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Review of Metaheuristic Optimization Algorithms for Power Systems Problems

Author

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  • Ahmed M. Nassef

    (Department of Electrical Engineering, College of Engineering in Wadi Alddawasir, Prince Sattam Bin Abdulaziz University, Wadi Alddawasir 11991, Saudi Arabia
    Computers and Automatic Control Engineering Department, Faculty of Engineering, Tanta University, Tanta 31733, Egypt)

  • Mohammad Ali Abdelkareem

    (Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates)

  • Hussein M. Maghrabie

    (Faculty of Engineering, South Valley University, Qena 83523, Egypt)

  • Ahmad Baroutaji

    (School of Engineering and Applied Science, Aston University, Aston Triangle, Birmingham B4 7ET, UK)

Abstract

Metaheuristic optimization algorithms are tools based on mathematical concepts that are used to solve complicated optimization issues. These algorithms are intended to locate or develop a sufficiently good solution to an optimization issue, particularly when information is sparse or inaccurate or computer capability is restricted. Power systems play a crucial role in promoting environmental sustainability by reducing greenhouse gas emissions and supporting renewable energy sources. Using metaheuristics to optimize the performance of modern power systems is an attractive topic. This research paper investigates the applicability of several metaheuristic optimization algorithms to power system challenges. Firstly, this paper reviews the fundamental concepts of metaheuristic optimization algorithms. Then, six problems regarding the power systems are presented and discussed. These problems are optimizing the power flow in transmission and distribution networks, optimizing the reactive power dispatching, optimizing the combined economic and emission dispatching, optimal Volt/Var controlling in the distribution power systems, and optimizing the size and placement of DGs. A list of several used metaheuristic optimization algorithms is presented and discussed. The relevant results approved the ability of the metaheuristic optimization algorithm to solve the power system problems effectively. This, in particular, explains their wide deployment in this field.

Suggested Citation

  • Ahmed M. Nassef & Mohammad Ali Abdelkareem & Hussein M. Maghrabie & Ahmad Baroutaji, 2023. "Review of Metaheuristic Optimization Algorithms for Power Systems Problems," Sustainability, MDPI, vol. 15(12), pages 1-27, June.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:12:p:9434-:d:1169178
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    References listed on IDEAS

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    1. Hegazy Rezk & A. G. Olabi & Enas Taha Sayed & Tabbi Wilberforce, 2023. "Role of Metaheuristics in Optimizing Microgrids Operating and Management Issues: A Comprehensive Review," Sustainability, MDPI, vol. 15(6), pages 1-27, March.
    2. Muhammad Haris Khan & Abasin Ulasyar & Abraiz Khattak & Haris Sheh Zad & Mohammad Alsharef & Ahmad Aziz Alahmadi & Nasim Ullah, 2022. "Optimal Sizing and Allocation of Distributed Generation in the Radial Power Distribution System Using Honey Badger Algorithm," Energies, MDPI, vol. 15(16), pages 1-18, August.
    3. Hegazy Rezk & A. G. Olabi & Tabbi Wilberforce & Enas Taha Sayed, 2023. "A Comprehensive Review and Application of Metaheuristics in Solving the Optimal Parameter Identification Problems," Sustainability, MDPI, vol. 15(7), pages 1-24, March.
    4. Niknam, Taher & Firouzi, Bahman Bahmani & Ostadi, Amir, 2010. "A new fuzzy adaptive particle swarm optimization for daily Volt/Var control in distribution networks considering distributed generators," Applied Energy, Elsevier, vol. 87(6), pages 1919-1928, June.
    5. Zare, Mohsen & Niknam, Taher, 2013. "A new multi-objective for environmental and economic management of Volt/Var Control considering renewable energy resources," Energy, Elsevier, vol. 55(C), pages 236-252.
    6. Panda, Ambarish & Tripathy, M., 2015. "Security constrained optimal power flow solution of wind-thermal generation system using modified bacteria foraging algorithm," Energy, Elsevier, vol. 93(P1), pages 816-827.
    7. Adolfo Blengini Neto & Maria Beatriz Barbosa & Lia Moreira Mota & Marina Lavorato & Marcius F. H. de Carvalho, 2022. "Optimal Power Flow Technique for Distribution System Considering Distributed Energy Resources (DER)," Energies, MDPI, vol. 15(22), pages 1-16, November.
    8. Gianfranco Chicco & Andrea Mazza, 2020. "Metaheuristic Optimization of Power and Energy Systems: Underlying Principles and Main Issues of the ‘Rush to Heuristics’," Energies, MDPI, vol. 13(19), pages 1-38, September.
    9. Mahdi, Fahad Parvez & Vasant, Pandian & Kallimani, Vish & Watada, Junzo & Fai, Patrick Yeoh Siew & Abdullah-Al-Wadud, M., 2018. "A holistic review on optimization strategies for combined economic emission dispatch problem," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 3006-3020.
    10. Abdulaziz Alshammari & Rakan C. Chabaan, 2023. "Metaheruistic Optimization Based Ensemble Machine Learning Model for Designing Detection Coil with Prediction of Electric Vehicle Charging Time," Sustainability, MDPI, vol. 15(8), pages 1-17, April.
    11. Abdelaziz, A.Y. & Ali, E.S. & Abd Elazim, S.M., 2016. "Implementation of flower pollination algorithm for solving economic load dispatch and combined economic emission dispatch problems in power systems," Energy, Elsevier, vol. 101(C), pages 506-518.
    12. Sultana, U. & Khairuddin, Azhar B. & Mokhtar, A.S. & Zareen, N. & Sultana, Beenish, 2016. "Grey wolf optimizer based placement and sizing of multiple distributed generation in the distribution system," Energy, Elsevier, vol. 111(C), pages 525-536.
    13. Warid Warid & Hashim Hizam & Norman Mariun & Noor Izzri Abdul-Wahab, 2016. "Optimal Power Flow Using the Jaya Algorithm," Energies, MDPI, vol. 9(9), pages 1-18, August.
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