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SUMMARYThis paper describes the use of topology optimization as a synthesis tool for the design of largedisplacement compliant mechanisms. An objective function for the synthesis of large-displacement mechanisms is proposed together with a formulation for synthesis of path-generating compliant mechanisms. The responses of the compliant mechanisms are modelled using a total Lagrangian ÿnite element formulation, the sensitivity analysis is performed using the adjoint method and the optimization problem is solved using the method of moving asymptotes. Procedures to circumvent some numerical problems are discussed.

A wind farm layout optimization framework based on a multi-fidelity optimization approach is applied to the offshore test case of Middelgrunden, Denmark as well as to the onshore test case of Stag Holt -Coldham wind farm, UK. While aesthetic considerations have heavily influenced the famous curved design of the Middelgrunden wind farm, this work focuses on demonstrating a method that optimizes the profit of wind farms over their lifetime based on a balance of the energy production income, the electrical grid costs, the foundations cost, and the cost of wake turbulence induced fatigue degradation of different wind turbine components. A multi-fidelity concept is adapted, which uses cost function models of increasing complexity (and decreasing speed) to accelerate the convergence to an optimum solution. In the EU-FP6 TOP-FARM project, three levels of complexity are considered. The first level uses a simple stationary wind farm wake model to estimate the Annual Energy Production (AEP), a foundations cost model depending on the water depth and an electrical grid cost function dictated by cable length. The second level calculates the AEP and adds a wake-induced fatigue degradation cost function on the basis of the interpolation in a database of simulations performed for various wind speeds and wake setups with the aero-elastic code HAWC2 and the dynamic wake meandering model. The third level, not considered in this present paper, includes directly the HAWC2 and the dynamic wake meandering model in the optimization loop in order to estimate both the fatigue costs and the AEP. The novelty of this work is the implementation of the multi-fidelity approach in the context of wind farm optimization, the inclusion of the fatigue degradation costs in the optimization framework, and its application on the optimal performance as seen through an economical perspective.

The present work contains a deformable trailing edge fl ap controller integrated in a numerically simulated modern, variablespeed, pitch-regulated megawatt (MW)-size wind turbine. The aeroservoelastic multi-body code HAWC2 acts as a component in the control loop design. At the core of the proposed controller, all unsteady loads are divided by frequency content. Blade pitching and generator moment react to low-frequency excitations, whereas fl aps deal with high-frequency excitations. The present work should be regarded as an investigation into the fatigue load reduction potential when applying trailing edge fl aps on a wind turbine blade rather than a conclusive control design with traditional issues like stability and robustness fully investigated. Recent works have shown that the fatigue load reduction by use of trailing edge fl aps may be greater than for traditional pitch control methods. By enabling the trailing edge to move independently and quickly along the spanwise position of the blade, local small fl utuations in the aerodynamic forces can be alleviated by deformation of the airfoil fl ap. Strain gauges are used as input for the fl ap controller, and the effect of placing strain gauges at various radial positions on the blade is investigated. An optimization routine minimizes blade root fatigue loads. Calculations are based on the 5 MW reference wind turbine part of the UpWind project primarily with a mean turbulent wind speed close to rated power. A fatigue load reduction of 25% in the blade root moment was obtained for a continuous 6.3 m long fl ap. 194Flaps and wind turbine controllers using strain gauge sensors P. B. Andersen et al. Wind Energ. 2010; 13:193-206 196 Flaps and wind turbine controllers using strain gauge sensors P. B. Andersen et al.

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