Next Article in Journal
Perceptions and Role of Tourist Destination Residents Compared to Other Event Stakeholders in a Small-Scale Sports Event. The Case of the FIS World Junior Alpine Ski Championships 2019 in Val di Fassa
Previous Article in Journal
Analysis of Environmental Productivity on Fossil Fuel Power Plants in the U.S.
Open AccessArticle

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

1
Faculty of Engineering, Department of Electrical and Electronics Engineering, Advanced Lightning and Power Energy System(ALPER), Universiti Putra Malaysia (UPM), Selangor 43400, Malaysia
2
Department of Electrical Engineering, Government College of Technology, Coimbatore 641013, India
3
Department of Electrical Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore 641062, India
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(24), 6908; https://doi.org/10.3390/su11246908
Received: 17 September 2019 / Revised: 1 November 2019 / Accepted: 2 November 2019 / Published: 4 December 2019
(This article belongs to the Section Energy Sustainability)
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.
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) automatic load frequency control (ALFC); proportional-integral-derivative (PID) controller; two-area interconnected power system (TAIPS); particle swarm optimized-gravitational search algorithm (PSO-GSA)
MDPI and ACS Style

VeerapandiyanVeerasamy; Abdul Wahab, N.I.; Ramachandran, R.; Vinayagam, A.; Othman, M.L.; HashimHizam; Kumar, J.S. Automatic Load Frequency Control of a Multi-Area Dynamic Interconnected Power System Using a Hybrid PSO-GSA-Tuned PID Controller. Sustainability 2019, 11, 6908.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop