Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) Indonesian Journal of Electrical Engineering and Computer Science
Kayode Timothy Akindeji
Durban University of Technology
Control & Systems Engineering Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Solution of load frequency control through jaya technique with unified power flow controller and redox flow battery Avinash Panwar; Vinesh Agarwal; Gulshan Sharma; Kayode Timothy Akindeji; Narayanan Krishnan
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1247-1257

Abstract

This paper proposes the initial strategy of designing two degree of freedom proportional integral derivative (2DOF-PID) made load frequency control (LFC) action optimized using Jaya optimization algorithm for a hydro-hydro system. At first, the PID optimized through Jaya is used for hydro-dominated system, and the comparative analysis of all possible error definitions are carried out to show the benefits of selecting integral time absolute error (ITAE) for LFC. Then, 2DOF-PID is designed for the hydro governing system, and its performance is compared with other designs to show the efficacy of the present LFC about computed error values gain of the various models via graphical LFC. The results obtained through simulations are promising but oscillatory with greater settling time. Hence, the proposed controller is retuned by considering the unified power flow control (UPFC) in arrangement with the tie-line and redox flow battery (RFB) units in area-2, and it is further seen that the outcomes of the application show the prevalence of the proposed work.
Grid-tied photovoltaic system MPPT algorithms performance: comparative analysis Louis Nicase Nguefack; Kayode Timothy Akindeji; Abayomi A. Adebiyi
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i1.pp317-334

Abstract

Between 2015 and 2024, global solar photovoltaic (PV) capacity rose significantly from 223.204 GW to 1624 GW, contributing to the reduction of greenhouse gas emissions associated with fossil-fuel-based power generation. Solar PV is recognized for its environmental benefits and is increasingly seen as a viable alternative for a long-term sustainable energy supply. However, the power output of PV systems is highly dependent on atmospheric conditions, particularly solar irradiation and temperature, which can cause fluctuations and reduce overall efficiency. To address this, maximum power point tracking (MPPT) techniques are employed to optimize energy extraction under varying environmental conditions. This study presents a comparative analysis of four MPPT algorithms, perturb-and-observe (P&O), incremental conductance (InC), fuzzy logic control (FLC), and artificial neural network (ANN) for grid-tied PV systems using MATLAB/Simulink. Each algorithm was evaluated under dynamic conditions to determine its tracking efficiency and responsiveness. The results show that while conventional methods like P&O and InC are simpler, they are less effective under rapidly changing conditions. FLC demonstrates faster convergence but requires greater computational resources. The intelligent controllers demonstrated superior performance: FLC achieved the highest power output of 1.019×10⁶ W with a corresponding voltage of 1.422×10⁴ V, while the ANN algorithm followed closely with 9.650×10⁵ W and 1.200×10⁴ V, respectively. The comparative insights gained from this analysis offer practical guidance for selecting MPPT controllers in real-world solar energy applications.
Co-Authors Abayomi A. Adebiyi Avinash Panwar Gulshan Sharma Louis Nicase Nguefack Narayanan Krishnan Vinesh Agarwal