Optimization of Multilevel Inverters Using Novelty-driven Multi-verse Optimization Algorithm
File version
Author(s)
Neshat, Mehdi
Mirjalili, Seyedali
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
Size
File type(s)
Location
Teesside Univ, Middlesbrough, United Kingdom
License
Abstract
All over the world, renewable energy technologies which need power electronics based inverters in their designs are becoming more and more popular, thus detailed analysis to test the operational efficiency is required. This paper utilizes a new adaptive Multi-verse Optimization (MVO) Algorithm combined with novelty search method to solve harmonic elimination problem in multilevel inverters. We compare the obtained numerical simulations to those obtained by using the grey wolf optimization and standard MVO algorithm. The numerical simulations are performed on 7, 11, and 15 level inverters with different modulation indexes. From the simulation results, we observe that adaptive novelty search Multi-verse Optimization (MVO) based approach was able to obtain less total harmonic distortion for different modulation indexes.
Journal Title
Conference Title
2021 56th International Universities Power Engineering Conference (UPEC)
Book Title
Edition
Volume
Issue
Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
Item Access Status
Note
Access the data
Related item(s)
Subject
Data structures and algorithms
Energy & Fuels
Engineering, Electrical & Electronic
harmonic distortion
local search
Persistent link to this record
Citation
Ceylan, O; Neshat, M; Mirjalili, S, Optimization of Multilevel Inverters Using Novelty-driven Multi-verse Optimization Algorithm, 2021 2021 56th International Universities Power Engineering Conference (UPEC), 2021