IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i17p4316-d401594.html
   My bibliography  Save this article

Solving the Optimal Reactive Power Dispatch Using Marine Predators Algorithm Considering the Uncertainties in Load and Wind-Solar Generation Systems

Author

Listed:
  • Mohamed Ebeed

    (Department of Electrical Engineering, Faculty of Engineering, Sohag University, Sohag 82524, Egypt)

  • Ayman Alhejji

    (Department of Electrical and Electronics Engineering Technology, Yanbu Industrial College, Yanbu Industrial City 41912, Saudi Arabia)

  • Salah Kamel

    (Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt)

  • Francisco Jurado

    (Department of Electrical Engineering, University of Jaén, EPS Linares, 23700 Jaén, Spain)

Abstract

The optimal reactive power dispatch (ORPD) problem is an important issue to assign the most efficient and secure operating point of the electrical system. The ORPD became a strenuous task, especially with the high penetration of renewable energy resources due to the intermittent and stochastic nature of wind speed and solar irradiance. In this paper, the ORPD is solved using a new natural inspired algorithm called the marine predators’ algorithm (MPA) considering the uncertainties of the load demand and the output powers of wind and solar generation systems. The scenario-based method is applied to handle the uncertainties of the system by generating deterministic scenarios from the probability density functions of the system parameters. The proposed algorithm is applied to solve the ORPD of the IEEE-30 bus system to minimize the power loss and the system voltage devotions. The result verifies that the proposed method is an efficient method for solving the ORPD compared with the state-of-the-art techniques.

Suggested Citation

  • Mohamed Ebeed & Ayman Alhejji & Salah Kamel & Francisco Jurado, 2020. "Solving the Optimal Reactive Power Dispatch Using Marine Predators Algorithm Considering the Uncertainties in Load and Wind-Solar Generation Systems," Energies, MDPI, vol. 13(17), pages 1-19, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4316-:d:401594
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/17/4316/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/17/4316/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shargh, S. & Khorshid ghazani, B. & Mohammadi-ivatloo, B. & Seyedi, H. & Abapour, M., 2016. "Probabilistic multi-objective optimal power flow considering correlated wind power and load uncertainties," Renewable Energy, Elsevier, vol. 94(C), pages 10-21.
    2. Zahir Sahli & Abdellatif Hamouda & Abdelghani Bekrar & Damien Trentesaux, 2018. "Reactive Power Dispatch Optimization with Voltage Profile Improvement Using an Efficient Hybrid Algorithm †," Energies, MDPI, vol. 11(8), pages 1-21, August.
    3. Zelan Li & Yijia Cao & Le Van Dai & Xiaoliang Yang & Thang Trung Nguyen, 2019. "Finding Solutions for Optimal Reactive Power Dispatch Problem by a Novel Improved Antlion Optimization Algorithm," Energies, MDPI, vol. 12(15), pages 1-31, August.
    4. Soroudi, Alireza & Amraee, Turaj, 2013. "Decision making under uncertainty in energy systems: State of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 376-384.
    5. Walter M. Villa-Acevedo & Jesús M. López-Lezama & Jaime A. Valencia-Velásquez, 2018. "A Novel Constraint Handling Approach for the Optimal Reactive Power Dispatch Problem," Energies, MDPI, vol. 11(9), pages 1-23, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wenbiao Yang & Kewen Xia & Tiejun Li & Min Xie & Fei Song, 2021. "A Multi-Strategy Marine Predator Algorithm and Its Application in Joint Regularization Semi-Supervised ELM," Mathematics, MDPI, vol. 9(3), pages 1-34, February.
    2. Umar Salman & Khalid Khan & Fahad Alismail & Muhammad Khalid, 2021. "Techno-Economic Assessment and Operational Planning of Wind-Battery Distributed Renewable Generation System," Sustainability, MDPI, vol. 13(12), pages 1-24, June.
    3. Khizer Mehmood & Naveed Ishtiaq Chaudhary & Zeshan Aslam Khan & Khalid Mehmood Cheema & Muhammad Asif Zahoor Raja & Ahmad H. Milyani & Abdullah Ahmed Azhari, 2022. "Nonlinear Hammerstein System Identification: A Novel Application of Marine Predator Optimization Using the Key Term Separation Technique," Mathematics, MDPI, vol. 10(22), pages 1-22, November.
    4. Shahenda Sarhan & Abdullah Shaheen & Ragab El-Sehiemy & Mona Gafar, 2023. "An Augmented Social Network Search Algorithm for Optimal Reactive Power Dispatch Problem," Mathematics, MDPI, vol. 11(5), pages 1-42, March.
    5. Lenin Kanagasabai, 2022. "Buoyancy based optimization algorithm for real power loss diminution," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2442-2457, October.
    6. Nasreddine Belbachir & Mohamed Zellagui & Samir Settoul & Claude Ziad El-Bayeh & Ragab A. El-Sehiemy, 2023. "Multi Dimension-Based Optimal Allocation of Uncertain Renewable Distributed Generation Outputs with Seasonal Source-Load Power Uncertainties in Electrical Distribution Network Using Marine Predator Al," Energies, MDPI, vol. 16(4), pages 1-24, February.
    7. Sulaiman Z. Almutairi & Emad A. Mohamed & Fayez F. M. El-Sousy, 2023. "A Novel Adaptive Manta-Ray Foraging Optimization for Stochastic ORPD Considering Uncertainties of Wind Power and Load Demand," Mathematics, MDPI, vol. 11(11), pages 1-35, June.
    8. Ashraf Ramadan & Mohamed Ebeed & Salah Kamel & Almoataz Y. Abdelaziz & Hassan Haes Alhelou, 2021. "Scenario-Based Stochastic Framework for Optimal Planning of Distribution Systems Including Renewable-Based DG Units," Sustainability, MDPI, vol. 13(6), pages 1-23, March.
    9. Lenin Kanagasabai, 2023. "Real power loss reduction by extreme learning machine based Panthera leo, chaotic based Jungle search and Quantum based Chipmunk search optimization algorithms," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 55-78, March.
    10. Lenin Kanagasabai, 2022. "Real power loss dwindling and voltage reliability enrichment by gradient based optimization algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2727-2742, October.
    11. Lenin Kanagasabai, 2023. "Legislative optimization algorithm for real power loss diminishing and voltage reliability escalation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(4), pages 1197-1207, August.
    12. Lenin Kanagasabai, 2022. "Mathematics based calculation and stemonitis inspired optimization algorithms for loss reduction and power solidity augmentation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2710-2726, October.
    13. Mohammed Hamouda Ali & Ahmed Mohammed Attiya Soliman & Mohamed Abdeen & Tarek Kandil & Almoataz Y. Abdelaziz & Adel El-Shahat, 2023. "A Novel Stochastic Optimizer Solving Optimal Reactive Power Dispatch Problem Considering Renewable Energy Resources," Energies, MDPI, vol. 16(4), pages 1-39, February.
    14. Andrei M. Tudose & Irina I. Picioroaga & Dorian O. Sidea & Constantin Bulac, 2021. "Solving Single- and Multi-Objective Optimal Reactive Power Dispatch Problems Using an Improved Salp Swarm Algorithm," Energies, MDPI, vol. 14(5), pages 1-20, February.
    15. Umar Waleed & Abdul Haseeb & Muhammad Mansoor Ashraf & Faisal Siddiq & Muhammad Rafiq & Muhammad Shafique, 2022. "A Multiobjective Artificial-Hummingbird-Algorithm-Based Framework for Optimal Reactive Power Dispatch Considering Renewable Energy Sources," Energies, MDPI, vol. 15(23), pages 1-23, December.
    16. Danalakshmi D. & Gopi R. & A. Hariharasudan & Iwona Otola & Yuriy Bilan, 2020. "Reactive Power Optimization and Price Management in Microgrid Enabled with Blockchain," Energies, MDPI, vol. 13(23), pages 1-20, November.
    17. Shahenda Sarhan & Ragab El-Sehiemy & Amlak Abaza & Mona Gafar, 2022. "Turbulent Flow of Water-Based Optimization for Solving Multi-Objective Technical and Economic Aspects of Optimal Power Flow Problems," Mathematics, MDPI, vol. 10(12), pages 1-22, June.

