Predictive Incremental Vector Control for DFIG With Weighted-Dynamic Objective Constraint-Handling Method-PSO Weighting Matrices Design

Author(s)

Rodrigues, Lucas Lima ^{[1, 2]} ; Solis-Chaves, J. Sebastian ^[3] ; Vilcanqui, Omar A. C. ^[1] ; Sguarezi Filho, Alfeu J. ^[2]

Affiliation

^[1] Univ Fed Acre, Ctr Exact & Technol Sci CCET, Rio Branco 69920-900, Rio Branco - Brazil

^[2] Fed Univ ABC UFABC, Modeling & Appl Social Sci Ctr CECS, Dept Engn, BR-09210580 Santo Andre, SP - Brazil

^[3] Univ Escuela Colombiana Carreras Ind ECCI, Dept Mechatron Engn, Bogota 111311 - Colombia

• Document type: Journal article
• Source: IEEE ACCESS; v. 8, p. 114112-114122, 2020.
• Web of Science Citations: 0

Abstract

This paper proposes a Particle Swarm Optimization (PSO) based method, the Weighted-Dynamic-Objective Constraint-Handling PSO Method (WDOCHM-PSO). This was used to design the weighting matrices of an incremental Model-Based Predictive Controller (MBPC) for a Doubly Fed Induction Generator (DFIG) applied in a small-scale wind energy system. In contrast to the original PSO, the proposed method has an inner mechanism for dealing with constraints and an adaptive search factor. Additionally, the proposed incremental MPBC implementation does not need the flux information, since the intrinsic integral action rejects the constant flux disturbance. Finally, experimental results show that the proposed controller with the new constraint handling design method is nearly two times faster (In terms of settling time) than other formulations reported in the literature. (AU)

• FAPESP's process: 17/04623-3 - Predictive control applied to the input converter for photovoltaic systems
• Grantee: Alfeu Joãozinho Sguarezi Filho
• Support Opportunities: Regular Research Grants
• FAPESP's process: 16/08645-9 - Interdisciplinary research activities in electric smart grids
• Grantee: João Bosco Ribeiro do Val
• Support Opportunities: Research Projects - Thematic Grants