IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v358y2024ics0306261923019098.html
   My bibliography  Save this article

Discrete optimal power flow with prohibited zones, multiple-fuel options, and practical operational rules for control devices

Author

Listed:
  • Alencar, Marina Valença
  • da Silva, Diego Nunes
  • Nepomuceno, Leonardo
  • Martins, André Christóvão Pio
  • Balbo, Antonio Roberto
  • Soler, Edilaine Martins

Abstract

Although the optimal power flow (OPF) problem has been extensively studied, solving realistic OPF models that accurately represent the operating behavior of power system components remains challenging. This paper proposes a novel model for the AC OPF problem, aiming to minimize the fuel costs of thermal units while taking into account valve-point loading effects (VPLE), prohibited operation zones (POZ), multiple fuel options (MFO), and operational rules associated with the discrete tap ratios of on-load tap changer (OLTC) transformers and with the discrete shunt susceptances of capacitor/reactor banks. These rules are represented using complementarity constraints. We propose a solution approach that integrates several strategies to address the non-smooth features of the objective function related to VPLE, the disjoint constraints and functions tied to POZ and MFO, the discrete characteristics of the reactive control variables, and the complementarity constraints governing operational rules linked to voltage control devices such as OLTC transformers and capacitor/reactor banks. The resulting optimization problem is designed to be compatible with commercial solver packages. Numerical tests on the IEEE 30, 118, and 300-bus systems aim to examine the cumulative impact of these operational factors on the optimal solution. The solution strategy proposed has demonstrated its effectiveness in solving the proposed OPF problem within reasonable computation times.

