy of the active distribution system, electric vehicle parking lot aggregators, and demand response aggregators in the day-ahead and real-time markets. This paper's solution methodology is another contribution that utilizes robust and lexicographic ordering optimization methods. At the first stage of the first level, the optimal bidding strategies of plug-in hybrid electric vehicle parking lot aggregators and demand response aggregators are explored. Then, at the second stage of the first level, the day-ahead optimization process finds the optimal scheduling of distributed energy resources and switching of electrical switches. Finally, at the second level, the real-time optimization problem optimizes the scheduling of system resources. Different case studies were carried out to assess the effectiveness of the algorithm. The proposed algorithm increases the system's day-ahead and real-time revenues by about 52.09% and 47.04% concerning the case without the proposed method, respectively.

Suggested Citation

  • Zakernezhad, Hamid & Setayesh Nazar, Mehrdad & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Optimal scheduling of an active distribution system considering distributed energy resources, demand response aggregators and electrical energy storage," Applied Energy, Elsevier, vol. 314(C).
  • Handle: RePEc:eee:appene:v:314:y:2022:i:c:s0306261922002999
    DOI: 10.1016/j.apenergy.2022.118865
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922002999
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2022.118865?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. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    2. Zhang, Jingrui & Li, Zhuoyun & Wang, Beibei, 2021. "Within-day rolling optimal scheduling problem for active distribution networks by multi-objective evolutionary algorithm based on decomposition integrating with thought of simulated annealing," Energy, Elsevier, vol. 223(C).
    3. Zakernezhad, Hamid & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Optimal resilient operation of multi-carrier energy systems in electricity markets considering distributed energy resource aggregators," Applied Energy, Elsevier, vol. 299(C).
    4. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "An integrated optimization framework for combined heat and power units, distributed generation and plug-in electric vehicles," Energy, Elsevier, vol. 202(C).
    5. Zhou, Yulu & Zhang, Jingrui, 2020. "Three-layer day-ahead scheduling for active distribution network by considering multiple stakeholders," Energy, Elsevier, vol. 207(C).
    6. Zhang, Jingrui & Zhou, Yulu & Li, Zhuoyun & Cai, Junfeng, 2021. "Three-level day-ahead optimal scheduling framework considering multi-stakeholders in active distribution networks: Up-to-down approach," Energy, Elsevier, vol. 219(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. Zare Oskouei, Morteza & Gharehpetian, Gevork B., 2024. "Flexibility enhancement of multi-district DISCOs considering a trade-off between congestion and extractable reserve capacity from virtual energy storage systems," Applied Energy, Elsevier, vol. 353(PB).
    2. Aguado, José A. & Paredes, Ángel, 2023. "Coordinated and decentralized trading of flexibility products in Inter-DSO Local Electricity Markets via ADMM," Applied Energy, Elsevier, vol. 337(C).
    3. Azarnia, Mahsa & Rahimiyan, Morteza & Siano, Pierluigi, 2024. "Offering of active distribution network in real-time energy market by integrated energy management system and Volt-Var optimization," Applied Energy, Elsevier, vol. 358(C).
    4. Venizelos Venizelou & Apostolos C. Tsolakis & Demetres Evagorou & Christos Patsonakis & Ioannis Koskinas & Phivos Therapontos & Lampros Zyglakis & Dimosthenis Ioannidis & George Makrides & Dimitrios T, 2023. "DSO-Aggregator Demand Response Cooperation Framework towards Reliable, Fair and Secure Flexibility Dispatch," Energies, MDPI, vol. 16(6), pages 1-21, March.
    5. Firouzi, Mehdi & Setayesh Nazar, Mehrdad & Shafie-khah, Miadreza & Catalão, João P.S., 2023. "Integrated framework for modeling the interactions of plug-in hybrid electric vehicles aggregators, parking lots and distributed generation facilities in electricity markets," Applied Energy, Elsevier, vol. 334(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. Suryakiran, B.V. & Nizami, Sohrab & Verma, Ashu & Saha, Tapan Kumar & Mishra, Sukumar, 2023. "A DSO-based day-ahead market mechanism for optimal operational planning of active distribution network," Energy, Elsevier, vol. 282(C).
