Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

TÜBİTAK

2022

Maximum power point tracking

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Modeling And Validation Of The Thermoelectric Generator With Considering The Change Of The Seebeck Effect And Internal Resistance, Mehmet Ali̇ Üstüner, Hayati̇ Mamur, Sezai̇ Taşkin Nov 2022

Modeling And Validation Of The Thermoelectric Generator With Considering The Change Of The Seebeck Effect And Internal Resistance, Mehmet Ali̇ Üstüner, Hayati̇ Mamur, Sezai̇ Taşkin

Turkish Journal of Electrical Engineering and Computer Sciences

Thermoelectric generators (TEGs) produce power in direct proportion to the temperature difference between their surfaces. The Seebeck coefficient and internal resistance of the thermoelements (TEs) that make up the TEGs change depending on the temperature change. In simulation studies, it is seen that these two values are kept constant. However, this situation prevents approaching the data of TEG in real applications. In this study, a TEG Simulink/MATLAB ® model has been developed to capture real TEG module data, which considers changing of both the Seebeck coefficient and the internal resistance depending on the temperature difference change. To achieve this aim, …


Comparison Of Deep Learning And Regression-Based Mppt Algorithms In Pv Systems, Murat Sali̇m Karabi̇naoğlu, Beki̇r Çakir, Mustafa Engi̇n Başoğlu, Abdülvehhab Kazdaloğlu, Azi̇z Güneroğlu Sep 2022

Comparison Of Deep Learning And Regression-Based Mppt Algorithms In Pv Systems, Murat Sali̇m Karabi̇naoğlu, Beki̇r Çakir, Mustafa Engi̇n Başoğlu, Abdülvehhab Kazdaloğlu, Azi̇z Güneroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Solar energy systems (SES) and photovoltaic (PV) modules should be operated at the maximum power point (MPP) to achieve the highest efficiency in the energy generation processes. Maximum power point tracking (MPPT) applications using conventional methods may not be able to follow the global MPP (GMPP) of the PV system under changing atmospheric conditions and they could oscillate around the local MPP. In this study, a machine learning and deep learning (DL) based long short-term memory (LSTM) model is proposed as an innovative solution for MPPT. Contrary to the traditional MPPT applications using current and voltage sensors, the output resistance …