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Controlling of Multi-Level Inverter under Shading Conditions Using Artificial Neural Network

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dc.contributor.advisor Khader, Sameer
dc.contributor.author Khader, Sameer
dc.contributor.author Qawasmeh, Abdelsami
dc.date.accessioned 2021-04-20T11:03:37Z
dc.date.accessioned 2022-05-22T08:55:27Z
dc.date.available 2021-04-20T11:03:37Z
dc.date.available 2022-05-22T08:55:27Z
dc.date.issued 2020-06
dc.identifier.issn 0000000091950263
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/8340
dc.description.abstract This paper describes the effects of photovoltaic voltage changes on Multi-level inverter (MLI) due to solar irradiation variations, and methods to overcome these changes. The irradiation variation affects the generated voltage, which in turn varies the switching angles required to turn-on the inverter power switches in order to obtain minimum harmonic content in the output voltage profile. Genetic Algorithm (GA) is used to solve harmonics elimination equations of eleven level inverters with equal and unequal dc sources. After that artificial neural network (ANN) algorithm is proposed to generate appropriate set of switching angles for MLI at any level of input dc sources voltage causing minimization of the total harmonic distortion (THD) to an acceptable limit. MATLAB/Simulink platform is used as a simulation tool and Fast Fourier Transform (FFT) analyses are carried out for output voltage profile to verify the reliability and accuracy of the applied technique for controlling the MLI harmonic distortion. According to the simulation results, the obtained THD for equal dc source is 9.38%, while for variable or unequal dc sources it varies between 10.26% and 12.93% as the input dc voltage varies between 4.47V and 11.43V respectively. The proposed ANN algorithm provides satisfied simulation results that match with results obtained by alternative algorithms. en_US
dc.language.iso en en_US
dc.publisher World Academy of Science, Engineering and Technology International Journal of Energy and Power Engineering en_US
dc.relation.ispartofseries Vol:14, No:6, 2020;PP 154-159
dc.subject Multi level inverter, genetic algorithm, artificial neural network , total harmonic distortion. en_US
dc.title Controlling of Multi-Level Inverter under Shading Conditions Using Artificial Neural Network en_US
dc.type Article en_US


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