IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i6p1468-d334905.html
   My bibliography  Save this article

Sensitivity Analysis of the Impact of the Sub- Hourly Stochastic Unit Commitment on Power System Dynamics

Author

Listed:
  • Taulant Kërçi

    (School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland)

  • Juan S. Giraldo

    (Electrical Energy Systems, Department of Electrical Engineering, Eindhoven University of Technology, 5600 Eindhoven, The Netherlands)

  • Federico Milano

    (School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland)

Abstract

Subhourly modeling of power systems and the use of the stochastic optimization are two relevant solutions proposed in the literature to address the integration of stochastic renewable energy sources. With this aim, this paper deals with the effect of different formulations of the subhourly stochastic unit commitment (SUC) problem on power system dynamics. Different SUC models are presented and embedded into time domain simulations (TDS) through a cosimulation platform. The objective of the paper is to study the combined impact of different frequency control/machine parameters and different SUC formulations on the long-term dynamic behaviour of power systems. The analysis is based on extensive Monte Carlo TDS (MC-TDS) and a variety of scenarios based on the New England 39-bus system.

Suggested Citation

  • Taulant Kërçi & Juan S. Giraldo & Federico Milano, 2020. "Sensitivity Analysis of the Impact of the Sub- Hourly Stochastic Unit Commitment on Power System Dynamics," Energies, MDPI, vol. 13(6), pages 1-17, March.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:6:p:1468-:d:334905
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/6/1468/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/6/1468/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Jiadong & Wang, Jianhui & Liu, Cong & Ruiz, Juan P., 2013. "Stochastic unit commitment with sub-hourly dispatch constraints," Applied Energy, Elsevier, vol. 105(C), pages 418-422.
    2. 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, April.
    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. 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.
    2. Pandžić, Hrvoje & Kuzle, Igor & Capuder, Tomislav, 2013. "Virtual power plant mid-term dispatch optimization," Applied Energy, Elsevier, vol. 101(C), pages 134-141.
    3. 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.
    4. 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).
    5. Christos N. Dimitriadis & Evangelos G. Tsimopoulos & Michael C. Georgiadis, 2021. "A Review on the Complementarity Modelling in Competitive Electricity Markets," Energies, MDPI, vol. 14(21), pages 1-27, November.
    6. Mohagheghi, Erfan & Gabash, Aouss & Alramlawi, Mansour & Li, Pu, 2018. "Real-time optimal power flow with reactive power dispatch of wind stations using a reconciliation algorithm," Renewable Energy, Elsevier, vol. 126(C), pages 509-523.
    7. 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.
    8. Jaber Valinejad & Mousa Marzband & Michael Elsdon & Ameena Saad Al-Sumaiti & Taghi Barforoushi, 2019. "Dynamic Carbon-Constrained EPEC Model for Strategic Generation Investment Incentives with the Aim of Reducing CO 2 Emissions," Energies, MDPI, vol. 12(24), pages 1-35, December.
    9. Hernán Gómez-Villarreal & Miguel Carrión & Ruth Domínguez, 2019. "Optimal Management of Combined-Cycle Gas Units with Gas Storage under Uncertainty," Energies, MDPI, vol. 13(1), pages 1-29, December.
    10. Alfredo Alcayde & Raul Baños & Francisco M. Arrabal-Campos & Francisco G. Montoya, 2019. "Optimization of the Contracted Electric Power by Means of Genetic Algorithms," Energies, MDPI, vol. 12(7), pages 1-13, April.
    11. Hanif, Sarmad & Alam, M.J.E. & Roshan, Kini & Bhatti, Bilal A. & Bedoya, Juan C., 2022. "Multi-service battery energy storage system optimization and control," Applied Energy, Elsevier, vol. 311(C).
    12. Thibaut Th'eate & S'ebastien Mathieu & Damien Ernst, 2020. "An Artificial Intelligence Solution for Electricity Procurement in Forward Markets," Papers 2006.05784, arXiv.org, revised Dec 2020.
    13. Xie, Kaigui & Dong, Jizhe & Singh, Chanan & Hu, Bo, 2016. "Optimal capacity and type planning of generating units in a bundled wind–thermal generation system," Applied Energy, Elsevier, vol. 164(C), pages 200-210.
    14. Savelli, Iacopo & Morstyn, Thomas, 2021. "Electricity prices and tariffs to keep everyone happy: A framework for fixed and nodal prices coexistence in distribution grids with optimal tariffs for investment cost recovery," Omega, Elsevier, vol. 103(C).
    15. Nielsen, Maria Grønnegaard & Morales, Juan Miguel & Zugno, Marco & Pedersen, Thomas Engberg & Madsen, Henrik, 2016. "Economic valuation of heat pumps and electric boilers in the Danish energy system," Applied Energy, Elsevier, vol. 167(C), pages 189-200.
    16. Wei, Wei & Liu, Feng & Wang, Jianhui & Chen, Laijun & Mei, Shengwei & Yuan, Tiejiang, 2016. "Robust environmental-economic dispatch incorporating wind power generation and carbon capture plants," Applied Energy, Elsevier, vol. 183(C), pages 674-684.
    17. Paolo Falbo & Carlos Ruiz, 2021. "Joint optimization of sales-mix and generation plan for a large electricity producer," Papers 2110.02016, arXiv.org.
    18. Guanglei Wang & Hassan Hijazi, 2018. "Mathematical programming methods for microgrid design and operations: a survey on deterministic and stochastic approaches," Computational Optimization and Applications, Springer, vol. 71(2), pages 553-608, November.
    19. Moret, Fabio & Pinson, Pierre & Papakonstantinou, Athanasios, 2020. "Heterogeneous risk preferences in community-based electricity markets," European Journal of Operational Research, Elsevier, vol. 287(1), pages 36-48.
    20. Ali Reza Kheirkhah & Carlos Frederico Meschini Almeida & Nelson Kagan & Jonatas Boas Leite, 2023. "Optimal Probabilistic Allocation of Photovoltaic Distributed Generation: Proposing a Scenario-Based Stochastic Programming Model," Energies, MDPI, vol. 16(21), pages 1-18, October.

    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:gam:jeners:v:13:y:2020:i:6:p:1468-:d:334905. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.