    2. Liu, Zhouding & Nazari-Heris, Morteza, 2023. "Optimal bidding strategy of multi-carrier systems in electricity markets using information gap decision theory," Energy, Elsevier, vol. 280(C).
    3. Firouzi, Mehdi & Setayesh Nazar, Mehrdad & Shafie-khah, Miadreza & Catalão, João P.S., 2023. "Integrated framework for modeling the interactions of plug-in hybrid electric vehicles aggregators, parking lots and distributed generation facilities in electricity markets," Applied Energy, Elsevier, vol. 334(C).
    4. Jianwen Ren & Yingqiang Xu & Shiyuan Wang, 2018. "A Distributed Robust Dispatch Approach for Interconnected Systems with a High Proportion of Wind Power Penetration," Energies, MDPI, vol. 11(4), pages 1-18, April.
    5. Wenqing Chen & Melvyn Sim & Jie Sun & Chung-Piaw Teo, 2010. "From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization," Operations Research, INFORMS, vol. 58(2), pages 470-485, April.
    6. Stefan Mišković, 2017. "A VNS-LP algorithm for the robust dynamic maximal covering location problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1011-1033, October.
    7. Sarhadi, Hassan & Naoum-Sawaya, Joe & Verma, Manish, 2020. "A robust optimization approach to locating and stockpiling marine oil-spill response facilities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    8. Li, Shukai & Liu, Ronghui & Yang, Lixing & Gao, Ziyou, 2019. "Robust dynamic bus controls considering delay disturbances and passenger demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 88-109.
    9. Jeong, Jaehee & Premsankar, Gopika & Ghaddar, Bissan & Tarkoma, Sasu, 2024. "A robust optimization approach for placement of applications in edge computing considering latency uncertainty," Omega, Elsevier, vol. 126(C).
    10. Chassein, André & Dokka, Trivikram & Goerigk, Marc, 2019. "Algorithms and uncertainty sets for data-driven robust shortest path problems," European Journal of Operational Research, Elsevier, vol. 274(2), pages 671-686.
    11. Kandpal, Bakul & Pareek, Parikshit & Verma, Ashu, 2022. "A robust day-ahead scheduling strategy for EV charging stations in unbalanced distribution grid," Energy, Elsevier, vol. 249(C).
    12. Guo, Shiliang & Li, Pengpeng & Ma, Kai & Yang, Bo & Yang, Jie, 2022. "Robust energy management for industrial microgrid considering charging and discharging pressure of electric vehicles," Applied Energy, Elsevier, vol. 325(C).
    13. Shen, Feifei & Zhao, Liang & Wang, Meihong & Du, Wenli & Qian, Feng, 2022. "Data-driven adaptive robust optimization for energy systems in ethylene plant under demand uncertainty," Applied Energy, Elsevier, vol. 307(C).
    14. Baringo, Luis & Boffino, Luigi & Oggioni, Giorgia, 2020. "Robust expansion planning of a distribution system with electric vehicles, storage and renewable units," Applied Energy, Elsevier, vol. 265(C).
    15. Hasani, Aliakbar & Khosrojerdi, Amirhossein, 2016. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 20-52.
    16. Popović, Željko N. & KovaÄ ki, Neven V. & Popović, Dragan S., 2020. "Resilient distribution network planning under the severe windstorms using a risk-based approach," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    17. Dimitris Bertsimas & Agni Orfanoudaki, 2021. "Algorithmic Insurance," Papers 2106.00839, arXiv.org, revised Dec 2022.
    18. Rafael Epstein & Andres Neely & Andres Weintraub & Fernando Valenzuela & Sergio Hurtado & Guillermo Gonzalez & Alex Beiza & Mauricio Naveas & Florencio Infante & Fernando Alarcon & Gustavo Angulo & Cr, 2012. "A Strategic Empty Container Logistics Optimization in a Major Shipping Company," Interfaces, INFORMS, vol. 42(1), pages 5-16, February.
    19. Lu, Chung-Cheng & Ying, Kuo-Ching & Chen, Hui-Ju, 2016. "Real-time relief distribution in the aftermath of disasters – A rolling horizon approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 1-20.
    20. Beck, Yasmine & Ljubić, Ivana & Schmidt, Martin, 2023. "A survey on bilevel optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 311(2), pages 401-426.

    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:314:y:2022:i:c:s0306261922002999. 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.