Open AccessLow cost ANN based MPPT for the mismatched PV modules
Author(s) -
S. Berclin Jeyaprabha
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1706/1/012083
Subject(s) - maximum power point tracking , photovoltaic system , solar micro inverter , maximum power principle , control theory (sociology) , computer science , uniqueness , pyranometer , power (physics) , point (geometry) , automotive engineering , voltage , engineering , control (management) , mathematics , solar energy , electrical engineering , artificial intelligence , physics , mathematical analysis , geometry , inverter , quantum mechanics
Due to manufacturing dispersal, the photovoltaic (PV) panels of similar rating and manufacturer have distinctive characteristics in practical. As the maximum power point tracking (MPPT) becomes essential to optimally utilize the solar PV panel, distributed maximum power point tracking (DMPPT) is considered in this paper to follow the MPP of each panel. As the common MPP value is used in the existing DMPPT method to control all the panels, it fails to consider the uniqueness of each panel. By considering the uniqueness of each panel, the ANN based MPPT is implemented in this paper. As the ANN is trained using the actual characteristics of each panel based on the operating current, voltage and temperature, it is able to track the actual MPP. Due to the solar irradiance free MPPT, the costly pyranometer is not required in the actual PV system for MPPT. It reduces the cost of the system and also provides the interruption free tracking due to its independent nature on V oc and I sc values. Also, because of the looping free behaviour of the proposed algorithm, it is capable of following the MPP at rapidly varying condition. The proposed technique and the verified outcomes are discussed here in detail.