Open AccessMulti-Objective Flower Pollination Algorithm Based Controller for UPQC Including Hybrid Power Source
Author(s) -
Khalid Hussain,
P. Sridhar
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c8433.019320
Subject(s) - voltage sag , total harmonic distortion , particle swarm optimization , control theory (sociology) , controller (irrigation) , pid controller , algorithm , differential evolution , computer science , evolutionary programming , ac power , voltage , engineering , evolutionary algorithm , mathematical optimization , control engineering , mathematics , power quality , electrical engineering , control (management) , temperature control , agronomy , artificial intelligence , biology
This paper presents a new control method for Unified Power Quality Conditioner (UPQC) for effective management of the power-sharing and improvement of the quality of power. The voltage disturbances produced in the source side due to non-linear load conditions can be protected using the UPQC model. Flexible Alternating Current Transmission System (FACTS) devices were fed through a hybrid power generator that had the primary source, a Proton Exchange Membrane Fuel Cell (PEMFC) and a secondary source, a supercapacitor. In this paper, a multi-objective function (power factor, voltage sag, and the total harmonic distortion (THD)) with different control strategies have been considered. An optimization algorithm named Flower Pollination Algorithm (FPA) has used for optimizing Proportional Integral (PI) coefficients. A suitable fitness function has been developed for the FPA method and the simulation performed. The performance of the FPA method has been compared with three different algorithms, namely, particle swarm optimization algorithm (PSOA), Differential Evolution Algorithm (DEA), and Ant Colony Optimization Algorithm (ACOA). The result obtained shows the proposed FPA providing the best result compared to other methods.