• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2023, Volume: 16, Issue: 39, Pages: 3361-3374

Original Article

Application of Intelligent controller For Load Frequency Control for Multi-Area Multi-Source Power System

Received Date:14 July 2023, Accepted Date:18 September 2023, Published Date:25 October 2023


Objectives: This paper demonstrates the application of an artificial intelligence (AI) based controller for load frequency control for a two-area multi-source interconnected power system. Fuzzy PID controller parameters area Tuned using Artificial BEE colony (ABC) algorithm. The FLC-PID performance is simulated and verified using MATLAB. Method: For evaluating LFC Problem two different systems are considered. The first system consists of four units of the non-reheat thermal power system. The analysis is further extended by adding a hydropower plant unit with a non-reheat thermal unit. A perturbation of 0.01 P.U in step load form is considered for each area for the automatic generation control (AGC) study. Finding: The suggested controller Fuzzy-PID robustness is observed by varying operating loading conditions and plant parameters for a wide range. The variation in time constant (seconds) of system parameters is carried out in a range of +75% to -75%. The objective is to improve the steady-state error of the tie-line power deviation and frequency variation of an interlinked power plant. By the suggested approach, the variation in frequency and tie-line power is minimized to a great extent. Novelty: Artificial BEE colony (ABC) algorithm is effective. The performance of the adapted controller is compared with the previously published tuned PID controller based on Settling Time (ST) and ITAE Error. The proposed controller shows superiority. It is observed that the proposed technique can handle abrupt amplification of load (PU) and variation in system parameters like the governor, and turbine time constant. Eigenvalue analysis is also carried out. The result of the Fuzzy-PID controller is also compared with the proposed-FOPID and Proposed-ANFIS controller. The parameter of fractional order is also optimized by the ABC algorithm. For simulation, MATLAB 2016 @ Version is taken. Keywords: Fuzzy Logic Control (FLC), Automatic Control Error (ACE), Fractional Order PID (FOPID), Adaptive Neuro­Fuzzy Logic Controller (ANFIS), Artificial BEE Colony (ABC), Multi­Source Multi­Area System (MSMAS)


  1. Sharma D. Automatic generation control of multi source interconnected power system using adaptive neuro-fuzzy inference system. International Journal of Engineering, Science and Technology. 2020;12(3):66–80. Available from: https://doi.org/10.4314/ijest.v12i3.7
  2. Ahmadi S, Talami SH, Sahnesaraie MA, Dini F, Tahernejadjozam B, Ashgevari Y. FUZZY aided PID controller is optimized by GA algorithm for Load Frequency Control of Multi-Source Power Systems. 2020 IEEE 18th World Symposium on Applied Machine Intelligence and Informatics (SAMI). 2020. Available from: https://doi.org/10.1109/SAMI48414.2020.9108759
  3. Dash PM, Baliarsingh A, Mohaptra SK. Application hybrid GSAPSO Technique for AGC in Inter Connected Power System with Generation Rate Constant. WSEAS Transactions On Circuits And Systems. 2022;20(1):271–288. Available from: https://doi.org/10.37394/23201.2021.20.31
  4. Ramesh M, Yadav AK, Pathak PK. Artificial Gorilla Troops Optimizer for Frequency Regulation of Wind Contributed Microgrid System. Journal of Computational and Nonlinear Dynamics. 2023;18(1):1–19. Available from: https://doi.org/10.1115/1.4056135
  5. Sahu RK, Panda S, Padhan S. A hybrid firefly algorithm and pattern search technique for automatic generation control of multi area power systems. International Journal of Electrical Power & Energy Systems. 2015;64(1):9–23. Available from: https://doi.org/10.1016/j.ijepes.2014.07.013
  6. Nayak JR, Pati TK, Sahu BK, Kar SK. Fuzzy-PID controller optimized TLBO algorithm on automatic generation control of a two-area interconnected power system. 2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015]. 2015. Available from: https://doi.org/10.1109/ICCPCT.2015.7159427
  7. Al-Nussairi M, Al-Majidi S, Mshkil A, Dakhil A, Abbod M, Al-Raweshidy H. Design of a Two-Area Automatic Generation Control Using a Single Input Fuzzy Gain Scheduling PID Controller. International Journal of Intelligent Engineering and Systems. 2022;15(6):443–455. Available from: https://inass.org/wp-content/uploads/2022/08/2022123140-2.pdf
  8. Rashid A, Saini S, Safiullah S, Farooq Z. System Dynamics and Frequency Regulation of a Multi-Area Power System Using an Optimal Controller. International Journal of Innovative Research in Engineering & Management. 2022;p. 66–72. Available from: https://doi.org/10.55524/ijirem.2022.9.3.9
  9. Gheisarnejad M, Khooban MH. Design an optimal fuzzy fractional proportional integral derivative controller with derivative filter for load frequency control in power systems. Transactions of the Institute of Measurement and Control. 2019;41(9):2563–2581. Available from: https://doi.org/10.1177/0142331218804309
  10. Chandrakala KRMV, Balamurugan S, Sankaranarayanan K. Variable structure fuzzy gain scheduling based load frequency controller for multi source multi area hydro thermal system. Electrical Power and Energy Systems. 2013;(09) 375–381. Available from: https://doi.org/10.1016/j.ijepes.2013.05.009
  11. Kumar NK, Gopi RS, Kuppusamy R, Nikolovski S, Teekaraman Y, Vairavasundaram I, et al. Fuzzy Logic-Based Load Frequency Control in an Island Hybrid Power System Model Using Artificial Bee Colony Optimization. Energies. 2022;15(6):2199. Available from: https://doi.org/10.3390/en15062199
  12. Shouran M, Anayi F, Packianather M, Habil M. Load Frequency Control Based on the Bees Algorithm for the Great Britain Power System. Designs. 2021;5(3):50. Available from: https://doi.org/10.3390/designs5030050
  13. Yadav S, Namrata K, Kumar N, Samadhiya A. Fuzzy based load frequency control of power system incorporating nonlinearity. 2022 4th International Conference on Energy, Power and Environment (ICEPE). 2022;p. 1–6. Available from: https://doi.org/10.1109/ICEPE55035.2022.9798219


© 2023 Nath & Sambariya. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)


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