Open AccessMOPSO‐based optimal control of shunt active power filter using a variable structure fuzzy logic sliding mode controller for hybrid (FC‐PV‐Wind‐Battery) energy utilisation scheme
Author(s) -
Elgammal Adel A.A.,
Elnaggar Mohammed F.
Publication year - 2017
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2016.0440
Subject(s) - control theory (sociology) , total harmonic distortion , photovoltaic system , wind power , voltage , particle swarm optimization , fuzzy logic , controller (irrigation) , engineering , computer science , algorithm , electrical engineering , control (management) , artificial intelligence , agronomy , biology
This paper presents an effective concept for hybrid fuel cell‐photovoltaic‐wind‐battery active power filter (FC‐PV‐Wind‐Battery) energy scheme based on the variable structure sliding mode fuzzy logic controller (SMFLC) using the multi‐objective particle swarm optimisation (MOPSO). The parameters of the fuzzy logic control membership functions and the weighting factors of the SMFLC can be tuned by MOPSO in such an approach to optimise the dynamic performance of the shunt active power filter (SAPF) and minimise the total harmonic distortion (THD) of the source current waveform and voltage waveform of the hybrid (FC‐PV‐Wind‐Battery). A group of objective functions was chosen to validate the dynamic performance of the SAPF and the effectiveness of the MOPSO‐SMFLC. These selected fitness functions are: (i) minimising the error of the inverter capacitor DC voltage, (ii) minimising the THD of the output current and voltage of DC and AC sides and (iii) minimising the controller reaching time. A computer simulation study using Simulink/Matlab and experimental laboratory prototype were carried on to asses and compare the dynamic performance of the proposed MOPSO‐SMFLC controller with the conventional proportional–integral–derivative, variable structure SMFLC, the feed‐forward multilayer neural network controller and the variable structure SMFLC based on the single‐objective particle swarm optimisation.