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

Applied Sciences

Juan H. Almazán-Covarrubias¹  Adrián F. Peña-Delgado¹  Hernán Peraza-Vázquez²  Pedro Martín García-Vite³ 

[1] Departamento de Mecatrónica y Energías Renovables, Universidad Tecnológica de Altamira, Boulevard de los Ríos Km. 3+100, Puerto Industrial Altamira, Altamira 89601, Mexico;Instituto Politécnico Nacional, Research Center for Applied Science and Advanced Technology (CICATA), Km. 14.5 Carretera Tampico-Puerto Industrial Altamira, Altamira 89600, Mexico;TecNM/Instituto Tecnológico de Ciudad Madero, Juventino Rosas y Jesús Urueta s/n, Col. Los Mangos, Cd. Madero 89318, Mexico;

关键词: metaheuristic algorithms;    optimization;    multilevel inverters;    harmonics;   

DOI  :  10.3390/app12030992

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown