TY - JOUR
T1 - Low cost ANN based MPPT for the mismatched PV modules
AU - Jeyaprabha, S. Berclin
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/12/22
Y1 - 2020/12/22
N2 - 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 Voc and Isc 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.
AB - 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 Voc and Isc 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.
UR - http://www.scopus.com/inward/record.url?scp=85098514348&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1706/1/012083
DO - 10.1088/1742-6596/1706/1/012083
M3 - Conference article
AN - SCOPUS:85098514348
SN - 1742-6588
VL - 1706
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012083
T2 - 1st International Conference on Advances in Physical Sciences and Materials 2020, ICAPSM 2020
Y2 - 13 August 2020 through 14 August 2020
ER -