IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v358y2024ics0306261924000187.html
   My bibliography  Save this article

Offering of active distribution network in real-time energy market by integrated energy management system and Volt-Var optimization

Author

Listed:
  • Azarnia, Mahsa
  • Rahimiyan, Morteza
  • Siano, Pierluigi

Abstract

This paper considers an active distribution network (ADN) that can benefit from price-responsive demands, inverter-based photovoltaic (PV) generating units, and battery energy storage systems (BESSs) to participate in the real-time energy market. However, a challenging issue arises due to the coupling of energy offerings in the market and Volt-Var schedules of system devices. This paper develops an integrated framework of energy management system and Volt-Var optimization (EMS-VVO) in the ADN. This application is in bidirectional communication with the energy market and electricity assets. In the first stage and some minutes before each hour, the EMS-VVO unit makes the offering decisions in the energy market, as well as the schedules of demands and slow-acting devices (i.e., on-load tap changers (OLTCs) and capacitors) under uncertainties in the market prices, PV power production, and power loads. In the second stage, when the actual values of available PV productions and the updated market prices are known during the power delivery, this application controls the voltage in minutes by dispatching the fast-acting devices (i.e., PV generating units and BESSs) throughout the distribution network in minutes. A number of comparative out-of-sample simulations through a 69-node test system demonstrate how the offering and controlling decisions of the ADN can be modified under different PV penetration levels, voltage violation penalties, demand flexibility levels, and reactive power capabilities of fast-acting devices.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:358:y:2024:i:c:s0306261924000187
    DOI: 10.1016/j.apenergy.2024.122635
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924000187
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.122635?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. Venkatesan, Naveen & Solanki, Jignesh & Solanki, Sarika Khushalani, 2012. "Residential Demand Response model and impact on voltage profile and losses of an electric distribution network," Applied Energy, Elsevier, vol. 96(C), pages 84-91.
    2. Anaya, Karim L. & Pollitt, Michael G., 2020. "Reactive power procurement: A review of current trends," Applied Energy, Elsevier, vol. 270(C).
    3. Vijayan, Vineeth & Mohapatra, Abheejeet & Singh, S.N., 2021. "Demand Response with Volt/Var Optimization for unbalanced active distribution systems," Applied Energy, Elsevier, vol. 300(C).
    4. 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).
    5. Siano, Pierluigi, 2014. "Demand response and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 461-478.
    6. Nikmehr, Nima & Najafi-Ravadanegh, Sajad & Khodaei, Amin, 2017. "Probabilistic optimal scheduling of networked microgrids considering time-based demand response programs under uncertainty," Applied Energy, Elsevier, vol. 198(C), pages 267-279.
    7. Antonio J. Conejo & Miguel Carrión & Juan M. Morales, 2010. "Decision Making Under Uncertainty in Electricity Markets," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7421-1, January.
    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. Erdinc, Ozan, 2014. "Economic impacts of small-scale own generating and storage units, and electric vehicles under different demand response strategies for smart households," Applied Energy, Elsevier, vol. 126(C), pages 142-150.
    2. Grover-Silva, Etta & Heleno, Miguel & Mashayekh, Salman & Cardoso, Gonçalo & Girard, Robin & Kariniotakis, George, 2018. "A stochastic optimal power flow for scheduling flexible resources in microgrids operation," Applied Energy, Elsevier, vol. 229(C), pages 201-208.
    3. Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    4. Sheikhahmadi, P. & Bahramara, S. & Moshtagh, J. & Yazdani Damavandi, M., 2018. "A risk-based approach for modeling the strategic behavior of a distribution company in wholesale energy market," Applied Energy, Elsevier, vol. 214(C), pages 24-38.
    5. Hooshmand, Ehsan & Rabiee, Abbas, 2019. "Energy management in distribution systems, considering the impact of reconfiguration, RESs, ESSs and DR: A trade-off between cost and reliability," Renewable Energy, Elsevier, vol. 139(C), pages 346-358.
    6. Vázquez-Canteli, José R. & Nagy, Zoltán, 2019. "Reinforcement learning for demand response: A review of algorithms and modeling techniques," Applied Energy, Elsevier, vol. 235(C), pages 1072-1089.
    7. Ghasemi, Ahmad & Jamshidi Monfared, Houman & Loni, Abdolah & Marzband, Mousa, 2021. "CVaR-based retail electricity pricing in day-ahead scheduling of microgrids," Energy, Elsevier, vol. 227(C).
    8. Yan, Xing & Ozturk, Yusuf & Hu, Zechun & Song, Yonghua, 2018. "A review on price-driven residential demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 411-419.
    9. Ampimah, Benjamin Chris & Sun, Mei & Han, Dun & Wang, Xueyin, 2018. "Optimizing sheddable and shiftable residential electricity consumption by incentivized peak and off-peak credit function approach," Applied Energy, Elsevier, vol. 210(C), pages 1299-1309.
    10. Petinrin, J.O. & Shaabanb, Mohamed, 2016. "Impact of renewable generation on voltage control in distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 770-783.
    11. Zakariazadeh, Alireza & Homaee, Omid & Jadid, Shahram & Siano, Pierluigi, 2014. "A new approach for real time voltage control using demand response in an automated distribution system," Applied Energy, Elsevier, vol. 117(C), pages 157-166.
    12. Yasemin Merzifonluoglu & Eray Uzgoren, 2018. "Photovoltaic power plant design considering multiple uncertainties and risk," Annals of Operations Research, Springer, vol. 262(1), pages 153-184, March.
    13. Karim L. Anaya & Michael G. Pollitt, 2021. "How to Procure Flexibility Services within the Electricity Distribution System: Lessons from an International Review of Innovation Projects," Energies, MDPI, vol. 14(15), pages 1-26, July.
    14. Villa-Arrieta, Manuel & Sumper, Andreas, 2018. "A model for an economic evaluation of energy systems using TRNSYS," Applied Energy, Elsevier, vol. 215(C), pages 765-777.
    15. Singh, Bharat & Kumar, Ashwani, 2023. "Optimal energy management and feasibility analysis of hybrid renewable energy sources with BESS and impact of electric vehicle load with demand response program," Energy, Elsevier, vol. 278(PA).
    16. McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
    17. Hu, Maomao & Xiao, Fu & Wang, Lingshi, 2017. "Investigation of demand response potentials of residential air conditioners in smart grids using grey-box room thermal model," Applied Energy, Elsevier, vol. 207(C), pages 324-335.
    18. Pandžić, Hrvoje & Kuzle, Igor & Capuder, Tomislav, 2013. "Virtual power plant mid-term dispatch optimization," Applied Energy, Elsevier, vol. 101(C), pages 134-141.
    19. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    20. Sadeghian, Omid & Mohammadpour Shotorbani, Amin & Mohammadi-Ivatloo, Behnam & Sadiq, Rehan & Hewage, Kasun, 2021. "Risk-averse maintenance scheduling of generation units in combined heat and power systems with demand response," Reliability Engineering and System Safety, Elsevier, vol. 216(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:358:y:2024:i:c:s0306261924000187. 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.