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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.