IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2024i1p18-d1551710.html
   My bibliography  Save this article

Leveraging Harris Hawks Optimization for Enhanced Multi-Objective Optimal Power Flow in Complex Power Systems

Author

Listed:
  • Fahad Alsokhiry

    (Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

The utilization of Harris Hawks Optimization (HHO) for Multi-Objective Optimal Power Flow (MaO-OPF) challenges presented in this paper is both novel and compelling, as this approach has not been previously applied to these types of optimization problems. HHO, which shares characteristics with ant behavior, demonstrates significant strength in addressing high-dimensional, nonlinear optimization issues within power systems. In this study, HHO is implemented on an IEEE 30-bus power system, optimizing six competing objectives: minimizing total fuel cost, emissions, active power loss, reactive power loss, reducing voltage deviation, and enhancing voltage steady state. The effectiveness of HHO is assessed by comparing its performance to two alternative methods, MOEA/D-DRA and NSGA-III. Experimental results reveal that solutions derived from HHO exhibit superior convergence, enhanced diversity maintenance, and higher quality Pareto-optimal solutions compared to the MOEA/D trail algorithms. The research breaks new ground in the application of the Harris Hawks Optimization (HHO) algorithm to the Multi-Objective Optimal Power Flow (MaO-OPF) problem. The restructuring not only incorporates self-adaptive constraint-handling techniques and dynamic exploration exploitation strategies, but also addresses the more pressing requirements of modern power systems with even better convergence, and both sequential and global computational efficiency than existing skill. This approach proves to be a powerful and effective solution for addressing the complex challenges associated with MaO, enabling power systems to manage multiple conflicting objectives more efficiently.

