research-article

Fractional-Order PID Controller Design Optimization for Load Frequency Control via Flower Pollination Algorithm

Authors:

Thitipong Niyomsat,

Deacha PuangdownreongAuthors Info & Claims

AICCC '19: Proceedings of the 2019 2nd Artificial Intelligence and Cloud Computing Conference

Pages 197 - 202

https://doi.org/10.1145/3375959.3375963

Published: 16 February 2020 Publication History

Abstract

This paper presents a design of an optimal fractional-order PID (FOPID) controller for the load frequency control (LFC) in power systems. Based on the modern optimization, the flower pollination algorithm (FPA) is utilized by searching for the appropriate values of the FOPID parameters for the given LFC in the single area power system. To perform its effectiveness, the FOPID controllers optimized by the FPA are tested against three different turbines in power systems, i.e. non-reheated, reheated and hydro turbines. Results obtained by the FOPID will be compared with those obtained by the conventional integer-order PID (IOPID) controller. As results, it was found that both IOPID and FOPID controllers designed by the FPA can improve the damping of the power system responses. However, the FOPID controller shows superior results to the IOPID by giving very satisfactory responses with less damping and faster recovering for all cases.

References

[1]

Kundur, P. 1994. Power System Stability and Control. McGraw-Hill, New York.

[2]

Elgerd, O. I. 1983. Electric Energy Systems Theory: An Introduction. McGraw-Hill, New Delhi.

[3]

Shayeghi, H., Shayanfar, H. A., and Jalili, A. 2009. Load frequency control strategies: a state-of-the-art survey for the researcher. Energy Conversion and Management. 50, 344--353.

[4]

Hote, Y. V. and Jain, S. 2018. PID controller design for load frequency control: past, present and future challenges. IFAC-PaperOnLine. 51, 4, 604--609.

[5]

Alhelou, H. H., Hamedani-Golshan, M-E., Zamani, R., Heydarian-Forushani, E. and Siano, P. 2018. Challenges and opportunities of load frequency control in conventional, modern and future smart power systems: a comprehensive review. Energies. 11, 2497, 1--35.

[6]

Cavin, R. K., Budge, M. C., and Rasmussen, P. 1971. An optimal linear system approach to load frequency control. IEEE Transactions on Power Apparatus and Systems. PAS-90, 6, 2472--2482.

[7]

Vrdoljak, K., Peri, N., and Petrovi, I. 2010. Sliding mode based load-frequency control in power systems. Electric Power Systems Research. 80, 5, 514--527.

[8]

Tan, W. 2010. Unified tuning of PID load frequency controller for power systems via IMC. IEEE Transactions on Power Systems. 25, 1, 341--350.

[9]

Moon, Y.H., Ryu, H.S., Lee, J.G., and Kim, S. 2001. Power system load frequency control using noise-tolerable PID feedback. In Proceedings of the IEEE International Symposium on Industrial Electronics. 3, 1714--1718.

[10]

Jain, S. and Hote, Y. V. 2018. Design of fractional PID for Load frequency control via internal model control and big bang big crunch optimization. In Proceedings of the 3rd IFAC Conference on Advances in Proportional-Integral-Derivative Control. 610--615.

[11]

Delassi, A., Arif, S., and Mokrani, L. 2014. Comparison between PID, fractional PID and Fuzzy PID for load frequency control problem. In Proceedings of the International Conference on Information Processing and Electrical Engineering (ICIPEE14).

[12]

Podlubny, I. 1994. Fractional-Order Systems and Fractional-Order Controllers. UEF-03-94, Slovak Academy of Sciences, Kosice.

[13]

Podlubny, I. 1999. Fractional-order systems and PIλDμ-controllers. IEEE Transactions on Automatic Control. 44, 1, 208--214.

[14]

Chen, Y. Q., Petráš, I., and Dingyü, X. 2009. Fractional order control - a tutorial. In Proceedings of the American Control Conference. 1397--1411.

[15]

Shah, P. and Agashe, A. 2016. Review of fractional PID controller. Mechatronics. 38, 29--41.

[16]

Yang, X. S. 2012. Flower pollination algorithm for global optimization, unconventional computation and natural computation. Lecture Notes in Computer Science. 7445, 240--249.

