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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM67018

Fuzzy Logic Based Load Frequency Control of a Single Area Power System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM67018

Volume:

10 |

8 |

Aug 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM67018

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GUNJAN SAHU

GUNJAN SAHU

Department of Electrical Engineering

RSR Rungta College of Engineering and Technology, Bhilai, India.

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Mentors

Satya Prakash Makhija

Satya Prakash Makhija

Department of Electrical Engineering

RSR Rungta College of Engineering and Technology, Bhilai, India.

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Abstract

Load frequency control (LFC) is a fundamental requirement for maintaining the stability and reliability of an electric power system, particularly under continuously varying load demand. Any mismatch between generation and demand manifests as a deviation in system frequency, which must be corrected quickly and with minimum oscillation in order to keep the network within its permissible operating limits. This paper investigates the load frequency control of a single area power system, consisting of a speed governor, turbine, generator and load demand, using four different controllers: a conventional Proportional Integral (PI) controller, a Proportional Integral Derivative (PID) controller, a Fuzzy Logic Controller (FLC), and a Fuzzy Tuned PI (FTPI) controller in which the fuzzy inference system dynamically supplies the proportional and integral gains. The controllers are designed and simulated in the MATLAB/SIMULINK environment. Their closed-loop frequency responses are compared based on peak frequency deviation, settling time, steady-state error (SSE), Integral Absolute Error (IAE), and Integral Time Absolute Error (ITAE). A comprehensive comparative analysis is carried out to identify the controller that provides the best overall trade-off between transient response, steady-state accuracy, and error minimization for the single-area power system.

KEYWORDS

Load frequency control PI controller PID controller Fuzzy logic controller Fuzzy tuned PI controller Single area power system.

Cite This Article

GUNJAN SAHU, Satya Prakash Makhija, "Fuzzy Logic Based Load Frequency Control of a Single Area Power System," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 8, pp. 1-4, Aug 2026. https://doi.org/10.55041/IJSREM67018

Full Article/Conclusion

This paper has presented the design and comparative evaluation of PI, PID, fuzzy logic, and fuzzy tuned PI controllers for the load frequency control of a single area power system. The gains of the conventional PI and PID controllers were obtained using the Cohen–Coon reaction curve tuning method, while the fuzzy logic and fuzzy tuned PI controllers were designed using a two-input, one-output for fuzzy logic case and two-output for the FTPI case. fuzzy inference system based on the frequency error and its rate of change. Simulation results for a step change in load demand show that, while the conventional PI controller is effective at removing steady-state frequency error, the fuzzy-based controllers and in particular the fuzzy tuned PI controller offer a noticeably faster transient response for the single area system. Future work may extend this single area study to a two-area or multi-area interconnected system, and may also explore metaheuristic optimisation of the fuzzy rule base and membership functions to further improve the dynamic performance of the controller.

References

[1] Thenmalar, K. J. M. T. P. (2021). Fuzzy logic based load frequency control of power system. Materials Today: Proceedings, 45, 8170-8175.. [2] Buragohain, A. R., & Das, D. N. K. (2024). Load frequency control of a single area system using fuzzy logic controller and comparison with integral and PID controller. Available at SSRN 4958990. [3] Singh, A., Yadav, S., Tiwari, N., Nishad, D. K., & Khalid, S. (2025). Optimized PID controller and model order reduction of reheated turbine for load frequency control using teaching learning-based optimization. Scientific Reports, 15(1), 3759. [4] Abazari, A., Monsef, H., & Wu, B. (2019). Load frequency control by de‐loaded wind farm using the optimal fuzzy‐based PID droop controller. IET Renewable Power Generation, 13(1), 180-190. [5] Kheshti, M., Ding, L., Askarian‐Abyaneh, H., Singh, A. R., Zare, S., & Terzija, V. (2021). Improving frequency regulation of wind‐integrated multi‐area systems using LFA‐fuzzy PID control. International Transactions on Electrical Energy Systems, 31(3), e12802. [6] Dokht Shakibjoo, A., Moradzadeh, M., Moussavi, S. Z., & Vandevelde, L. (2020). A novel technique for load frequency control of multi-area power systems. Energies, 13(9), 2125. [7] Jan, M. U., Xin, A., Abdelbaky, M. A., Rehman, H. U., & Iqbal, S. (2020). Adaptive and fuzzy PI controllers design for frequency regulation of isolated microgrid integrated with electric vehicles. IEEe Access, 8, 87621-87632. [8] Yakout, A. H., Kotb, H., Hasanien, H. M., & Aboras, K. M. (2021). Optimal fuzzy PIDF load frequency controller for hybrid microgrid system using marine predator algorithm. IEEe Access, 9, 54220-54232. [9] Dahab, Y. A., Abubakr, H., & Mohamed, T. H. (2020). Adaptive load frequency control of power systems using electro-search optimization supported by the balloon effect. IEEE access, 8, 7408-7422. [10] Al-Majidi, S. D., Kh. AL-Nussairi, M., Mohammed, A. J., Dakhil, A. M., Abbod, M. F., & Al-Raweshidy, H. S. (2022). Design of a load frequency controller based on an optimal neural network. Energies, 15(17), 6223.

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Publication Date

8/31/2026

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Double-Blind Peer Review

Review Rounds: 2

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