<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The major shortcoming in the extraction of electrical energy occurs due to partial shading over a limited area of vast spread solar panels underpinning reduction of efficiency. A number of panels are interconnected in series and parallel to form a photovoltaic (PV) array for large power plants and a shadow over a single cell deteriorates overall performance. As a consequence, several peaks are added to the P-V curve causing hotspots in PV panels, degradation of the PV system, and collapse of tracking algorithms. In order to minimize such issues in PV panels, an effective optimization technique is developed by reconfiguring the panels which are capable of reaching the full global power point in a PV system under partial shading conditions. The study proposes particle swarm optimization (PSO) using PV characteristics of Quaid-e-Azam Solar Plant (QASP) in Punjab, Pakistan<sup>1</sup>. In PSO, electrical connections of PV modules are changed keeping their physical locations unaltered aiming to improve the performance of the PV system. After reconfiguration, the algorithm finds the best combination of PV modules by equalizing the row currents followed by the comparison of row current, voltages, and power of panels. The proposed PSO is proved to be an efficient method for reconfiguring PV modules in very less computational time by increasing the output power of shaded modules.</p>
</abstract>

The major shortcoming in the extraction of electrical energy occurs due to partial shading over a limited area of vast spread solar panels underpinning reduction of efficiency. A number of panels are interconnected in series and parallel to form a photovoltaic (PV) array for large power plants and a shadow over a single cell deteriorates overall performance. As a consequence, several peaks are added to the P-V curve causing hotspots in PV panels, degradation of the PV system, and collapse of tracking algorithms. In order to minimize such issues in PV panels, an effective optimization technique is developed by reconfiguring the panels which are capable of reaching the full global power point in a PV system under partial shading conditions. The study proposes particle swarm optimization (PSO) using PV characteristics of Quaid-e-Azam Solar Plant (QASP) in Punjab, Pakistan1. In PSO, electrical connections of PV modules are changed keeping their physical locations unaltered aiming to improve the performance of the PV system. After reconfiguration, the algorithm finds the best combination of PV modules by equalizing the row currents followed by the comparison of row current, voltages, and power of panels. The proposed PSO is proved to be an efficient method for reconfiguring PV modules in very less computational time by increasing the output power of shaded modules.

Reconfiguration and Analysis of PV Array based on Particle Swarm Optimization of Solar Plant

Electrical, Control and Communication Engineering

This work is licensed under the Creative Commons Attribution 4.0 International License.

The major shortcoming in the extraction of electrical energy occurs due to partial shading over a limited area of vast spread solar panels underpinning...

Reconfiguration and Analysis of PV Array based on Particle Swarm Optimization of Solar Plant

Online veröffentlicht: 19. Jan. 2023

Seitenbereich: 18 - 26

DOI: https://doi.org/10.2478/ecce-2022-0003

Schlüsselwörter
Computational efficiency, maximum power point trackers, particle swarm optimization, photoelectricity, photovoltaic systems, power system transients

© 2022 Muhammad Sheryar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Reconfiguration and Analysis of PV Array based on Particle Swarm Optimization of Solar Plant

Online veröffentlicht: 19. Jan. 2023

Seitenbereich: 18 - 26

DOI: https://doi.org/10.2478/ecce-2022-0003

SchlüsselwörterComputational efficiency, maximum power point trackers, particle swarm optimization, photoelectricity, photovoltaic systems, power system transients

© 2022 Muhammad Sheryar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Computational efficiency, maximum power point trackers, particle swarm optimization, photoelectricity, photovoltaic systems, power system transients