Suggested Citation

  • Alencar, Marina Valença & da Silva, Diego Nunes & Nepomuceno, Leonardo & Martins, André Christóvão Pio & Balbo, Antonio Roberto & Soler, Edilaine Martins, 2024. "Discrete optimal power flow with prohibited zones, multiple-fuel options, and practical operational rules for control devices," Applied Energy, Elsevier, vol. 358(C).
    • Handle: RePEc:eee:appene:v:358:y:2024:i:c:s0306261923019098
    DOI: 10.1016/j.apenergy.2023.122545
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923019098
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.122545?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. Shaheen, Abdullah M. & El-Sehiemy, Ragab A. & Hasanien, Hany M. & Ginidi, Ahmed R., 2022. "An improved heap optimization algorithm for efficient energy management based optimal power flow model," Energy, Elsevier, vol. 250(C).
    2. Mohamed Farhat & Salah Kamel & Ahmed M. Atallah & Mohamed H. Hassan & Ahmed M. Agwa, 2022. "ESMA-OPF: Enhanced Slime Mould Algorithm for Solving Optimal Power Flow Problem," Sustainability, MDPI, vol. 14(4), pages 1-33, February.
    3. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Quasi-oppositional turbulent water flow-based optimization for cascaded short term hydrothermal scheduling with valve-point effects and multiple fuels," Energy, Elsevier, vol. 251(C).
    4. Soler, Edilaine Martins & de Sousa, Vanusa Alves & da Costa, Geraldo R.M., 2012. "A modified Primal–Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables," European Journal of Operational Research, Elsevier, vol. 222(3), pages 616-622.
    5. Narimani, Mohammad Rasoul & Azizipanah-Abarghooee, Rasoul & Zoghdar-Moghadam-Shahrekohne, Behrouz & Gholami, Kayvan, 2013. "A novel approach to multi-objective optimal power flow by a new hybrid optimization algorithm considering generator constraints and multi-fuel type," Energy, Elsevier, vol. 49(C), pages 119-136.
    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. Khaled Nusair & Lina Alhmoud, 2020. "Application of Equilibrium Optimizer Algorithm for Optimal Power Flow with High Penetration of Renewable Energy," Energies, MDPI, vol. 13(22), pages 1-35, November.
    2. Fitiwi, Desta Z. & Olmos, L. & Rivier, M. & de Cuadra, F. & Pérez-Arriaga, I.J., 2016. "Finding a representative network losses model for large-scale transmission expansion planning with renewable energy sources," Energy, Elsevier, vol. 101(C), pages 343-358.
    3. Elattar, Ehab E. & ElSayed, Salah K., 2019. "Modified JAYA algorithm for optimal power flow incorporating renewable energy sources considering the cost, emission, power loss and voltage profile improvement," Energy, Elsevier, vol. 178(C), pages 598-609.
    4. Srikanth Reddy, K. & Panwar, Lokesh & Panigrahi, B.K. & Kumar, Rajesh, 2018. "Modeling and analysis of profit based self scheduling of GENCO in electricity markets with renewable energy penetration and emission constraints," Renewable Energy, Elsevier, vol. 116(PA), pages 48-63.
    5. Mohammed Hamouda Ali & Ali M. El-Rifaie & Ahmed A. F. Youssef & Vladimir N. Tulsky & Mohamed A. Tolba, 2023. "Techno-Economic Strategy for the Load Dispatch and Power Flow in Power Grids Using Peafowl Optimization Algorithm," Energies, MDPI, vol. 16(2), pages 1-29, January.
    6. Ghasemi, Mojtaba & Ghavidel, Sahand & Ghanbarian, Mohammad Mehdi & Gharibzadeh, Masihallah & Azizi Vahed, Ali, 2014. "Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm," Energy, Elsevier, vol. 78(C), pages 276-289.
    7. Li, Shuijia & Gong, Wenyin & Wang, Ling & Yan, Xuesong & Hu, Chengyu, 2020. "Optimal power flow by means of improved adaptive differential evolution," Energy, Elsevier, vol. 198(C).
    8. Younes, Mimoun & Khodja, Fouad & Kherfane, Riad Lakhdar, 2014. "Multi-objective economic emission dispatch solution using hybrid FFA (firefly algorithm) and considering wind power penetration," Energy, Elsevier, vol. 67(C), pages 595-606.
    9. Ali S. Alghamdi, 2022. "Optimal Power Flow in Wind–Photovoltaic Energy Regulation Systems Using a Modified Turbulent Water Flow-Based Optimization," Sustainability, MDPI, vol. 14(24), pages 1-27, December.
    10. Gengli Song & Hua Wei, 2022. "Distributionally Robust Multi-Energy Dynamic Optimal Power Flow Considering Water Spillage with Wasserstein Metric," Energies, MDPI, vol. 15(11), pages 1-18, May.
    11. Narimani, Hossein & Razavi, Seyed-Ehsan & Azizivahed, Ali & Naderi, Ehsan & Fathi, Mehdi & Ataei, Mohammad H. & Narimani, Mohammad Rasoul, 2018. "A multi-objective framework for multi-area economic emission dispatch," Energy, Elsevier, vol. 154(C), pages 126-142.
    12. Mahmoud A. Ali & Salah Kamel & Mohamed H. Hassan & Emad M. Ahmed & Mohana Alanazi, 2022. "Optimal Power Flow Solution of Power Systems with Renewable Energy Sources Using White Sharks Algorithm," Sustainability, MDPI, vol. 14(10), pages 1-21, May.
    13. Azizivahed, Ali & Narimani, Hossein & Fathi, Mehdi & Naderi, Ehsan & Safarpour, Hamid Reza & Narimani, Mohammad Rasoul, 2018. "Multi-objective dynamic distribution feeder reconfiguration in automated distribution systems," Energy, Elsevier, vol. 147(C), pages 896-914.
    14. Gouthamkumar Nadakuditi & Harish Pulluri & Preeti Dahiya & K. S. R. Murthy & P. Srinivasa Varma & Mohit Bajaj & Torki Altameem & Walid El-Shafai & Mostafa M. Fouda, 2023. "Non-Dominated Sorting-Based Hybrid Optimization Technique for Multi-Objective Hydrothermal Scheduling," Energies, MDPI, vol. 16(5), pages 1-25, February.
    15. Shin-Yeu Lin & Ai-Chih Lin, 2016. "Risk-Limiting Scheduling of Optimal Non-Renewable Power Generation for Systems with Uncertain Power Generation and Load Demand," Energies, MDPI, vol. 9(11), pages 1-16, October.
    16. Esmaili, Masoud & Shayanfar, Heidar Ali & Moslemi, Ramin, 2014. "Locating series FACTS devices for multi-objective congestion management improving voltage and transient stability," European Journal of Operational Research, Elsevier, vol. 236(2), pages 763-773.
    17. Martin Ćalasan & Tatjana Konjić & Katarina Kecojević & Lazar Nikitović, 2020. "Optimal Allocation of Static Var Compensators in Electric Power Systems," Energies, MDPI, vol. 13(12), pages 1-24, June.
    18. Khan, Babar Sattar & Qamar, Affaq & Ullah, Farman & Bilal, Muhammad, 2023. "Ingenuity of Shannon entropy-based fractional order hybrid swarming strategy to solve optimal power flows," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    19. Li, Y.Z. & Wu, Q.H. & Li, M.S. & Zhan, J.P., 2014. "Mean-variance model for power system economic dispatch with wind power integrated," Energy, Elsevier, vol. 72(C), pages 510-520.
    20. Ragab El-Sehiemy & Abdullah Shaheen & Ahmed Ginidi & Mostafa Elhosseini, 2022. "A Honey Badger Optimization for Minimizing the Pollutant Environmental Emissions-Based Economic Dispatch Model Integrating Combined Heat and Power Units," Energies, MDPI, vol. 15(20), pages 1-22, 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:eee:appene:v:358:y:2024:i:c:s0306261923019098. 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.