A Comparison of Multi-Objective Optimisation of Two Wind Turbine Controller Designs. Issue 2 (September 2020)

• Record Type: Journal Article
• Authors: Yu, W.; Engels, W. P.; Stock-Williams, C.F.W.
• Is Part Of: Journal of physics. Volume 1618:Issue 2(2020)
• Publication Date: 2020-09
• Subjects: wind turbine -- state-space model controller -- multi-objective -- Bayesian optimization -- Pareto front; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1618/2/022046
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: This paper presents a comparison between two pitch controllers for a 10MW wind turbine, a baseline using PI and a state-space model, where each controller's parameters have been chosen using Bayesian optimization. Four objectives are simultaneously examined: energy output; pitch action; blade load; and tower load. First, it is shown that, for both controllers, using parameters selected from the obtained Pareto fronts achieves higher energy production with less energy consumption of pitch activities and with less load in blade and tower, compared with settings chosen by an expert. Second, in this robust comparison of the capabilities of both controllers, the increased degrees of freedom and reduced simplification in the more advanced controller are seen to have greater potential to improve each of the objectives.