Open AccessAdvanced wavelet transform based shunt hybrid active filter in PV integrated power distribution system for power quality enhancement
Author(s) -
Ranjan Das Soumya,
Mishra Alok K.,
Ray Prakash K.,
Mohanty Asit,
Mishra Dillip K.,
Li Li,
Hossain M.J.,
Mallick Ranjan K.
Publication year - 2020
Publication title -
iet energy systems integration
Language(s) - English
Resource type - Journals
ISSN - 2516-8401
DOI - 10.1049/iet-esi.2020.0015
Subject(s) - control theory (sociology) , photovoltaic system , least mean squares filter , electronic engineering , computer science , active filter , wavelet transform , voltage , engineering , wavelet , adaptive filter , artificial intelligence , control (management) , electrical engineering
Power quality (PQ) issues are significant in inverter‐fed distributed generation system with non‐linear loads which degrades the performance of the consumer equipments and the power system itself. Therefore, this work presents an improved photovoltaic (PV) coupled hybrid filter for the improvement in PQ in an active distribution system. A shunt hybrid active filter (SHAF) integrated with PV is designed with the help of an advanced signal processing approach called dual tree‐complex wavelet transform (DT‐CWT) for extracting the frequency information in the voltage and current due to the PQ disturbances. For calculating the reference current and switching signals, zero attracting least mean square (ZA‐LMS) is considered in the hybrid filter and adaptive perturb and observe‐fuzzy algorithm is proposed for maximum power point tracking in PV system to improve the performance under different operating conditions. The system model using the proposed technique is developed in MATLAB/Simulink and real‐time experimental set up using two different controllers, i.e. the conventional proportional‐integral (PI) and fuzzy‐PI controllers. The results on comparison illustrates better performance of the proposed ZA‐LMS and DT‐CWT with fuzzy‐PI based SHAF technique for PQ improvements with respect to that of LMS/normalised LMS with PI/fuzzy‐PI based SHAF under different operating scenarios.