Next Article in Journal
An Integrated Open Approach to Capturing Systematic Knowledge for Manufacturing Process Innovation Based on Collective Intelligence
Next Article in Special Issue
An Evolutionary-Based MPPT Algorithm for Photovoltaic Systems under Dynamic Partial Shading
Previous Article in Journal
MAP-MRF-Based Super-Resolution Reconstruction Approach for Coded Aperture Compressive Temporal Imaging
Previous Article in Special Issue
Comparison of Training Approaches for Photovoltaic Forecasts by Means of Machine Learning
Article Menu
Issue 3 (March) cover image

Export Article

Open AccessFeature PaperArticle
Appl. Sci. 2018, 8(3), 339; https://doi.org/10.3390/app8030339

Metaheuristic Algorithm for Photovoltaic Parameters: Comparative Study and Prediction with a Firefly Algorithm

1
Mathematics Informatic & Applications Team, National School of Applied Sciences, Abdelmalek Essaadi University, Tanger 1818, Morocco
2
Department of Energy, Politecnico di Milano, 20156 Milano, Italy
3
Electrical Engineering Department, University Politehnica of Bucharest, Bucharest 060042, Romania
*
Author to whom correspondence should be addressed.
Received: 31 December 2017 / Revised: 15 February 2018 / Accepted: 20 February 2018 / Published: 27 February 2018
(This article belongs to the Special Issue Computational Intelligence in Photovoltaic Systems)
Full-Text   |   PDF [6175 KB, uploaded 6 March 2018]   |  

Abstract

In this paper, a Firefly algorithm is proposed for identification and comparative study of five, seven and eight parameters of a single and double diode solar cell and photovoltaic module under different solar irradiation and temperature. Further, a metaheuristic algorithm is proposed in order to predict the electrical parameters of three different solar cell technologies. The first is a commercial RTC mono-crystalline silicon solar cell with single and double diodes at 33 °C and 1000 W/m2. The second, is a flexible hydrogenated amorphous silicon a-Si:H solar cell single diode. The third is a commercial photovoltaic module (Photowatt-PWP 201) in which 36 polycrystalline silicon cells are connected in series, single diode, at 25 °C and 1000 W/m2 from experimental current-voltage. The proposed constrained objective function is adapted to minimize the absolute errors between experimental and predicted values of voltage and current in two zones. Finally, for performance validation, the parameters obtained through the Firefly algorithm are compared with recent research papers reporting metaheuristic optimization algorithms and analytical methods. The presented results confirm the validity and reliability of the Firefly algorithm in extracting the optimal parameters of the photovoltaic solar cell. View Full-Text
Keywords: solar cell; metaheuristic algorithm; electrical parameters; analytical methods; firefly algorithm; statistical errors solar cell; metaheuristic algorithm; electrical parameters; analytical methods; firefly algorithm; statistical errors
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Louzazni, M.; Khouya, A.; Amechnoue, K.; Gandelli, A.; Mussetta, M.; Crăciunescu, A. Metaheuristic Algorithm for Photovoltaic Parameters: Comparative Study and Prediction with a Firefly Algorithm. Appl. Sci. 2018, 8, 339.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top