Details

Autor(en) / Beteiligte

• Bouden, Abdelmalek
• Haouam, Abdeslam
• Ounnas, Djamel
• Guiza, Dhaouadi

Titel

Efficiency improvement of a thermal photovoltaic hybrid system optimized by using an artificial neural network

Ist Teil von

• 2019 1st International Conference on Sustainable Renewable Energy Systems and Applications (ICSRESA), 2019, p.1-5

Ort / Verlag

IEEE

Erscheinungsjahr

2019

Quelle

IEEE Xplore Digital Library

Beschreibungen/Notizen

• During the photovoltaic conversion of the solar collector, heat is generated, which increases the temperature of PV cell and decreases its efficiency. This phenomenon is exploited by combining between the PV system and the thermal system to form the photovoltaic thermal hybrid solar collectors (PVT), which generates electricity and heat at the same time. This paper presents efficiency improvement of a thermal photovoltaic hybrid system by using an artificial neural network (ANN) to ensure the operation of a generator at its maximum power point (MPPT) and reduce the error between the operating power and the maximum reference power which is variable depending on the load and climatic conditions. The results show that the ANN system correct decisions and avoid cases of indecision, with their ability to adapt to unknown situations.