Abstract
The recent advantages in the thermal extraction schemes of Photovoltaic (PV) systems became more feasible for domestic applications. The amount of thermal energy available at the PV backside is the source for all thermal extraction/utilizing schemes. But, till now, there is no accurate theoretical method to find the module temperature by any mathematical equation to be adaptable for all the conditions. In this work, we introduced the soft computing based estimation using Adaptive Neural Fuzzy Inference Systems (ANFIS) tool in MATLAB to estimate the module temperature of PV with respect to change of irradiance, ambient temperature, and wind velocity.
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Babu, C., Pathipooranam, P. (2020). PV Module Temperature Estimation by Using ANFIS. In: Das, K., Bansal, J., Deep, K., Nagar, A., Pathipooranam, P., Naidu, R. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 1048. Springer, Singapore. https://doi.org/10.1007/978-981-15-0035-0_24
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DOI: https://doi.org/10.1007/978-981-15-0035-0_24
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