IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i9p1570-d809840.html
   My bibliography  Save this article

Knacks of Fractional Order Swarming Intelligence for Parameter Estimation of Harmonics in Electrical Systems

Author

Listed:
  • Naveed Ahmed Malik

    (Graduate School of Engineering Science and Technology, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan)

  • Ching-Lung Chang

    (Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan)

  • Naveed Ishtiaq Chaudhary

    (Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan)

  • Muhammad Asif Zahoor Raja

    (Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan)

  • Khalid Mehmood Cheema

    (Department of Electronic Engineering, Fatima Jinnah Women University, Rawalpindi 46000, Pakistan)

  • Chi-Min Shu

    (Department of Safety, Health, and Environmental Engineering, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan)

  • Sultan S. Alshamrani

    (Department of Information Technology, College of Computer and Information Technology, Taif University, Taif 21944, Saudi Arabia)

Abstract

The efficient parameter estimation of harmonics is required to effectively design filters to mitigate their adverse effects on the power quality of electrical systems. In this study, a fractional order swarming optimization technique is proposed for the parameter estimation of harmonics normally present in industrial loads. The proposed fractional order particle swarm optimization (FOPSO) effectively estimates the amplitude and phase parameters corresponding to the first, third, fifth, seventh and eleventh harmonics. The performance of the FOPSO was evaluated for ten fractional orders with noiseless and noisy scenarios. The robustness efficiency of the proposed FOPSO was analyzed by considering different levels of additive white Gaussian noise in the harmonic signal. Monte Carlo simulations confirmed the reliability of the FOPSO for a lower fractional order ( λ = 0.1) with a faster convergence rate and no divergent run compared to other fractional orders as well as to standard PSO ( λ = 1).

Suggested Citation

  • Naveed Ahmed Malik & Ching-Lung Chang & Naveed Ishtiaq Chaudhary & Muhammad Asif Zahoor Raja & Khalid Mehmood Cheema & Chi-Min Shu & Sultan S. Alshamrani, 2022. "Knacks of Fractional Order Swarming Intelligence for Parameter Estimation of Harmonics in Electrical Systems," Mathematics, MDPI, vol. 10(9), pages 1-20, May.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:9:p:1570-:d:809840
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/9/1570/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/9/1570/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ling Xu & Feng Ding & Quanmin Zhu, 2021. "Decomposition strategy-based hierarchical least mean square algorithm for control systems from the impulse responses," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(9), pages 1806-1821, July.
    2. Ahmet Ocak Akdemir & Saad Ihsan Butt & Muhammad Nadeem & Maria Alessandra Ragusa, 2021. "New General Variants of Chebyshev Type Inequalities via Generalized Fractional Integral Operators," Mathematics, MDPI, vol. 9(2), pages 1-10, January.
    3. Mohammadian, M. & Lorestani, A. & Ardehali, M.M., 2018. "Optimization of single and multi-areas economic dispatch problems based on evolutionary particle swarm optimization algorithm," Energy, Elsevier, vol. 161(C), pages 710-724.
    4. Zeshan Aslam Khan & Naveed Ishtiaq Chaudhary & Syed Zubair, 2019. "Fractional stochastic gradient descent for recommender systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 275-285, June.
    5. Chaudhary, Naveed Ishtiaq & Raja, Muhammad Asif Zahoor & Khan, Zeshan Aslam & Mehmood, Ammara & Shah, Syed Muslim, 2022. "Design of fractional hierarchical gradient descent algorithm for parameter estimation of nonlinear control autoregressive systems," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    6. Natthanon Phannil & Chaiyan Jettanasen & Atthapol Ngaopitakkul, 2018. "Harmonics and Reduction of Energy Consumption in Lighting Systems by Using LED Lamps," Energies, MDPI, vol. 11(11), pages 1-27, November.
    7. Abedi Pahnehkolaei, Seyed Mehdi & Alfi, Alireza & Tenreiro Machado, J.A., 2022. "Analytical stability analysis of the fractional-order particle swarm optimization algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    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. Naveed Ahmed Malik & Naveed Ishtiaq Chaudhary & Muhammad Asif Zahoor Raja, 2023. "Firefly Optimization Heuristics for Sustainable Estimation in Power System Harmonics," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    2. Khizer Mehmood & Naveed Ishtiaq Chaudhary & Zeshan Aslam Khan & Muhammad Asif Zahoor Raja & Khalid Mehmood Cheema & Ahmad H. Milyani, 2022. "Design of Aquila Optimization Heuristic for Identification of Control Autoregressive Systems," Mathematics, MDPI, vol. 10(10), pages 1-23, May.

