Tuning a model predictive controller for doubly fed induction generator employing a constrained genetic algorithm

Autor(es)

Rodrigues, Lucas L. ^[1] ; Potts, Alain S. ^[1] ; Vilcanqui, Omar A. C. ^[2] ; Sguarezi Filho, Alfeu J. ^[1]

Afiliação do(s) autor(es)

^[1] Fed Univ ABC UFABC, Santo Andre, SP - Brazil

^[2] Fed Univ Acre UFAC, Rio Branco, AC - Brazil

• Tipo de documento: Artigo Científico
• Fonte: IET ELECTRIC POWER APPLICATIONS; v. 13, n. 6, p. 819-826, JUN 2019.
• Citações Web of Science: 0

Resumo

This study presents a model predictive control (MPC) for a doubly fed induction generator (DFIG) power control using a state-space prediction model. Genetic algorithms (GAs) have demonstrated their potential in finding good solutions for complex problems. However, GA in its original form lacks a mechanism for handling constraints. In this way, a method for tuning the MPC based on a novel constrained GA is proposed. In this way, the method permits a good solution for the weighing matrices with predetermined maximum requirements, such as maximum overshoot, just using the DFIG control simulation. Finally, experimental results are presented to endorse the proposed theory. (AU)

• Processo FAPESP: 17/04623-3 - Controle preditivo aplicado ao conversor de entrada de um sistema fotovoltaico
• Beneficiário: Alfeu Joãozinho Sguarezi Filho
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 16/08645-9 - Pesquisas interdisciplinares em redes inteligentes de energia elétrica
• Beneficiário: João Bosco Ribeiro do Val
• Modalidade de apoio: Auxílio à Pesquisa - Temático