IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v287y2024ics0360544223030554.html
   My bibliography  Save this article

Assessment of smart grid operation under emergency situations

Author

Listed:
  • Fotopoulou, Maria
  • Rakopoulos, Dimitrios
  • Petridis, Stefanos
  • Drosatos, Panagiotis

Abstract

Smart grids constitute a major trend of electrical networks, the operation of which is underpinned by innovative optimization algorithms. Yet, sometimes, their normal operation is challenged by emergencies that require a Decision Support System (DSS) that modifies the Energy Management System (EMS) accordingly, taking into account the disconnected parts. The purpose of this research is to assess the impact of emergencies on smart grids through a novel optimization algorithm. The algorithm comprises an optimizer, which maximizes the autonomy of the smart grid, prioritizing its Renewable Energy Sources (RES), and Artificial Neural Networks (ANN), which provide forecasts related to the intermittent RES production. The assessment of each emergency includes the reduction of the grid's autonomous and sustainable operation, the increase of curtailments, CO2 emissions, etc. The algorithm is applied on a model of an actual smart grid in Spain, investigating a variety of cases. According to the results, an emergency affecting the smart grid's RES during noon might cause up to 46 % reduction of its autonomy, which, in this case, means 31 kWh of remaining autonomy, and an emergency affecting the storage might cause curtailments up to 25 % of RES production, in this case equal to 35 kWh of curtailed energy.

