Solar-Based Thermoelectric Generator and its ANFIS Model

Yıl 2018, Cilt: 14 Sayı: 3, 271 - 276, 30.09.2018

Ali Ekber Özdemir

https://doi.org/10.18466/cbayarfbe.421575

Öz

In this work, it is
aimed to construct an Adaptive Neuro Fuzzy Inference System (ANFIS) model using
the experimental values of our previous work on solar heating with wind chimney
thermoelectric generator and to predict the generated open circuit voltage of
experimental system under variable conditions. The ANFIS model constructed
makes use of input parameters such as local radiation intensity on solar
collector tube (W), ambiance temperature ^oC and average wind
velocity in the chimney (m/s). Open circuit voltage (V) is denoted as output.
Selected experimental data sets are used in training and testing procedures to
accomplish the model required. Assessment of the outcomes of the study reveals
that the proposed modeling by ANFIS is consistent and validated by the
experimental results. Promising results show that ANFIS model can be used to
estimate the output parameter of solar-based generator (the open circuit
voltage) correctly and this result can use enhancing of presented system.  Employment of artificial neural networks on
renewable energy systems is a rather new area of study. Hence, continuing work
via neural network structures will be related to the optimization and
improvement of these generators for useful energy producing.

Anahtar Kelimeler

Energy conversion, Fuzzy neural networks, Renewable energy sources, Solar heating, Thermoelectricity

Kaynakça

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