Including the power regulation strategy in aerodynamic optimization of wind turbines for increased design freedom

Abstract

In wind turbine optimization, the standard power regulation strategy follows a constrained trajectory based on the maximum power coefficient. It can be updated automatically during the optimization process by solving a nested maximization problem at each iteration. We argue that this model does not take advantage of the load alleviation potential of the regulation strategy and additionally requires significant computational effort. An alternative approach is proposed, where the rotational speed and pitch angle control points for the entire operation range are set as design variables, changing the problem formulation from nested to one-level. The nested and one-level formulations are theoretically and numerically compared on different aerodynamic blade design optimization problems for AEP maximization. The aerodynamics are calculated with a steady-state blade element momentum method. The onelevel approach increases the design freedom of the problem and allows introducing a secondary objective in the design of the regulation strategy. Numerical results indicate that a standard regulation strategy can still emerge from a one-level optimization. Second, we illustrate that novel optimal regulation strategies can emerge from the one-level optimization approach. This is demonstrated by adding a thrust penalty term and a constraint on the maximum thrust. A region of minimal thrust tracking and a peak-shaving strategy appear automatically in the optimal design.control co-design, multi-disciplinary analysis and optimization, power regulation strategy, wind turbine blade design | INTRODUCTIONDesigning a modern wind turbine is a complex engineering task, due to the multi-disciplinary nature and the uncertain environment it must operate in. Many different objectives and requirements need to be considered during the design process: power extraction, reduction of costs, stability, noise, and so forth. In addition, the designer has to take into account the different disciplines involved with the goals of (i) accurately forecast the behavior of the final design and (ii) take advantage of the potential couplings between disciplines to improve the design. This makes numerical optimization an ideal tool to be used for wind turbine design. Numerous studies have focused on the development of numerical tools for optimization with the goal of handling the multi-disciplinary aspect of wind turbine design. For example, Bottasso et al 1 take in account the aero-elastic

Open-Loop Control Co-Design of Floating Offshore Wind Turbines Using Linear Parameter-Varying Models

“…The maintenance costs and the total lifetime energy output are dependent on how the system operates and, consequently, depend on the environment and how it is controlled [21,22]. Recent studies have shown that advanced control strategies for offshore wind applications can increase the power extracted from the turbine and minimize the levelized cost [23,24]. Most conventional LCOE estimates have not incorporated detailed dynamic assessments nor the impact of novel control strategies.…”