Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applications

This study investigates the application of a PID controller with a fractional derivative component (PIDDμ), optimized using the stochastic fractional search (SFS) technique, for load frequency control (LFC) in power systems. Additionally, solar PV and battery energy storage systems (BESS) and flywhe...

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Main Authors: S.B. Masikana, Gulshan Sharma, Sachin Sharma, Pitshou N. Bokoro, Emre Çelik
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:e-Prime: Advances in Electrical Engineering, Electronics and Energy
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Online Access:http://www.sciencedirect.com/science/article/pii/S277267112400367X
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author S.B. Masikana
Gulshan Sharma
Sachin Sharma
Pitshou N. Bokoro
Emre Çelik
author_facet S.B. Masikana
Gulshan Sharma
Sachin Sharma
Pitshou N. Bokoro
Emre Çelik
author_sort S.B. Masikana
collection DOAJ
description This study investigates the application of a PID controller with a fractional derivative component (PIDDμ), optimized using the stochastic fractional search (SFS) technique, for load frequency control (LFC) in power systems. Additionally, solar PV and battery energy storage systems (BESS) and flywheel energy storage systems (FESS) are integrated as backup sources to enhance the LFC performance. To assess the effectiveness of the proposed approach, three error metrics—Integral Time Absolute Error (ITAE), Integral Time Multiplied Square Error (ITSE), and Integral of Absolute Error (IAE)—are evaluated. The results are compared with recent optimization-based LFC techniques across various scenarios. It is found that the SFS-PIDDμ achieves IAE=0.006786, ITSE=1.07e-05, and ITAE=0.01853, which are significantly lower than the error values produced by other LFC techniques. Furthermore, integrating solar PV, along with BESS and FESS, further reduces these error values. The graphical LFC responses of the SFS-PIDDμ outperform other optimization-based LFC techniques. The robustness of the approach is also validated against random load changes of varying magnitudes and for broader parametric variations.
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institution OA Journals
issn 2772-6711
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publishDate 2024-12-01
publisher Elsevier
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series e-Prime: Advances in Electrical Engineering, Electronics and Energy
spelling doaj-art-e4f8b0a925af49d6a5f98f6d7094d4582025-08-20T02:35:47ZengElseviere-Prime: Advances in Electrical Engineering, Electronics and Energy2772-67112024-12-011010078710.1016/j.prime.2024.100787Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applicationsS.B. Masikana0Gulshan Sharma1Sachin Sharma2Pitshou N. Bokoro3Emre Çelik4Department of Electrical Engineering, Mangosuthu University of Technology, Durban & Department of Electrical Engineering Technology, University of Johannesburg, Johannesburg 2006, South AfricaDepartment of Electrical Engineering Technology, University of Johannesburg, Johannesburg, 2006, South Africa; Corresponding authors.Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnatka, India; Corresponding authors.Department of Electrical Engineering Technology, University of Johannesburg, Johannesburg, 2006, South AfricaDepartment of Electrical and Electronics Engineering, Engineering Faculty, Düzce University, TurkeyThis study investigates the application of a PID controller with a fractional derivative component (PIDDμ), optimized using the stochastic fractional search (SFS) technique, for load frequency control (LFC) in power systems. Additionally, solar PV and battery energy storage systems (BESS) and flywheel energy storage systems (FESS) are integrated as backup sources to enhance the LFC performance. To assess the effectiveness of the proposed approach, three error metrics—Integral Time Absolute Error (ITAE), Integral Time Multiplied Square Error (ITSE), and Integral of Absolute Error (IAE)—are evaluated. The results are compared with recent optimization-based LFC techniques across various scenarios. It is found that the SFS-PIDDμ achieves IAE=0.006786, ITSE=1.07e-05, and ITAE=0.01853, which are significantly lower than the error values produced by other LFC techniques. Furthermore, integrating solar PV, along with BESS and FESS, further reduces these error values. The graphical LFC responses of the SFS-PIDDμ outperform other optimization-based LFC techniques. The robustness of the approach is also validated against random load changes of varying magnitudes and for broader parametric variations.http://www.sciencedirect.com/science/article/pii/S277267112400367XLFCPID controllerStochastic fractional search algorithmSolar PVBESSFESS
spellingShingle S.B. Masikana
Gulshan Sharma
Sachin Sharma
Pitshou N. Bokoro
Emre Çelik
Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applications
e-Prime: Advances in Electrical Engineering, Electronics and Energy
LFC
PID controller
Stochastic fractional search algorithm
Solar PV
BESS
FESS
title Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applications
title_full Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applications
title_fullStr Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applications
title_full_unstemmed Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applications
title_short Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applications
title_sort solar pv focused lfc studies utilizing an sfs optimized pid with fractional derivative piddμ and incorporating bess and fess applications
topic LFC
PID controller
Stochastic fractional search algorithm
Solar PV
BESS
FESS
url http://www.sciencedirect.com/science/article/pii/S277267112400367X
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