Comparison of MPPT Algorithms Under Uniformly Varying Atmospheric Conditions

• Published in: 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) pp. 1406 - 1411
• Main Authors: Kaushik, Chirag, Garg, Rachana, Priya Mahajan, Prof
• Format: Conference Proceeding
• Language: English
• Published: IEEE 11-08-2022
• Subjects: Artificial Neural network; Artificial neural networks; Boost Converter; Fill Factor; Fill factor (solar cell); Fuzzy logic; Instruments; Maximum power point trackers; Maximum Power Point tracking; Photovoltaic systems; Radiation effects; Temperature; Type 1 Fuzzy logic Controller
• DOI: 10.1109/ICICICT54557.2022.9917652

Power output from a photovoltaic (PV) array changes based on the change in ambient temperature and solar irradiation. Conventional Maximum Power Point (MPP) techniques were adopted to extract maximum power from PV array which were easy to implement but multiple drawbacks were observed related to oscillations around MPP and slower response under varying atmospheric conditions. To overcome such drawbacks of conventional algorithms, PV system requires some intelligent techniques to track the maximum power point which may help to design more efficient PV system. Authors in the present study have highlighted the comparison of multiple conventional and intelligent control techniques such as Perturb and Observe(P&O), Incremental Conductance (INC), Type 1 Fuzzy logic controller (T1-FLC) and Artificial Neural Network (ANN) based techniques. Uniform variation of solar irradiation and ambient temperature has been considered to compare the oscillations in output power waveform, power loss and fill factor of PV array. Superiority of ANN based technique has been established for all the considered factors. The work has been carried out using MATLAB/SIMULINK environment.