An Improved Dingo Optimization Algorithm Applied to SHE-PWM Modulation Strategy

This paper presents a modification to the dingo optimization algorithm (mDOA) to solve the non-linear set of equations of the selective harmonic elimination (SHE) control technique widely applied in multilevel inverters. In addition, said modification is conducted to the survival criteria by includi...

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Bibliographic Details
Published in:Applied sciences 2022-02, Vol.12 (3), p.992
Main Authors: Almazán-Covarrubias, Juan H., Peraza-Vázquez, Hernán, Peña-Delgado, Adrián F., García-Vite, Pedro Martín
Format: Article
Language:English
Subjects:
Algorithms
Fuel cells
harmonics
Inverters
Linear equations
metaheuristic algorithms
multilevel inverters
Optimization
Optimization algorithms
Pulse duration modulation
Renewable resources
Statistical tests
Survival
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Summary:This paper presents a modification to the dingo optimization algorithm (mDOA) to solve the non-linear set of equations of the selective harmonic elimination (SHE) control technique widely applied in multilevel inverters. In addition, said modification is conducted to the survival criteria by including a local search to provide a better balance when replacing vectors (dingoes) with a low survival rate. The proposed method is also benchmarked with some unimodal functions to illustrate its better exploitation capabilities. Finally, the SHE optimization results were calculated and compared with three well-known state-of-the-art metaheuristics, where the modified version of the dingo optimization algorithm showed very competitive results. The significant difference between the mDOA results and the rest of the algorithms is determined by the Wilcoxon rank-sum non-parametric statistical test with a 5% degree of significance. The p-values confirm the meaningful advantage of the mDOA compared to other bio-inspired algorithms for many modulation indexes. Experimentally, the proposed algorithm is validated through the implementation of a three-phase 11-level inverter.
ISSN:2076-3417
2076-3417
DOI:10.3390/app12030992