Identification of unknown parameters of a single diode photovoltaic model using particle swarm optimization with binary constraints

被引:90
|
作者
Bana, Sangram [1 ]
Saini, R. P. [1 ]
机构
[1] Indian Inst Technol, Alternate Hydro Energy Ctr, Roorkee 247667, Uttar Pradesh, India
关键词
Photovoltaic (PV) model; Maximum power point (MPP); Binary constraints; Particle swarm optimization (PSO); ALGORITHM; MODULES; PERFORMANCE; EXTRACTION; SYSTEM;
D O I
10.1016/j.renene.2016.10.010
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Photo-voltaic (PV) is a static medium to convert solar energy directly into electricity. In order to predict the performance of a PV system before being installed, a reliable and accurate model design of PV systems is essential. To validate the design of a PV system like maximum power point (MPP) and micro grid system through simulation, an accurate solar PV model is required. However, information provided by manufacturers in data sheets is not sufficient for simulating the characteristic of a PV module under normal as well as under diverse environmental conditions. In this paper, a particle swarm optimization (PSO) technique with binary constraints has been presented to identify the unknown parameters of a single diode model of solar PV module. Multi-crystalline and mono-crystalline technologies based PV modules are considered under the present study. Based on the results obtained, it has been found that PSO algorithm yields a high value of accuracy irrespective of temperature variations. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1299 / 1310
页数:12
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