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Automatic load frequency control of a multi-area dynamic interconnected power system using a hybrid PSO-GSA-tuned PID controller


Citation

Veerasamy, Veerapandiyan and Abdul Wahab, Noor Izzri and Ramachandran, Rajeswari and Vinayagam, Arangarajan and Othman, Mohammad Lutfi and Hizam, Hashim and Satheeshkumar, Jeevitha (2019) Automatic load frequency control of a multi-area dynamic interconnected power system using a hybrid PSO-GSA-tuned PID controller. Sustainability, 11 (24). art. no. 6908. pp. 1-20. ISSN 2071-1050

Abstract

This paper proposes a new population-based hybrid particle swarm optimized-gravitational search algorithm (PSO-GSA) for tuning the parameters of the proportional-integral-derivative (PID) controller of a two-area interconnected dynamic power system with the presence of nonlinearities such as generator rate constraints (GRC) and governor dead-band (GDB). The tuning of controller parameters such as Kp, Ki, and Kd are obtained by minimizing the objective function formulated using the steady-state performance indices like Integral absolute error (IAE) of tie-line power and frequency deviation of interconnected system. To test the robustness of the propounded controller, the system is studied with system uncertainties, such as change in load demand, synchronizing power coefficient and inertia constant. The two-area interconnected power system (TAIPS) is modeled and simulated using Matlab/Simulink. The results exhibit that the steady-state and transient performance indices such as IAE, settling time, and control effort are impressively enhanced by an amount of 87.65%, 15.39%, and 91.17% in area-1 and 86.46%, 41.35%, and 91.04% in area-2, respectively, by the proposed method compared to other techniques presented. The minimum control effort of PSO-GSA-tuned PID controller depicts the robust performance of the controller compared to other non-meta-heuristic and meta-heuristic methods presented. The proffered method is also validated using the hardware-in-the-loop (HIL) real-time digital simulation to study the effectiveness of the controller.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.3390/su11246908
Publisher: MDPI
Keywords: Automatic load frequency control (ALFC); Proportional-integral-derivative (PID) controller; Two-area interconnected power system (TAIPS); Particle swarm optimized-gravitational search algorithm (PSO-GSA)
Depositing User: Nabilah Mustapa
Date Deposited: 04 May 2020 15:58
Last Modified: 04 May 2020 15:58
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/su11246908
URI: http://psasir.upm.edu.my/id/eprint/38212
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