High performing extraction procedure for the one-diode model of a photovoltaic panel from experimental I–V curves by using reduced forms

Laudani, Antonino; Fulginei, Francesco Riganti; Salvini, Alessandro

doi:10.1016/j.solener.2014.02.014

Cited by 218 publications

(151 citation statements)

References 40 publications

Supporting

Mentioning

126

Contrasting

Unclassified

Order By: Relevance

“…The similarity between the model results and the performance of the real system proves the superiority of the proposed method. Recently, a deterministic approach was used to solve the problem of parameter identification for solar cells, such as [5,6,20], etc. Firstly, the comparison between the proposed method, the method in [20] (see 2.D) and the method in [5] is made in terms of computational cost.…”

Section: Parameter Identifications and Resultsmentioning

confidence: 99%

“…The nstep of the proposed method are 603 and 932 for the single and double diode models, respectively. The nstep of the proposed in [5] is 23 while the nGuess and nstep of the method in [20] are 147 and 178. Note that the value of nGuess and nstep are different from [20] because we and [20] chose different initial values for the independent parameters Rs and a.…”

Section: Parameter Identifications and Resultsmentioning

confidence: 99%

“…The nstep of the proposed in [5] is 23 while the nGuess and nstep of the method in [20] are 147 and 178. Note that the value of nGuess and nstep are different from [20] because we and [20] chose different initial values for the independent parameters Rs and a. In the subsequence, we made a comparison between the proposed method, the method in [20] (see 2.D) and the method in [5] by conducting an experiment under nonstandard test conditions.…”

Section: Parameter Identifications and Resultsmentioning

confidence: 99%

“…Note that the value of nGuess and nstep are different from [20] because we and [20] chose different initial values for the independent parameters Rs and a. In the subsequence, we made a comparison between the proposed method, the method in [20] (see 2.D) and the method in [5] by conducting an experiment under nonstandard test conditions. The Rmse index defined by Equation (19) is used to measure accuracy of different methods.…”

Section: Parameter Identifications and Resultsmentioning

confidence: 99%

See 3 more Smart Citations

Application of Artificial Bee Colony in Model Parameter Identification of Solar Cells

2015

View full text Add to dashboard Cite

Abstract:The identification of values of solar cell parameters is of great interest for evaluating solar cell performances. The algorithm of an artificial bee colony was used to extract model parameters of solar cells from current-voltage characteristics. Firstly, the best-so-for mechanism was introduced to the original artificial bee colony. Then, a method was proposed to identify parameters for a single diode model and double diode model using this improved artificial bee colony. Experimental results clearly demonstrate the effectiveness of the proposed method and its superior performance compared to other competing methods.

show abstract

Section: Parameter Identifications and Resultsmentioning

confidence: 99%

Section: Parameter Identifications and Resultsmentioning

confidence: 99%

Section: Parameter Identifications and Resultsmentioning

confidence: 99%

Section: Parameter Identifications and Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Application of Artificial Bee Colony in Model Parameter Identification of Solar Cells

2015

View full text Add to dashboard Cite

show abstract

“…Analytical methods [5][6][7][8][9][10] required less computational time for parameter extraction due to their simple structure and perform efficiently at standard testing conditions (STC) for some models but these methods are found to be unsuitable for solar model for wide range of changing weather conditions. Because, the mathematical model of PV panel represented is implicit in nature.…”

Section: Introductionmentioning

confidence: 99%

Extraction of Solar Cell Modelling Parameters Using Differential Evolution Algorithm

Tamrakar¹,

Gupta²

2015

International Journal of Innovative Research in Electrical, Ele

View full text Add to dashboard Cite

Abstract:Energy from the sun is the best option for electricity generation as it is abundantly available everywhere and sustainable source. Advance of Photovoltaic (PV) technology in recent years has made solar energy one of the practical alternative energy sources available in the energy market. In order to make the PV energy more affordable and cost effective, major focus of the research community and industry is improvement on power efficiency of PV systems. Parameter extraction of solar cell plays a crucial role in the simulation and design calculation of PV system. In this paper, in order to fast and accurately extract the solar cell parameters, differential evolution (DE) is proposed. The single diode and double diode model of solar cell is used as the basis for the extraction problem. The analysis carried out using current-voltage (I-V) characteristics showed that the proposed DE outperforms other methods, namely the genetic algorithm (GA) and partical swarm optimization (PSO).

show abstract

A novel black widow optimization approach to improve the precision in parameter estimation problem of solar photovoltaic electrical model

Chauhan

Prakash

2022

Env Prog and Sustain Energy

View full text Add to dashboard Cite

Mathematical modeling of solar photovoltaic (PV) cell/module or array is to assess its unknown modeling parameters with the experimental current-voltage (I-V) characteristic or from the manufacturer's datasheet, where exploitation of implicit and precise solution is a stern concern among researchers for the designing of an optimized solar PV system. Hence, in this article, a robust pheromone value black widow optimization (pv-BWO) algorithm is proposed to estimate precise modeling parameters of equivalent solar PV single-diode model (SDM), double-diode model (DDM), and three-diode model (TDM). The proposed algorithm is well investigated in coordination with three case studies that hold polycrystalline and monocrystalline PV modules. The suggested technique is validated through the analysis of I-V and power-voltage (P-V) performance characteristics that are meticulously analyzed under various environmental constraints. The first two case studies are widely investigated in the literature also, whereas, to affirm the suitability of pv-BWO under real implementation the third case study is carried out in an experimental environment. Furthermore, the pv-BWO method for the aforesaid case studies are validated and compared with the experimental data along with various well-established parameter estimation techniques in literature, where the proposed method promises a more reliable, stable, and precise solution for the parameter estimation problem.

show abstract

High performing extraction procedure for the one-diode model of a photovoltaic panel from experimental I–V curves by using reduced forms

Cited by 218 publications

References 40 publications

Application of Artificial Bee Colony in Model Parameter Identification of Solar Cells

Application of Artificial Bee Colony in Model Parameter Identification of Solar Cells

Extraction of Solar Cell Modelling Parameters Using Differential Evolution Algorithm

A novel black widow optimization approach to improve the precision in parameter estimation problem of solar photovoltaic electrical model

Contact Info

Product

Resources

About