scholarly journals Parameter Optimization of Single-Diode Model of Photovoltaic Cell Using Memetic Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Yourim Yoon ◽  
Zong Woo Geem
Keyword(s):  
Solar Cell ◽  
Least Squares Method ◽  
Memetic Algorithm ◽  
Cell Model ◽  
Harmony Search ◽  
Cuckoo Search ◽  
Photovoltaic Cell ◽  
Pattern Search ◽  
Cell Parameters ◽  
Local Searches

This study proposes a memetic approach for optimally determining the parameter values of single-diode-equivalent solar cell model. The memetic algorithm, which combines metaheuristic and gradient-based techniques, has the merit of good performance in both global and local searches. First, 10 single algorithms were considered including genetic algorithm, simulated annealing, particle swarm optimization, harmony search, differential evolution, cuckoo search, least squares method, and pattern search; then their final solutions were used as initial vectors for generalized reduced gradient technique. From this memetic approach, we could further improve the accuracy of the estimated solar cell parameters when compared with single algorithm approaches.

Photovoltaic Cell Parameters Identification Using Nonlinear Mathematical Programming

2013 ◽  
Vol 827 ◽  
pp. 186-190
Author(s):  
Helal Al-Hamadi
Keyword(s):  
Solar Cell ◽  
Mathematical Programming ◽  
Cell Model ◽  
Optimal Estimation ◽  
Photovoltaic Cell ◽  
Model Parameters ◽  
Programming Technique ◽  
Cell Parameters ◽  
Nonlinear Mathematical Programming ◽  
Cell Current

This paper proposes a mathematical programming based approach for optimal estimation of photovoltaic cell model parameters. In this study, solar cell models are used to represent the current-voltage characteristics of the solar cell. The model is represented as a non-linear function that relates the cell current and voltage with some parameters to be estimated. No direct general analytical solution exists for such function. Given the input-output characteristic data of the solar cell, a mathematical programming technique is used to solve a set of transcendental equations to optimally estimate the solar cell parameters.

Hybrid Optimization Approach for Evaluating Photovoltaic Cell Parameters

2013 ◽  
Vol 373-375 ◽  
pp. 1261-1264
Author(s):  
Mei Ying Ye
Keyword(s):  
Cell Model ◽  
Computation Time ◽  
Photovoltaic Cell ◽  
Evaluation Procedure ◽  
Model Parameters ◽  
Optimization Approach ◽  
Problem Space ◽  
Local Optima ◽  
Cell Parameters ◽  
Intelligent Technique

A new hybrid intelligent technique is proposed to evaluate photovoltaic cell model parameters in this paper. The intelligent technique is based on a hybrid of genetic algorithm (GA) and LevenbergMarquardt algorithm (LMA). In the proposed hybrid intelligent technique, the GA firstly searches the entire problem space to get a set of roughly estimated solutions, i.e. near-optimal solutions. Then the LMA performs a local optima search in order to carry out further optimizations. An example has been used to demonstrate the evaluation procedure in order to test the performance of the proposed approach. The results show that the proposed technique has better performance than the GA approach in terms of the objective function value, the computation time and the reconstructedI-Vcurve shape.

Optimal extraction of solar cell parameters using pattern search

2012 ◽  
Vol 44 ◽  
pp. 238-245 ◽  
Author(s):  
M.F. AlHajri ◽  
K.M. El-Naggar ◽  
M.R. AlRashidi ◽  
A.K. Al-Othman
Keyword(s):  
Solar Cell ◽  
Pattern Search ◽  
Cell Parameters

scholarly journals Measuring the Solar Cell Parameters Using Fuzzy Set Technique

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Mohammed S. Rasheed ◽  
Mohammed Abdelhadi Sarhan
Keyword(s):  
Solar Cell ◽  
Fuzzy Set ◽  
Silicon Solar Cell ◽  
Simulation Method ◽  
Photovoltaic Cell ◽  
Comparison Method ◽  
Physical Parameters ◽  
Simple Method ◽  
Cell Parameters ◽  
Method Show