    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. Chaudhary, Naveed Ishtiaq & Khan, Zeshan Aslam & Kiani, Adiqa Kausar & Raja, Muhammad Asif Zahoor & Chaudhary, Iqra Ishtiaq & Pinto, Carla M.A., 2022. "Design of auxiliary model based normalized fractional gradient algorithm for nonlinear output-error systems," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    2. Mehmood, Khizer & Chaudhary, Naveed Ishtiaq & Khan, Zeshan Aslam & Cheema, Khalid Mehmood & Raja, Muhammad Asif Zahoor & Shu, Chi-Min, 2023. "Novel knacks of chaotic maps with Archimedes optimization paradigm for nonlinear ARX model identification with key term separation," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    3. Ce Zhang & Xiangxiang Meng & Yan Ji, 2023. "Parameter Estimation of Fractional Wiener Systems with the Application of Photovoltaic Cell Models," Mathematics, MDPI, vol. 11(13), pages 1-22, June.
    4. Stefano Lodetti & Izaskun Azcarate & José Julio Gutiérrez & Luis Alberto Leturiondo & Koldo Redondo & Purificación Sáiz & Julio J. Melero & Jorge Bruna, 2019. "Flicker of Modern Lighting Technologies Due to Rapid Voltage Changes," Energies, MDPI, vol. 12(5), pages 1-16, March.
    5. Xue-Bo Jin & Wen-Tao Gong & Jian-Lei Kong & Yu-Ting Bai & Ting-Li Su, 2022. "PFVAE: A Planar Flow-Based Variational Auto-Encoder Prediction Model for Time Series Data," Mathematics, MDPI, vol. 10(4), pages 1-17, February.
    6. Wang, Yajun & Wang, Jidong & Cao, Man & Kong, Xiangyu & Abderrahim, Bouchedjira & Yuan, Long & Vartosh, Aris, 2023. "Dynamic emission dispatch considering the probabilistic model with multiple smart energy system players based on a developed fuzzy theory-based harmony search algorithm," Energy, Elsevier, vol. 269(C).
    7. Jairo Hernández & Andrés A. Romero & Jan Meyer & Ana María Blanco, 2020. "Impact of Nonlinear Lighting Loads on the Neutral Conductor Current of Low Voltage Residential Grids," Energies, MDPI, vol. 13(18), pages 1-20, September.
    8. Chaudhary, Naveed Ishtiaq & Raja, Muhammad Asif Zahoor & Khan, Zeshan Aslam & Mehmood, Ammara & Shah, Syed Muslim, 2022. "Design of fractional hierarchical gradient descent algorithm for parameter estimation of nonlinear control autoregressive systems," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    9. Khan, Zeshan Aslam & Chaudhary, Naveed Ishtiaq & Khan, Taimoor Ali & Farooq, Umair & Pinto, Carla M.A. & Raja, Muhammad Asif Zahoor, 2023. "Enhanced fractional prediction scheme for effective matrix factorization in chaotic feedback recommender systems," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    10. Fatma Yaprakdal & Mustafa Baysal & Amjad Anvari-Moghaddam, 2019. "Optimal Operational Scheduling of Reconfigurable Microgrids in Presence of Renewable Energy Sources," Energies, MDPI, vol. 12(10), pages 1-17, May.
    11. Huang, Yuqing & Lan, Hai & Hong, Ying-Yi & Wen, Shuli & Yin, He, 2019. "Optimal generation scheduling for a deep-water semi-submersible drilling platform with uncertain renewable power generation and loads," Energy, Elsevier, vol. 181(C), pages 897-907.
    12. Liu, Lianggui & Zhang, Rui & Chen, Qiuxia, 2022. "High-performance global peak tracking technique for PV arrays subject to rapidly changing PSC," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    13. Zhang, Heng & Hu, Xiao & Cheng, Haozhong & Zhang, Shenxi & Hong, Shaoyun & Gu, Qingfa, 2021. "Coordinated scheduling of generators and tie lines in multi-area power systems under wind energy uncertainty," Energy, Elsevier, vol. 222(C).
    14. Yurdagül Benteşen Yakut, 2024. "Optimization of Proportional–Integral (PI) and Fractional-Order Proportional–Integral (FOPI) Parameters Using Particle Swarm Optimization/Genetic Algorithm (PSO/GA) in a DC/DC Converter for Improving ," Energies, MDPI, vol. 17(4), pages 1-20, February.
    15. Saad Ihsan Butt & Josip Pečarić & Sanja Tipurić-Spužević, 2023. "Generalized Čebyšev and Grüss Type Results in Weighted Lebesgue Spaces," Mathematics, MDPI, vol. 11(7), pages 1-19, April.
    16. Song, Dongran & Liu, Junbo & Yang, Jian & Su, Mei & Wang, Yun & Yang, Xuebing & Huang, Lingxiang & Joo, Young Hoon, 2020. "Optimal design of wind turbines on high-altitude sites based on improved Yin-Yang pair optimization," Energy, Elsevier, vol. 193(C).
    17. Yunqi Jiang & Huaqing Zhang & Kai Zhang & Jian Wang & Shiti Cui & Jianfa Han & Liming Zhang & Jun Yao, 2022. "Reservoir Characterization and Productivity Forecast Based on Knowledge Interaction Neural Network," Mathematics, MDPI, vol. 10(9), pages 1-22, May.
    18. Meng, Anbo & Zeng, Cong & Xu, Xuancong & Ding, Weifeng & Liu, Shiyun & Chen, De & Yin, Hao, 2022. "Decentralized power economic dispatch by distributed crisscross optimization in multi-agent system," Energy, Elsevier, vol. 246(C).
    19. Sharifian, Yeganeh & Abdi, Hamdi, 2023. "Solving multi-area economic dispatch problem using hybrid exchange market algorithm with grasshopper optimization algorithm," Energy, Elsevier, vol. 267(C).
    20. Dhivya Swaminathan & Arul Rajagopalan & Oscar Danilo Montoya & Savitha Arul & Luis Fernando Grisales-Noreña, 2023. "Distribution Network Reconfiguration Based on Hybrid Golden Flower Algorithm for Smart Cities Evolution," Energies, MDPI, vol. 16(5), pages 1-24, 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:jmathe:v:10:y:2022:i:9:p:1570-:d:809840. 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.