Advanced modeling and control of 5 MW wind turbine using global optimization algorithms. Issue 5 (October 2019)

• Record Type: Journal Article
• Authors: Jafari, Soheil; Majidi Pishkenari, Mohsen; Sohrabi, Shahin; Feizarefi, Morteza
• Is Part Of: Wind engineering. Volume 43:Issue 5(2019)
• Page Start: 488
• Page End: 505
• Publication Date: 2019-10
• Subjects: Wind turbine -- controller gain tuning -- optimization -- meta-heuristics -- Imperialist Competitive Algorithm -- Differential Evolution; Wind-pressure -- Periodicals; Winds -- Periodicals; Wind power -- Periodicals; Engineering meteorology -- Periodicals; Pression du vent; Vents; Énergie éolienne; Météorologie appliquée; Engineering meteorology; Wind power; Wind-pressure; Winds; Periodicals; 621.4505
• DOI: 10.1177/0309524X18807471
• Languages: English
• ISSNs: 0309-524X

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.