Digital Library

[17]

Yang, X. S., Karamanoglua, M., and He, X. 2013. Multi-objective flower algorithm for optimization. Procedia Computer Science. 18, 861--868.

[18]

He, X. S., Yang, X. S., Karamanoglua, M., and Zhao, Y. X. 2017. Global convergence analysis of the flower pollination algorithm: a discrete-time Markov chain approach. Procedia Computer Science. 108, 1354--1364.

[19]

Chiroma, H., Shuib, N. L. M., Muaz, S. A., Abubakar, A. I., Ila, L. B., and Maitama, J. Z. 2015. A review of the applications of bio-inspired flower pollination algorithm. Procedia Computer Science. 62, 435--441.

[20]

Tepljakov, A. 2015. Fractional-order Modeling and Control of Dynamic Systems. Ph.D Dissertation of the Degree of Doctor of Philosophy in Informatics and System Engineering. Tallinn University of Technology, Estonia.

[21]

Tepljakov, A., Petlenkov, E., and Belikov, J. 2011. FOMCON: fractional-order modeling and control toolbox for MATLAB, In Proceedings of the 18th International Conference on Mixed Design of Integrated Circuits and Systems (MIXDES '11), 684--689.

[22]

Tepljakov, A., Petlenkov, E., and Belikov, J. 2011. FOMCON: a MATLAB toolbox for fractional-order system identification and control. International Journal of Microelectronics and Computer Science. 2, 2, 51--62.

Cited By

Hongesombut KKeteruksa R(2023)Fractional order based on a flower pollination algorithm PID controller and virtual inertia control for microgrid frequency stabilizationElectric Power Systems Research10.1016/j.epsr.2023.109381220(109381)Online publication date: Jul-2023
https://doi.org/10.1016/j.epsr.2023.109381
Keteruksa RHongesombut K(2022)Fractional Order based on the Flower Pollination Algorithm PID controller for Community Microgrids2022 19th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)10.1109/ECTI-CON54298.2022.9795553(1-5)Online publication date: 24-May-2022
https://doi.org/10.1109/ECTI-CON54298.2022.9795553
Sudha T(2021)Multi-Objective Optimization Based Multi-Objective Controller Tuning Method with Robust Stabilization of Fractional Calculus CSTRWSEAS TRANSACTIONS ON SYSTEMS AND CONTROL10.37394/23203.2021.16.3216(375-382)Online publication date: 8-Jul-2021
https://doi.org/10.37394/23203.2021.16.32
Show More Cited By

Index Terms

Fractional-Order PID Controller Design Optimization for Load Frequency Control via Flower Pollination Algorithm
1. Mathematics of computing
  1. Mathematical analysis
    1. Mathematical optimization
      1. Discrete optimization
        Optimization with randomized search heuristics

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AICCC '19: Proceedings of the 2019 2nd Artificial Intelligence and Cloud Computing Conference

December 2019

216 pages

ISBN:9781450372633

DOI:10.1145/3375959

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 16 February 2020

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AICCC 2019: 2019 2nd Artificial Intelligence and Cloud Computing Conference

December 21 - 23, 2019

Kobe, Japan

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Cited By

Hongesombut KKeteruksa R(2023)Fractional order based on a flower pollination algorithm PID controller and virtual inertia control for microgrid frequency stabilizationElectric Power Systems Research10.1016/j.epsr.2023.109381220(109381)Online publication date: Jul-2023
https://doi.org/10.1016/j.epsr.2023.109381
Keteruksa RHongesombut K(2022)Fractional Order based on the Flower Pollination Algorithm PID controller for Community Microgrids2022 19th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)10.1109/ECTI-CON54298.2022.9795553(1-5)Online publication date: 24-May-2022
https://doi.org/10.1109/ECTI-CON54298.2022.9795553
Sudha T(2021)Multi-Objective Optimization Based Multi-Objective Controller Tuning Method with Robust Stabilization of Fractional Calculus CSTRWSEAS TRANSACTIONS ON SYSTEMS AND CONTROL10.37394/23203.2021.16.3216(375-382)Online publication date: 8-Jul-2021
https://doi.org/10.37394/23203.2021.16.32

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