Automatic Load Frequency Control of a Multi-Area Dynamic Interconnected Power System Using a Hybrid PSO-GSA-Tuned PID Controller

Veerapandiyan Veerasamy, Noor Izzri Abdul Wahab, Rajeswari Ramachandran, Arangarajan Vinayagam, Mohammad Lutfi Othman, Hashim Hizam and Jeevitha Satheeshkumar
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Veerapandiyan Veerasamy: Faculty of Engineering, Department of Electrical and Electronics Engineering, Advanced Lightning and Power Energy System(ALPER), Universiti Putra Malaysia (UPM), Selangor 43400, Malaysia
Noor Izzri Abdul Wahab: Faculty of Engineering, Department of Electrical and Electronics Engineering, Advanced Lightning and Power Energy System(ALPER), Universiti Putra Malaysia (UPM), Selangor 43400, Malaysia
Rajeswari Ramachandran: Department of Electrical Engineering, Government College of Technology, Coimbatore 641013, India
Arangarajan Vinayagam: Department of Electrical Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore 641062, India
Mohammad Lutfi Othman: Faculty of Engineering, Department of Electrical and Electronics Engineering, Advanced Lightning and Power Energy System(ALPER), Universiti Putra Malaysia (UPM), Selangor 43400, Malaysia
Hashim Hizam: Faculty of Engineering, Department of Electrical and Electronics Engineering, Advanced Lightning and Power Energy System(ALPER), Universiti Putra Malaysia (UPM), Selangor 43400, Malaysia
Jeevitha Satheeshkumar: Department of Electrical Engineering, Government College of Technology, Coimbatore 641013, India

Sustainability, 2019, vol. 11, issue 24, 1-20

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 K p , K i , and K d 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.

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) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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