How to identify design optimization problems that can be improved with a control co-design approach ?

Jenna Iori*, Carlo Luigi Bottasso, Michael Kenneth McWilliam

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Control co-design is a promising approach for wind turbine design due to the importance of the controller in power production, stability and load alleviation. However, the high computational effort required to solve optimization problems with added control design variables is a major obstacle to quantify the benefit of this approach. In this work, we propose a methodology to identify if a design problem can benefit from control co-design. The estimation method, based on post-optimum sensitivity analysis, quantifies how the optimal objective value varies with a change in control tuning.

The performance of the method is evaluated on a tower design optimization problem, where fatigue load constraints are a major driver, and using a Linear Quadratic Regulator targeting fatigue load alleviation. We use the gradient-based multi-disciplinary optimization framework Cp-max. Fatigue damage is evaluated with time-domain simulations corresponding to the certification standards. The estimation method applied to the optimal tower mass and optimal levelized cost of energy show good agreement with the results of the control-co design optimization, while using only a fraction of the computational effort.

Our results additionally show that there may be little benefit to use control co-design in the presence of an active frequency constraint. However, for a soft-soft tower configuration where the resonance can be avoided with active control, using control co-design results in a higher tower with reduced mass.
Original languageEnglish
JournalWind Energy Science
DOIs
Publication statusPublished - 2023
Externally publishedYes

Keywords

  • Control co-design
  • Multi-disciplinary optimization
  • Wind Energy
  • Fatigue
  • Wind turbine tower
  • LQR controller
  • Design sensitivity analysis

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