Advanced modelling and control of 5MW wind turbine using global optimization algorithms

Date published

2018-10-29

Free to read from

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

SAGE

Department

Type

Article

ISSN

0309-524X

Format

Citation

Jafari S, Pishkenari MM, Sohrabi S, Feizarefi M. (2019) Advanced modelling and control of 5 MW wind turbine using global optimization algorithms. Wind Engineering, Volume 43, Issue 5, October 2019, pp. 488-505

Abstract

This article presents a methodological approach for controller gain tuning of wind turbines using global optimization algorithms. For this purpose, the wind turbine structural and aerodynamic modeling are first described and a complete model for a 5 MW wind turbine is developed as a case study based on a systematic modeling approach. The turbine control requirements are then described and classified using its power curve to generate an appropriate control structure for satisfying all turbine control modes simultaneously. Next, the controller gain tuning procedure is formulated as an engineering optimization problem where the command tracking error and minimum response time are defined as objective function indices and physical limitations (overspeed and oscillatory response) are considered as penalty functions. Taking the nonlinear nature of the turbine model and its controller into account, two meta-heuristic global optimization algorithms (Imperialist Competitive Algorithm and Differential Evolution) are used to deal with the defined objective functions where the mechanism of interaction between the defined problem and the used algorithms are presented in a flowchart feature. The results confirm that the proposed approach is satisfactory and both algorithms are able to achieve the optimized controller for the wind turbine.

Description

Software Description

Software Language

Github

Keywords

Wind turbine, controller gain tuning, optimization, meta-heuristics, Imperialist Competitive Algorithm, Differential Evolution

DOI

Rights

Attribution-NonCommercial 4.0 International

Relationships

Relationships

Supplements

Funder/s