Optimal Control of a Single-Stage Modular PV-Grid-Driven System Using a Gradient Optimization Algorithm
Saleh Masoud Abdallah Altbawi,
Ahmad Safawi Bin Mokhtar,
Saifulnizam Bin Abdul Khalid,
Nusrat Husain,
Ashraf Yahya,
Syed Aqeel Haider,
Rayan Hamza Alsisi,
Lubna Moin
Affiliations
Saleh Masoud Abdallah Altbawi
Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia
Ahmad Safawi Bin Mokhtar
Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia
Saifulnizam Bin Abdul Khalid
Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia
Nusrat Husain
Department of Electronics & Power Engineering, Pakistan Navy Engineering College, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan
Ashraf Yahya
Department of Electronics & Power Engineering, Pakistan Navy Engineering College, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan
Syed Aqeel Haider
Department of Computer & Information Systems Engineering, Faculty of Electrical & Computer Engineering, NED University of Engineering and Technology, Karachi 75270, Pakistan
Rayan Hamza Alsisi
Department of Electrical Engineering, Faculty of Engineering, Islamic University of Madinah, Madinah 41411, Saudi Arabia
Lubna Moin
Department of Electronics & Power Engineering, Pakistan Navy Engineering College, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan
There are many studies that focus on extracting harmonics from both DC and AC sides of grid-interfaced photovoltaic (PV) systems. Based on these studies, the paper introduces an efficient method depending on hybrid DC voltage, and an active and reactive power (DC-V PQ) control scheme in a single-stage three-phase grid-interfaced PV system. The proposed scheme is designed to regulate DC voltage to minimize power loss and energy share between the network reconfiguration and the utility grid. Moreover, the technique is more effective at dealing with uncertainty and has higher reliability under various operating scenarios. These operations are the insertion of linear load 1, nonlinear load, and linear load 2. Moreover, a novel objective function (OF) is developed to improve the dynamic response of the system. OF is coupled with a particle swarm optimization (PSO) algorithm and a gradient optimization (GBO) algorithm. The analysis and the comparative study prove the superiority of GBO with counterfeits algorithm.
