Work

Enhancing Sustainability in Renewable Energy: Comparative Analysis of Optimization Algorithms for Accurate PV Parameter Estimation

Year: 2025

Type: article

Abstract: This study presents a comparative analysis of various optimization algorithms—Differential Evolution (DE), Particle Swarm Optimization (PSO), Arithmetic Optimization Algorithm (AOA), and Hippopotamus Optimization Algorithm (HOA)—for parameter identification in photovoltaic (PV) models. By utilizing RTC France solar cell data, we demonstrate that accurate parameter estimation is crucial for enhancing the efficiency of PV systems, ultimately supporting sustainable energy solutions. Our results indicate that DE achieves the lowest root mean square error (RMSE) of 0.0001 for the double-diode model (DDM), outperforming other methods in terms of accuracy and convergence speed. Both the HOA and PSO also show competitive RMSE values, underscoring their effectiveness in optimizing parameters for PV models. This research not only contributes to improved PV model precision but also aids in the broader effort to advance renewable energy technologies, thereby fostering a more sustainable future.

Source: Sustainability

DOI: 10.3390/su17062718

Authors: Hanaa Fathi, Deema Mohammed Alsekait, Arar Al Tawil, Israa Wahbi Kamal, Mohammad Sameer Aloun, Ibrahim I. M. Manhrawy

Institutions: Amman Arab University, Princess Nourah bint Abdulrahman University, Applied Science Private University

Language: English

Topic: Photovoltaic System Optimization Techniques

Subfield: Renewable Energy, Sustainability and the Environment

Field: Energy

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action

Open Access status: gold

Estimated APC paid: $2,896