Parameter extraction of two diode solar PV model using Fireworks algorithm

被引:160
作者
Babu, T. Sudhakar [1 ]
Ram, J. Prasanth [1 ]
Sangeetha, K. [1 ]
Laudani, Antonino [2 ]
Rajasekar, N. [1 ]
机构
[1] VIT Univ, Solar Energy Res Cell, Sch Elect Engn SELECT, Vellore 632014, Tamil Nadu, India
[2] Univ Roma Tre, Elect Engn, Rome, Italy
关键词
Fireworks Algorithm (FWA); Parameter estimation; Two diode model; Genetic Algorithm (GA); IDENTIFICATION; OPTIMIZATION; SEARCH; SYSTEM;
D O I
10.1016/j.solener.2016.10.044
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The double diode model for photovoltaic (PV) modules is currently less adopted than one-diode model because of the difficulty in the extraction of its seven unknown parameters by, I-PV, I-01, I-02, R-s, R-p, a(1) and a(2), which is a serious inverse problem. This paper proposes application of the Fireworks Algorithm (FWA) for the accurate identification of these unknown parameters in such a way to solve effectively this modeling problem. In particular, firstly, the FWA has been comprehensively tested with two different technologies of Mono-Crystalline (SM55 & SP70) and Multi-Crystalline (Kyocera200GT) PV modules. In addition, further statistical and error analysis for three different panels are exclusively carried out to validate the suitability of proposed methodology. The results of proposed algorithm are benchmarked with popular Genetic Algorithm and Particle Swarm Optimization (PSO) methods. Fitness convergence curves or FWA method for SM55, SP70 and Kyocera200GT produce very less objective function as 2.2498E-07, 2.85765E-08 and 4.0075E-08 respectively. This illustrates the wise and accurate validation of FWA method. Calculated curve-fit via FWA in agreement to datasheet curve strongly suggest the FWA can constitute the core of suitable optimization code for two diode PV parameter extraction. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:265 / 276
页数:12
相关论文
共 26 条
[1]   Flower Pollination Algorithm based solar PV parameter estimation [J].
Alam, D. F. ;
Yousri, D. A. ;
Eteiba, M. B. .
ENERGY CONVERSION AND MANAGEMENT, 2015, 101 :410-422
[2]   Optimal extraction of solar cell parameters using pattern search [J].
AlHajri, M. F. ;
El-Naggar, K. M. ;
AlRashidi, M. R. ;
Al-Othman, A. K. .
RENEWABLE ENERGY, 2012, 44 :238-245
[3]  
[Anonymous], 2015, SOLAR PHOTOVOLTAICS
[4]   Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach [J].
Askarzadeh, Alireza ;
Rezazadeh, Alireza .
SOLAR ENERGY, 2013, 90 :123-133
[5]   Artificial bee swarm optimization algorithm for parameters identification of solar cell models [J].
Askarzadeh, Alireza ;
Rezazadeh, Alireza .
APPLIED ENERGY, 2013, 102 :943-949
[6]   Parameter identification for solar cell models using harmony search-based algorithms [J].
Askarzadeh, Alireza ;
Rezazadeh, Alireza .
SOLAR ENERGY, 2012, 86 (11) :3241-3249
[7]   A near accurate solar PV emulator using dSPACE controller for real-time control [J].
Azharuddin, S. Mohammed ;
Vysakh, M. ;
Thakur, Harshal Vilas ;
Nishant, B. ;
Babu, T. Sudhakar ;
Muralidhar, K. ;
Paul, Don ;
Jacob, Basil ;
Balasubramanian, Karthik ;
Rajasekar, N. .
INTERNATIONAL CONFERENCE ON APPLIED ENERGY, ICAE2014, 2014, 61 :2640-2648
[8]   Modified Particle Swarm Optimization technique based Maximum Power Point Tracking for uniform and under partial shading condition [J].
Babu, T. Sudhakar ;
Rajasekar, N. ;
Sangeetha, K. .
APPLIED SOFT COMPUTING, 2015, 34 :613-624
[9]   Improvement and validation of a model for photovoltaic array performance [J].
De Soto, W ;
Klein, SA ;
Beckman, WA .
SOLAR ENERGY, 2006, 80 (01) :78-88
[10]   Simulated Annealing algorithm for photovoltaic parameters identification [J].
El-Naggar, K. M. ;
AlRashidi, M. R. ;
AlHajri, M. F. ;
Al-Othrnan, A. K. .
SOLAR ENERGY, 2012, 86 (01) :266-274