Identification of electrical parameters in a power network using genetic algorithms and transient measurements

In this chapter, we propose to perform a numerical technique based on genetic algorithms (GAs) to identify the electrical parameters (Is, Iph, Rs, Rsh, and n) of photovoltaic (PV) solar cells and modules. The one diode type approach is used to model the I–V characteristic of the solar cell. To extract electrical parameters, the approach is formulated as optimization problem. The GAs approach was used as a numerical technique in order to overcome problems involved in the local minima in the case optimization criteria. Compared to other methods, we find that the GAs is a very efficient technique to estimate the electrical parameters of photovoltaic solar cells and modules. Compared with other parameter extraction techniques, based on statistical study, results indicate the consistency and uniformity of method in terms of the quality of final solutions. In parallel, the simulated data with the extracted parameters of method base with GAs are in very good agreement with the experimental data in all cases.

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Parameter Optimization of Photovoltaic Solar Cell and Panel Using Genetic Algorithms Strategy

Nature-Inspired Computing ◽

10.4018/978-1-5225-0788-8.ch052 ◽

2016 ◽

pp. 1371-1390

Author(s):

Benmessaoud Mohammed Tarik ◽

Fatima Zohra Zerhouni ◽

Amine Boudghene Stambouli ◽

Mustapha Tioursi ◽

Aouad M'harer

Keyword(s):

Genetic Algorithms ◽

Solar Cells ◽

Solar Cell ◽

Numerical Technique ◽

Simulated Data ◽

Parameter Extraction ◽

Electrical Parameters ◽

Study Results ◽

The One ◽

Photovoltaic Solar Cells

In this chapter, we propose to perform a numerical technique based on genetic algorithms (GAs) to identify the electrical parameters (Is, Iph, Rs, Rsh, and n) of photovoltaic (PV) solar cells and modules. The one diode type approach is used to model the I–V characteristic of the solar cell. To extract electrical parameters, the approach is formulated as optimization problem. The GAs approach was used as a numerical technique in order to overcome problems involved in the local minima in the case optimization criteria. Compared to other methods, we find that the GAs is a very efficient technique to estimate the electrical parameters of photovoltaic solar cells and modules. Compared with other parameter extraction techniques, based on statistical study, results indicate the consistency and uniformity of method in terms of the quality of final solutions. In parallel, the simulated data with the extracted parameters of method base with GAs are in very good agreement with the experimental data in all cases.

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Application of genetic algorithms for the extraction of electrical parameters of multicrystalline silicon

Measurement Science and Technology ◽

10.1088/0957-0233/18/5/037 ◽

2007 ◽

Vol 18 (5) ◽

pp. 1472-1476 ◽

Cited By ~ 9

Author(s):

A Sellami ◽

M Zagrouba ◽

M Bouaïcha ◽

B Bessaïs

Keyword(s):

Genetic Algorithms ◽

Multicrystalline Silicon ◽

Electrical Parameters

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Improvement and Application of Genetic Algorithms in Reactive Power Optimization of Power Network

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.354-355.1058 ◽

2011 ◽

Vol 354-355 ◽

pp. 1058-1063

Author(s):

Lin Lei ◽

Yi Nan Ge ◽

Qin Yuan

Keyword(s):

Genetic Algorithms ◽

High Voltage ◽

Reactive Power ◽

Power Optimization ◽

Convergence Speed ◽

Power Network ◽

Reactive Power Optimization ◽

Simple Genetic Algorithms ◽

High Voltage System ◽

Bus System

Reactive power optimization that is optimized by Simple Genetic Algorithms has many limitations. According to the problem of reactive power optimization of high voltage system, the Simple Genetic Algorithms is improved. The improved algorithm is applied in reactive power optimization of IEEE-6 bus system, the results indicate that the improvement is effective and it can accelerate the convergence speed and enhance the ability of optimization.

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