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

Vivek Nath; D K Sambariya

doi:10.17485/IJST/v16i39.1769

Article

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

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Indian Journal of Science and Technology

DOI: 10.17485/IJST/v16i39.1769

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

Vivek Nath^1*, D K Sambariya²

¹Scholar, Rajasthan Technical University, Kota, India
²Associate Professor, Rajasthan Technical University,, Kota, India

*Corresponding Author
Email: [email protected]

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

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

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)

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Copyright

© 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)