<p>This work studies the application of fuzzy set (FS) and fuzzy logic (FC) methods to determine the optimal operating point of solar cell. The physical parameters of the solar cell have been measured practically using silicon solar cell. The important parameters of the silicon cell are compared with each other using fuzzy set comparison method (FSCM) based on (I-V) characteristic curves of the voltage of photovoltaic cell and the maximum power resulting from the cell; which is a simple method for the measurement. The results of the simulation method show that, the fuzzy set comparison method (FSCM) is better measuring these parameters.</p>

scholarly journals Parameterization of Solar Cell Model Using Multiculture & Hybrid Mutation Based Evolutionary Programming

2018 ◽  
Vol 7 (3.4) ◽  
pp. 138
Author(s):  
Sridhar N ◽  
Nagaraj Ramrao ◽  
Manoj Kumar Singh
Keyword(s):  
Solar Cell ◽  
Cell Model ◽  
Optimal Parameter ◽  
Harmony Search ◽  
Absolute Error ◽  
Evolutionary Programming ◽  
Swarm Optimization ◽  
Second Stage ◽  
Mutation Strategy ◽  
Cauchy Mutation

In this paper, parameterization of the single diode model for solar cell has presented. The problem of obtaining the optimal parameter has transformed as an optimization problem where individual absolute error has minimized by hybrid mutation strategy in the Evolutionary programming. Hybridization has given between Gaussian mutation strategy and Cauchy mutation strategy to obtain the better offspring. To increase the reliability of the solution, two stages based a multiculture architecture has proposed. On the first stage, a multi-population strategy has applied to form a multiculture environment, where each population evolved independently to explore the solution           domain.This stage will prevent the solution to trap in the local minima. In the second stage, evolved population from first stage combine and members having high fitness are selected to form a new population of the same size as the individual population in the first stage. This second stage population evolved further to meet the final objective. The performance of the proposed method has evaluated over a 57mm diameter commercial solar cell. The obtained performance has compared with results available in current literature where various other approaches like, Levenberg–Marquardt with Simulated annealing, Global Grouping-based Harmony Search, Artificial Bee Swarm Optimization, Chaotic Particle Swarm Optimization, Differential Evolution, etc. have considered. The proposed solution has delivered the minimum error in comparison to other methods and very closer to the experimental data. 

scholarly journals Estimation of Photovoltaic Cell Parameters Using Measurement Data of Photovoltaic Module String Currents and Voltages

2021 ◽  
Author(s):  
Shigeomi Hara ◽  
Hiroshi Douzono ◽  
Makoto Imamura
Keyword(s):  
Simulation Analysis ◽  
Cell Model ◽  
Measurement Data ◽  
String Model ◽  
Real Data ◽  
Photovoltaic Cell ◽  
Photovoltaic Module ◽  
Cell Parameters ◽  
Operating Environments ◽  
The Difference

Photovoltac (PV) models play an important role in the simulation analysis and fault diagnosis of PV systems. The<br>single diode model (SDM) is the most frequently used model in research and applications. There are numerous proposed methods to identify the SDM parameters. However, the characteristics of PV cells alter during the lifetime in normal operating environments; these variations may be due to degradation, faults, dust, weed, and so on. Therefore, it is crucial to estimate the actual parameters of the PV cells that represent those present state. The contribution of this study is to propose a method to estimate PV cell parameters on the basis of the measurement data regarding the currents and voltages of the PV module strings. A PV string model is described on the basis of the adaptive SDM for the PV cells in the system, and the parameters of each cell model are obtained by minimizing the difference between the measured string voltages and the string voltages computed by the model. The application of the proposed method to real data measured in a PV power plant is also presented to evaluate the proposed method.

scholarly journals Parameter Identification of Photovoltaic Cell Model Using Modified Elephant Herding Optimization-Based Algorithms

2021 ◽  
Vol 11 (24) ◽  
pp. 11929
Author(s):  
Amer Malki ◽  
Abdallah A. Mohamed ◽  
Yasser I. Rashwan ◽  
Ragab A. El-Sehiemy ◽  
Mostafa A. Elhosseini
Keyword(s):  
Solar Cell ◽  
Cell Model ◽  
Optimization Algorithms ◽  
Metaheuristic Algorithms ◽  
Local Optimum ◽  
Cell Models ◽  
Unknown Parameters ◽  
Solar Module ◽  
Cell Parameters ◽  
Pv Cell