Suggested Citation

  • Fotopoulou, Maria & Rakopoulos, Dimitrios & Petridis, Stefanos & Drosatos, Panagiotis, 2024. "Assessment of smart grid operation under emergency situations," Energy, Elsevier, vol. 287(C).
  • Handle: RePEc:eee:energy:v:287:y:2024:i:c:s0360544223030554
    DOI: 10.1016/j.energy.2023.129661
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223030554
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2023.129661?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. Tian, Man-Wen & Talebizadehsardari, Pouyan, 2021. "Energy cost and efficiency analysis of building resilience against power outage by shared parking station for electric vehicles and demand response program," Energy, Elsevier, vol. 215(PB).
    2. Woon, Kok Sin & Phuang, Zhen Xin & Taler, Jan & Varbanov, Petar Sabev & Chong, Cheng Tung & Klemeš, Jiří Jaromír & Lee, Chew Tin, 2023. "Recent advances in urban green energy development towards carbon emissions neutrality," Energy, Elsevier, vol. 267(C).
    3. Lund, Henrik & Andersen, Anders N. & Østergaard, Poul Alberg & Mathiesen, Brian Vad & Connolly, David, 2012. "From electricity smart grids to smart energy systems – A market operation based approach and understanding," Energy, Elsevier, vol. 42(1), pages 96-102.
    4. Alirezazadeh, Atefeh & Rashidinejad, Masoud & Abdollahi, Amir & Afzali, Peyman & Bakhshai, Alireza, 2020. "A new flexible model for generation scheduling in a smart grid," Energy, Elsevier, vol. 191(C).
    5. Tsao, Yu-Chung & Thanh, Vo-Van & Lu, Jye-Chyi, 2019. "Multiobjective robust fuzzy stochastic approach for sustainable smart grid design," Energy, Elsevier, vol. 176(C), pages 929-939.
    6. Jalali, Mohammad Majid & Kazemi, Ahad, 2015. "Demand side management in a smart grid with multiple electricity suppliers," Energy, Elsevier, vol. 81(C), pages 766-776.
    7. Personal, Enrique & Guerrero, Juan Ignacio & Garcia, Antonio & Peña, Manuel & Leon, Carlos, 2014. "Key performance indicators: A useful tool to assess Smart Grid goals," Energy, Elsevier, vol. 76(C), pages 976-988.
    8. Kaygusuz, Asim, 2019. "Closed loop elastic demand control by dynamic energy pricing in smart grids," Energy, Elsevier, vol. 176(C), pages 596-603.
    9. Mansour-lakouraj, Mohammad & Shahabi, Majid, 2019. "Comprehensive analysis of risk-based energy management for dependent micro-grid under normal and emergency operations," Energy, Elsevier, vol. 171(C), pages 928-943.
    10. Olabi, A.G. & Onumaegbu, C. & Wilberforce, Tabbi & Ramadan, Mohamad & Abdelkareem, Mohammad Ali & Al – Alami, Abdul Hai, 2021. "Critical review of energy storage systems," Energy, Elsevier, vol. 214(C).
    11. Theocharides, Spyros & Makrides, George & Livera, Andreas & Theristis, Marios & Kaimakis, Paris & Georghiou, George E., 2020. "Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing," Applied Energy, Elsevier, vol. 268(C).
    12. Lund, Henrik & Østergaard, Poul Alberg & Connolly, David & Mathiesen, Brian Vad, 2017. "Smart energy and smart energy systems," Energy, Elsevier, vol. 137(C), pages 556-565.
    13. Das, Saborni & Basu, Mousumi, 2020. "Day-ahead optimal bidding strategy of microgrid with demand response program considering uncertainties and outages of renewable energy resources," Energy, Elsevier, vol. 190(C).
    14. Muhammad Shahzad Nazir & Fahad Alturise & Sami Alshmrany & Hafiz. M. J Nazir & Muhammad Bilal & Ahmad N. Abdalla & P. Sanjeevikumar & Ziad M. Ali, 2020. "Wind Generation Forecasting Methods and Proliferation of Artificial Neural Network: A Review of Five Years Research Trend," Sustainability, MDPI, vol. 12(9), pages 1-27, May.
    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. Lund, Henrik & Thellufsen, Jakob Zinck & Sorknæs, Peter & Mathiesen, Brian Vad & Chang, Miguel & Madsen, Poul Thøis & Kany, Mikkel Strunge & Skov, Iva Ridjan, 2022. "Smart energy Denmark. A consistent and detailed strategy for a fully decarbonized society," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    2. David Drysdale & Brian Vad Mathiesen & Henrik Lund, 2019. "From Carbon Calculators to Energy System Analysis in Cities," Energies, MDPI, vol. 12(12), pages 1-21, June.
    3. Tengfei Ma & Junyong Wu & Liangliang Hao & Huaguang Yan & Dezhi Li, 2018. "A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach," Energies, MDPI, vol. 11(10), pages 1-19, October.
    4. Christensen, Paul A. & Anderson, Paul A. & Harper, Gavin D.J. & Lambert, Simon M. & Mrozik, Wojciech & Rajaeifar, Mohammad Ali & Wise, Malcolm S. & Heidrich, Oliver, 2021. "Risk management over the life cycle of lithium-ion batteries in electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    5. Sachajdak, Andrzej & Lappalainen, Jari & Mikkonen, Hannu, 2019. "Dynamic simulation in development of contemporary energy systems – oxy combustion case study," Energy, Elsevier, vol. 181(C), pages 964-973.
    6. Rasmus Magni Johannsen & Poul Alberg Østergaard & David Maya-Drysdale & Louise Krog Elmegaard Mouritsen, 2021. "Designing Tools for Energy System Scenario Making in Municipal Energy Planning," Energies, MDPI, vol. 14(5), pages 1-17, March.
    7. Antonio Parejo & Antonio Sanchez-Squella & Rodrigo Barraza & Fernando Yanine & Aldo Barrueto-Guzman & Carlos Leon, 2019. "Design and Simulation of an Energy Homeostaticity System for Electric and Thermal Power Management in a Building with Smart Microgrid," Energies, MDPI, vol. 12(9), pages 1-19, May.
    8. Sarker, Eity & Seyedmahmoudian, Mehdi & Jamei, Elmira & Horan, Ben & Stojcevski, Alex, 2020. "Optimal management of home loads with renewable energy integration and demand response strategy," Energy, Elsevier, vol. 210(C).
    9. Brown, T. & Schlachtberger, D. & Kies, A. & Schramm, S. & Greiner, M., 2018. "Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system," Energy, Elsevier, vol. 160(C), pages 720-739.
    10. David Maya-Drysdale & Louise Krog Jensen & Brian Vad Mathiesen, 2020. "Energy Vision Strategies for the EU Green New Deal: A Case Study of European Cities," Energies, MDPI, vol. 13(9), pages 1-20, May.
    11. Yin, Linfei & Luo, Shikui & Ma, Chenxiao, 2021. "Expandable depth and width adaptive dynamic programming for economic smart generation control of smart grids," Energy, Elsevier, vol. 232(C).
    12. Razmjoo, Armin & Mirjalili, Seyedali & Aliehyaei, Mehdi & Østergaard, Poul Alberg & Ahmadi, Abolfazl & Majidi Nezhad, Meysam, 2022. "Development of smart energy systems for communities: technologies, policies and applications," Energy, Elsevier, vol. 248(C).
    13. Claudiu Vasile Kifor & Alexandru Olteanu & Mihai Zerbes, 2023. "Key Performance Indicators for Smart Energy Systems in Sustainable Universities," Energies, MDPI, vol. 16(3), pages 1-19, January.
    14. Lund, Henrik, 2018. "Renewable heating strategies and their consequences for storage and grid infrastructures comparing a smart grid to a smart energy systems approach," Energy, Elsevier, vol. 151(C), pages 94-102.
    15. Kılkış, Şiir, 2023. "Integrated urban scenarios of emissions, land use efficiency and benchmarking for climate neutrality and sustainability," Energy, Elsevier, vol. 285(C).
    16. Zhang, Xiaoshun & Yu, Tao & Yang, Bo & Li, Li, 2016. "Virtual generation tribe based robust collaborative consensus algorithm for dynamic generation command dispatch optimization of smart grid," Energy, Elsevier, vol. 101(C), pages 34-51.
    17. Gilmore, Nicholas & Koskinen, Ilpo & van Gennip, Domenique & Paget, Greta & Burr, Patrick A. & Obbard, Edward G. & Daiyan, Rahman & Sproul, Alistair & Kay, Merlinde & Lennon, Alison & Konstantinou, Ge, 2022. "Clean energy futures: An Australian based foresight study," Energy, Elsevier, vol. 260(C).
    18. Lund, Henrik & Duic, Neven & Østergaard, Poul Alberg & Mathiesen, Brian Vad, 2018. "Future district heating systems and technologies: On the role of smart energy systems and 4th generation district heating," Energy, Elsevier, vol. 165(PA), pages 614-619.
    19. Marczinkowski, Hannah Mareike & Østergaard, Poul Alberg, 2018. "Residential versus communal combination of photovoltaic and battery in smart energy systems," Energy, Elsevier, vol. 152(C), pages 466-475.
    20. Lamnatou, Chr. & Chemisana, D. & Cristofari, C., 2022. "Smart grids and smart technologies in relation to photovoltaics, storage systems, buildings and the environment," Renewable Energy, Elsevier, vol. 185(C), pages 1376-1391.

    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:287:y:2024:i:c:s0360544223030554. 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.