Abstract
This paper presents the solution to mitigate the total harmonic distortion (THD) in multilevel inverters (MLIs) using novel improved whale optimization algorithm (IWOA). The IWOA falls under the category of swarm-based nature inspired optimization algorithms. It uses a novel diffusion process using a random walk technique and utilizes an additional ranking system to estimate the optimum solution to minimize THD. Moreover, THD minimization is further accomplished through nine various meta-heuristic algorithms for investigation and comparative analysis. The selected algorithms along with the proposed IWOA are rigorously tested on single phase 5 and 7 level cascaded H-Bridge MLIs for various performance parameters such as consistency, computational efficiency and speed of convergence. It is found that the proposed algorithm outperforms the nine algorithms and is efficient for THD minimization for modulation index (MI) in the range of 0–1. The results are analyzed and reported after thorough verification using MATLAB simulation.
Highlights
It presents a novel switching technique through improved whale optimization algorithm (IWOA) to optimize the switching angles of a single phase 5 and 7 level multilevel inverters (MLIs) in order to minimize the total harmonic distortion (THD).
IWOA incorporates a novel diffusion process and two new position updating techniques
The proposed IWOA provides better computational efficiency, improved consistency and faster convergence compared to the older whale optimization algorithm (WOA) with minimal tuning of the algorithm’s parameters.
The proposed IWOA is compared alongside various meta-heuristics like genetic algorithm (GA), particle swarm optimization (PSO), grey wolf optimizer (GWO), krill herd (KH), artificial electric field algorithm (AEFA), sun flower optimizer (SFO), galactic swarm optimization (GSO), fruit fly optimization algorithm (FOA) and whale optimization algorithm (WOA) for optimal THD minimization.
Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
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© 2020 Walter de Gruyter GmbH, Berlin/Boston
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- Review
- Power quality problem and key improvement technology for regional power grids
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- Experimental control of photovoltaic system using neuro – Kalman filter maximum power point tracking (MPPT) technique
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Articles in the same Issue
- Review
- Power quality problem and key improvement technology for regional power grids
- Research Articles
- Machine learning roles in advancing the power network stability due to deployments of renewable energies and electric vehicles
- Analysis between graph-based and Power Transfer Distribution Factors (PTDF)-based model reduction methods in Electric Power Systems
- Experimental control of photovoltaic system using neuro – Kalman filter maximum power point tracking (MPPT) technique
- Data compression techniques for Phasor Measurement Unit (PMU) applications in smart transmission grid
- Influence of inter-turn short circuit on the performance of 10 kV, 1000 kW induction motor
- Detection of coherent groups using measured signals, in an inter-area mode, for creating controlled islands to protect the power system from blackout
- Multi-objective optimization of optimal capacitor allocation in radial distribution systems
- A novel approach of closeness centrality measure for voltage stability analysis in an electric power grid
- Dynamic Simulation of Eastern Regional Grid of India using Power System Simulator for Engineering PSS®E
- Optimal total harmonic distortion minimization in multilevel inverter using improved whale optimization algorithm
- A cost effective accumulator management system for electric vehicles