Open AccessSingle sensor based MPPT for partially shaded solar photovoltaic by using human psychology optimisation algorithm
Author(s) -
Kumar Nishant,
Hussain Ikhlaq,
Singh Bhim,
Panigrahi Bijaya Ketan
Publication year - 2017
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2016.1497
Subject(s) - maximum power point tracking , photovoltaic system , microcontroller , battery (electricity) , computer science , maximum power principle , matlab , power (physics) , algorithm , engineering , electrical engineering , embedded system , voltage , inverter , physics , quantum mechanics , operating system
This study introduces a quick, highly efficient and a single sensor based maximum power point (MPP) tracking (MPPT) for partially shaded solar photovoltaic (PV) system. For this purpose, a novel ‘human psychology optimisation’ (HPO) algorithm is proposed, which is based on psychological and mental states of an ambitious person. The main objective of the HPO algorithm is the maximum extraction of the power from PV panel and efficiently supplying it to the load (battery). In this study, a single (current) sensor based MPPT for battery charging, by using HPO and some recent state‐of‐the‐art MPPT algorithms, is tested on MATLAB simulation and verified on a developed prototype of the partially shaded solar PV system. The efficient battery charging and quickly reaching the MPP by HPO w.r.t. all other algorithms, in steady‐state as well as in dynamic conditions, show the superiority over all the recent state‐of‐the‐art control methods. Moreover, due to the single sensor, the cost of the MPPT system is reduced, as well as due to HPO the computational burden is very less, so it can be easily implemented on the low‐cost microcontroller.