Suggested Citation

  • Fahad Alsokhiry, 2024. "Leveraging Harris Hawks Optimization for Enhanced Multi-Objective Optimal Power Flow in Complex Power Systems," Energies, MDPI, vol. 18(1), pages 1-33, December.
    • Handle: RePEc:gam:jeners:v:18:y:2024:i:1:p:18-:d:1551710
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/1/18/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/1/18/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David W. Sims & Emily J. Southall & Nicolas E. Humphries & Graeme C. Hays & Corey J. A. Bradshaw & Jonathan W. Pitchford & Alex James & Mohammed Z. Ahmed & Andrew S. Brierley & Mark A. Hindell & David, 2008. "Scaling laws of marine predator search behaviour," Nature, Nature, vol. 451(7182), pages 1098-1102, February.
    2. Paraskevas Koukaras & Konstantinos D. Afentoulis & Pashalis A. Gkaidatzis & Aristeidis Mystakidis & Dimosthenis Ioannidis & Stylianos I. Vagropoulos & Christos Tjortjis, 2024. "Integrating Blockchain in Smart Grids for Enhanced Demand Response: Challenges, Strategies, and Future Directions," Energies, MDPI, vol. 17(5), pages 1-32, February.
    3. Nicolas E. Humphries & Nuno Queiroz & Jennifer R. M. Dyer & Nicolas G. Pade & Michael K. Musyl & Kurt M. Schaefer & Daniel W. Fuller & Juerg M. Brunnschweiler & Thomas K. Doyle & Jonathan D. R. Hought, 2010. "Environmental context explains Lévy and Brownian movement patterns of marine predators," Nature, Nature, vol. 465(7301), pages 1066-1069, June.
    4. Abdulaziz Almalaq & Tawfik Guesmi & Saleh Albadran, 2023. "A Hybrid Chaotic-Based Multiobjective Differential Evolution Technique for Economic Emission Dispatch Problem," Energies, MDPI, vol. 16(12), pages 1-34, June.
    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. Bi, Zhimin & Liu, Shutang & Ouyang, Miao, 2022. "Spatial dynamics of a fractional predator-prey system with time delay and Allee effect," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    2. Toman, Kellan & Voulgarakis, Nikolaos K., 2022. "Stochastic pursuit-evasion curves for foraging dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    3. Cao, Jiajia & Zhou, Yanbin & Wei, Kun, 2024. "Modeling ants’ walks in patrolling multiple resources using stochastic approximation partial momentum refreshment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    4. Nauta, Johannes & Simoens, Pieter & Khaluf, Yara, 2022. "Group size and resource fractality drive multimodal search strategies: A quantitative analysis on group foraging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    5. Bi, Zhimin & Liu, Shutang & Ouyang, Miao, 2022. "Three-dimensional pattern dynamics of a fractional predator-prey model with cross-diffusion and herd behavior," Applied Mathematics and Computation, Elsevier, vol. 421(C).
    6. Muhammad Irfan & Abdul Wadood & Tahir Khurshaid & Bakht Muhammad Khan & Ki-Chai Kim & Seung-Ryle Oh & Sang-Bong Rhee, 2021. "An Optimized Adaptive Protection Scheme for Numerical and Directional Overcurrent Relay Coordination Using Harris Hawk Optimization," Energies, MDPI, vol. 14(18), pages 1-21, September.
    7. Shinohara, Shuji & Okamoto, Hiroshi & Manome, Nobuhito & Gunji, Pegio-Yukio & Nakajima, Yoshihiro & Moriyama, Toru & Chung, Ung-il, 2022. "Simulation of foraging behavior using a decision-making agent with Bayesian and inverse Bayesian inference: Temporal correlations and power laws in displacement patterns," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    8. Ferreira, A.S. & Raposo, E.P. & Viswanathan, G.M. & da Luz, M.G.E., 2012. "The influence of the environment on Lévy random search efficiency: Fractality and memory effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3234-3246.
    9. Andy Reynolds & Eliane Ceccon & Cristina Baldauf & Tassia Karina Medeiros & Octavio Miramontes, 2018. "Lévy foraging patterns of rural humans," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-16, June.
    10. Pauline Formaglio & Marina E. Wosniack & Raphael M. Tromer & Jaderson G. Polli & Yuri B. Matos & Hang Zhong & Ernesto P. Raposo & Marcos G. E. Luz & Rogerio Amino, 2023. "Plasmodium sporozoite search strategy to locate hotspots of blood vessel invasion," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    11. LaScala-Gruenewald, Diana E. & Mehta, Rohan S. & Liu, Yu & Denny, Mark W., 2019. "Sensory perception plays a larger role in foraging efficiency than heavy-tailed movement strategies," Ecological Modelling, Elsevier, vol. 404(C), pages 69-82.
    12. Hao, Mengli & Jia, Wantao & Wang, Liang & Li, Fuxiao, 2022. "Most probable trajectory of a tumor model with immune response subjected to asymmetric Lévy noise," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    13. Danish A. Ahmed & Sergei V. Petrovskii & Paulo F. C. Tilles, 2018. "The “Lévy or Diffusion” Controversy: How Important Is the Movement Pattern in the Context of Trapping?," Mathematics, MDPI, vol. 6(5), pages 1-27, May.
    14. E P Raposo & F Bartumeus & M G E da Luz & P J Ribeiro-Neto & T A Souza & G M Viswanathan, 2011. "How Landscape Heterogeneity Frames Optimal Diffusivity in Searching Processes," PLOS Computational Biology, Public Library of Science, vol. 7(11), pages 1-8, November.
    15. Andrea Censi & Andrew D Straw & Rosalyn W Sayaman & Richard M Murray & Michael H Dickinson, 2013. "Discriminating External and Internal Causes for Heading Changes in Freely Flying Drosophila," PLOS Computational Biology, Public Library of Science, vol. 9(2), pages 1-14, February.
    16. Sile Hu & Yuan Gao & Yuan Wang & Yuan Yu & Yue Bi & Linfeng Cao & Muhammad Farhan Khan & Jiaqiang Yang, 2024. "Optimal Configuration of Wind–Solar–Thermal-Storage Power Energy Based on Dynamic Inertia Weight Chaotic Particle Swarm," Energies, MDPI, vol. 17(5), pages 1-14, February.
    17. Pierpaolo Andriani & Bill McKelvey, 2009. "Perspective ---From Gaussian to Paretian Thinking: Causes and Implications of Power Laws in Organizations," Organization Science, INFORMS, vol. 20(6), pages 1053-1071, December.
    18. Franziska Matthäus & Mario S Mommer & Tine Curk & Jure Dobnikar, 2011. "On the Origin and Characteristics of Noise-Induced Lévy Walks of E. Coli," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-8, April.
    19. Yang, Yi & Huang, Jin, 2024. "Double fast algorithm for solving time-space fractional diffusion problems with spectral fractional Laplacian," Applied Mathematics and Computation, Elsevier, vol. 475(C).
    20. Gaël Kermarrec, 2020. "On Estimating the Hurst Parameter from Least-Squares Residuals. Case Study: Correlated Terrestrial Laser Scanner Range Noise," Mathematics, MDPI, vol. 8(5), pages 1-23, April.

    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:18:y:2024:i:1:p:18-:d:1551710. 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.