Abstract
This paper deals the artificial intelligence-based adaptive neuro-fuzzy inference system (ANFIS) for achievement of peak power from solar modules. This controller does not require the previous knowledge of database and has economical implementation as there is no additional sensor needed. The performance of ANFIS control is investigated by considering grid-integrated photovoltaic (PV) system. ANFIS supervisory control regulates the duty cycle of buck/boost converter under abrupt solar insolation. Simulated responses interpret that ANFIS has robust, rapid, and precise behavior under different operating conditions. Classical methods suffer more oscillating behavior with high settling period to obtain maximum PV power.
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Priyadarshi, N., Azam, F., Sharma, A.K., Vardia, M. (2020). An Adaptive Neuro-Fuzzy Inference System-Based Intelligent Grid-Connected Photovoltaic Power Generation. In: Sahana, S., Bhattacharjee, V. (eds) Advances in Computational Intelligence. Advances in Intelligent Systems and Computing, vol 988. Springer, Singapore. https://doi.org/10.1007/978-981-13-8222-2_1
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