%0 Journal Article %1 puthanveettilestimation %A Puthanveettil, Suresh E. %A Cho, Mengu %A Suresh, Amrita %D 2016 %J International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI) %K Solar algorithm cell characteristics current current-voltage genetic particle radiation resistance reverse saturation series shunt %N 1 %P 25 - 32 %T ESTIMATION OF THE PARAMETERS OF SOLAR CELLS FROM CURRENT-VOLTAGE CHARACTERISTICS USING GENETIC ALGORITHM %U https://aircconline.com/ijscai/V5N1/5116ijscai03.pdf %V 5 %X This paper presents a method for calculating the light generated current, the series resistance, shun resistance and the two components of the reverse saturation current usually encountered in the double diode representation of the solar cell from the experimental values of the current-voltage characteristics of the cell using genetic algorithm. The theory is able to regenerate the above mentioned parameters to very good accuracy when applied to cell data that was generated from pre-defined parameters. The method is applied to various types of space quality solar cells and sub cells. All parameters except the light generated current are seen to be nearly the same in the case of a cell whose characteristics under illumination and in dark were analyzed. The light generated current is nearly equal to the short- circuit current in all cases. The parameters obtained by this method and another method are nearly equal wherever applicable. The parameters are also shown to represent the current-voltage characteristics well.

@article{puthanveettilestimation, abstract = {This paper presents a method for calculating the light generated current, the series resistance, shun resistance and the two components of the reverse saturation current usually encountered in the double diode representation of the solar cell from the experimental values of the current-voltage characteristics of the cell using genetic algorithm. The theory is able to regenerate the above mentioned parameters to very good accuracy when applied to cell data that was generated from pre-defined parameters. The method is applied to various types of space quality solar cells and sub cells. All parameters except the light generated current are seen to be nearly the same in the case of a cell whose characteristics under illumination and in dark were analyzed. The light generated current is nearly equal to the short- circuit current in all cases. The parameters obtained by this method and another method are nearly equal wherever applicable. The parameters are also shown to represent the current-voltage characteristics well. }, added-at = {2021-10-20T09:29:31.000+0200}, author = {Puthanveettil, Suresh E. and Cho, Mengu and Suresh, Amrita}, biburl = {https://www.bibsonomy.org/bibtex/26a6b9011e1f17021dc21ed60a91f217c/leninsha}, interhash = {805468fb7a7aa9f215496495ac9890b9}, intrahash = {6a6b9011e1f17021dc21ed60a91f217c}, journal = {International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)}, keywords = {Solar algorithm cell characteristics current current-voltage genetic particle radiation resistance reverse saturation series shunt}, month = {February}, number = 1, pages = {25 - 32}, timestamp = {2021-10-20T09:29:31.000+0200}, title = {ESTIMATION OF THE PARAMETERS OF SOLAR CELLS FROM CURRENT-VOLTAGE CHARACTERISTICS USING GENETIC ALGORITHM}, url = {https://aircconline.com/ijscai/V5N1/5116ijscai03.pdf}, volume = 5, year = 2016 }