The use of metaheuristics in estimating the exact parameters of solar cell systems contributes greatly to performance improvement. The nonlinear electrical model of the solar cell has some parameters whose values are necessary to design photovoltaic (PV) systems accurately. The metaheuristic algorithms used to determine solar cell parameters have achieved remarkable success; however, most of these algorithms still produce local optimum solutions. In any case, changing to more suitable candidates through elephant herd optimization (EHO) equations is not guaranteed; in addition, instead of making parameter α adaptive throughout the evolution of the EHO, making them adaptive during the evolution of the EHO might be a preferable choice. The EHO technique is used in this work to estimate the optimum values of unknown parameters in single-, double-, and three-diode solar cell models. Models for five, seven, and ten unknown PV cell parameters are presented in these PV cell models. Applications are employed on two types of PV solar cells: the 57 mm diameter RTC Company of France commercial silicon for single- and double-diode models and multi-crystalline PV solar module CS6P-240P for the three-diode model. The total deviations between the actual and estimated result are used in this study as the objective function. The performance measures used in comparisons are the RMSE and relative error. The performance of EHO and the proposed three improved EHO algorithms are evaluated against the well-known optimization algorithms presented in the literature. The experimental results of EHO and the three improved EHO algorithms go as planned and proved to be comparable to recent metaheuristic algorithms. The three EHO-based variants outperform all competitors for the single-diode model, and in particular, the culture-based EHO (CEHO) outperforms others in the double/three-diode model. According the studied cases, the EHO variants have low levels of relative errors and therefore high accuracy compared with other optimization algorithms in the literature.

scholarly journals Estimation of Photovoltaic Cell Parameters Using Measurement Data of Photovoltaic Module String Currents and Voltages

2021 ◽  
Author(s):  
Shigeomi Hara ◽  
Hiroshi Douzono ◽  
Makoto Imamura
Keyword(s):  
Simulation Analysis ◽  
Cell Model ◽  
Measurement Data ◽  
String Model ◽  
Real Data ◽  
Photovoltaic Cell ◽  
Photovoltaic Module ◽  
Cell Parameters ◽  
Operating Environments ◽  
The Difference

Photovoltac (PV) models play an important role in the simulation analysis and fault diagnosis of PV systems. The<br>single diode model (SDM) is the most frequently used model in research and applications. There are numerous proposed methods to identify the SDM parameters. However, the characteristics of PV cells alter during the lifetime in normal operating environments; these variations may be due to degradation, faults, dust, weed, and so on. Therefore, it is crucial to estimate the actual parameters of the PV cells that represent those present state. The contribution of this study is to propose a method to estimate PV cell parameters on the basis of the measurement data regarding the currents and voltages of the PV module strings. A PV string model is described on the basis of the adaptive SDM for the PV cells in the system, and the parameters of each cell model are obtained by minimizing the difference between the measured string voltages and the string voltages computed by the model. The application of the proposed method to real data measured in a PV power plant is also presented to evaluate the proposed method.

scholarly journals Simple vs complex models for solar cells

2019 ◽  
Vol 85 ◽  
pp. 04004
Author(s):  
Andreea Săbăduş ◽  
Marius Paulescu
Keyword(s):  
Solar Cell ◽  
Cell Model ◽  
Specific Model ◽  
Photovoltaic Module ◽  
Model Parameters ◽  
Cell Parameters ◽  
Large Dispersion ◽  
Current Voltage ◽  
Complex Models ◽  
Current Voltage Characteristics

In this paper three different procedures for extracting the current-voltage characteristics of a crystalline photovoltaic module are studied. Each procedure is associated to a solar cell model characterized by a well-defined degree of complexity. The results emphasize that the simple models approximate the current-voltage characteristics of a solar cell as good as the more complex models. Even if all the procedures analysed in this paper approximate well the measured characteristics, the specific model parameters experience a large dispersion. From a broader perspective, the results raise a question mark on the ability of the current procedures to accurately extract the solar cell parameters.

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