    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. Sulaiman Z. Almutairi & Emad A. Mohamed & Fayez F. M. El-Sousy, 2023. "A Novel Adaptive Manta-Ray Foraging Optimization for Stochastic ORPD Considering Uncertainties of Wind Power and Load Demand," Mathematics, MDPI, vol. 11(11), pages 1-35, June.
    2. Samson Ademola Adegoke & Yanxia Sun, 2023. "Diminishing Active Power Loss and Improving Voltage Profile Using an Improved Pathfinder Algorithm Based on Inertia Weight," Energies, MDPI, vol. 16(3), pages 1-14, January.
    3. Ashraf Ramadan & Mohamed Ebeed & Salah Kamel & Almoataz Y. Abdelaziz & Hassan Haes Alhelou, 2021. "Scenario-Based Stochastic Framework for Optimal Planning of Distribution Systems Including Renewable-Based DG Units," Sustainability, MDPI, vol. 13(6), pages 1-23, March.
    4. Ovidiu Ivanov & Bogdan-Constantin Neagu & Gheorghe Grigoras & Mihai Gavrilas, 2019. "Optimal Capacitor Bank Allocation in Electricity Distribution Networks Using Metaheuristic Algorithms," Energies, MDPI, vol. 12(22), pages 1-36, November.
    5. S. N. V. S. K. Chaitanya & R. Ashok Bakkiyaraj & B. Venkateswara Rao, 2023. "Multi objective optimal reactive power dispatch for enrichment of power system behavior using modified ant lion optimizer," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 133-142, March.
    6. Mohammed Hamouda Ali & Ahmed Mohammed Attiya Soliman & Mohamed Abdeen & Tarek Kandil & Almoataz Y. Abdelaziz & Adel El-Shahat, 2023. "A Novel Stochastic Optimizer Solving Optimal Reactive Power Dispatch Problem Considering Renewable Energy Resources," Energies, MDPI, vol. 16(4), pages 1-39, February.
    7. Asma Meddeb & Nesrine Amor & Mohamed Abbes & Souad Chebbi, 2018. "A Novel Approach Based on Crow Search Algorithm for Solving Reactive Power Dispatch Problem," Energies, MDPI, vol. 11(12), pages 1-16, November.
    8. Soroudi, Alireza & Rabiee, Abbas & Keane, Andrew, 2017. "Distribution networks' energy losses versus hosting capacity of wind power in the presence of demand flexibility," Renewable Energy, Elsevier, vol. 102(PB), pages 316-325.
    9. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    10. Xiaoyang Deng & Jinghan He & Pei Zhang, 2017. "A Novel Probabilistic Optimal Power Flow Method to Handle Large Fluctuations of Stochastic Variables," Energies, MDPI, vol. 10(10), pages 1-21, October.
    11. Marcin Rabe & Dalia Streimikiene & Yuriy Bilan, 2019. "The Concept of Risk and Possibilities of Application of Mathematical Methods in Supporting Decision Making for Sustainable Energy Development," Sustainability, MDPI, vol. 11(4), pages 1-24, February.
    12. 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.
    13. Morshed, Mohammad Javad & Hmida, Jalel Ben & Fekih, Afef, 2018. "A probabilistic multi-objective approach for power flow optimization in hybrid wind-PV-PEV systems," Applied Energy, Elsevier, vol. 211(C), pages 1136-1149.
    14. Guoqiang Sun & Wenxue Wang & Yi Wu & Wei Hu & Zijun Yang & Zhinong Wei & Haixiang Zang & Sheng Chen, 2019. "A Nonlinear Analytical Algorithm for Predicting the Probabilistic Mass Flow of a Radial District Heating Network," Energies, MDPI, vol. 12(7), pages 1-20, March.
    15. Caputo, Antonio C. & Federici, Alessandro & Pelagagge, Pacifico M. & Salini, Paolo, 2023. "Offshore wind power system economic evaluation framework under aleatory and epistemic uncertainty," Applied Energy, Elsevier, vol. 350(C).
    16. Peng Cheng & Zhiyu Xu & Ruiye Li & Chao Shi, 2022. "A Hybrid Taguchi Particle Swarm Optimization Algorithm for Reactive Power Optimization of Deep-Water Semi-Submersible Platforms with New Energy Sources," Energies, MDPI, vol. 15(13), pages 1-16, June.
    17. Ahmed Al Ameri & Aouchenni Ounissa & Cristian Nichita & Aouzellag Djamal, 2017. "Power Loss Analysis for Wind Power Grid Integration Based on Weibull Distribution," Energies, MDPI, vol. 10(4), pages 1-16, April.
    18. Shahenda Sarhan & Abdullah Shaheen & Ragab El-Sehiemy & Mona Gafar, 2023. "An Augmented Social Network Search Algorithm for Optimal Reactive Power Dispatch Problem," Mathematics, MDPI, vol. 11(5), pages 1-42, March.
    19. Martín M. Sánchez-Mora & Walter M. Villa-Acevedo & Jesús M. López-Lezama, 2023. "Multi-Area and Multi-Period Optimal Reactive Power Dispatch in Electric Power Systems," Energies, MDPI, vol. 16(17), pages 1-24, September.
    20. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.

    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:17:p:4316-:d:401594. 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.