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Current state of the art wind power plant (WPP) controllers operate wind turbines (WTs) independently as individual machines, thus dispatching the WTs’ set points in an equal manner to all of them. To achieve optimal WPP control, three aspects need to be addressed: • Maximizing the yield (power production) balanced against turbine mechanical loading and electricity price • Enhancing WPP capability to provide ancillary services (primary, secondary, and tertiary reserves), and • Reducing operating costs (i.e. reduced fatigue load degradation of WTs and O&M requirement) over the lifetime of the WPP. The goal of TotalControl is to move the WPP controller design philosophy from individual optimization of WT operation to a coordinated optimization of the overall WPP performance. The TotalControl project aims to achieve this by developing and validating advanced integrated WPP/WT control schemes conditioned on grid demandsand wind turbine fatigue damage limits. For developing and testing of the different WPP controllers, a range of high-fidelity and medium-fidelity simulation models are used. These models are already available in the consortium, but will be thoroughly validated against full scale measurements in the Lillgrund WPP. Due to the complexity and multi-scale nature of WPP flow dynamics, the high-fidelity CFDbased models are very expensive in simulation time, e.g. requiring supercomputing, and therefore not well suited as control design models.

Designing wind farms in complex terrain is becoming more and more important, especially for countries like China, where a large portion of the territory is featured as complex terrain. Although potential richer wind resources could be expected at complex terrain sites (thanks to the terrain effects), they also expose many challenges for wind farm designers/developers. In this study, we present the FarmOpt methodology for designing wind farms in complex terrain, which combines thestate-of-the-art wind resource assessment methods with engineering wake models adapted for complex terrain and advanced layout optimization algorithms. Various constraints are also modelled and considered in the design optimization problem for maximizing the annual energy production (AEP). A case study is presented to illustrate the effectiveness of the methodology. Further developments of the FarmOpt tool are also briefly introduced.

Designing offshore wind farms next to existing or planned wind farm clusters has recently become a common practice in the North Sea. These types of projects face unprecedented challenges in term of wind energy siting. The currently ongoing European project FP7 EERA - DTOC (Design Tool for Offshore wind farm Clusters) is aiming at providing a new type of model work-flow to address this issue. The wake modeling part of the EERA - DTOC project is to improve the fundamental understanding of wind turbine wakes and modeling. One of these challenges is to create a new kind of wake modeling work-flow to combine wind farm (micro) and cluster (meso) scale wake models. For this purpose, a benchmark campaign is organized on the existing wind farm wake models available within the project, in order to identify which model would be the most appropriate for this coupling. A number of standardized wake cases for large offshore wind farms will be analyzed, which provide a reasonable range of conditions likely to be experienced in offshore wind farms. The systematic evaluation is based upon high - quality input data that is selected in the sister project IEA - Task 31 “WakeBench”.

The purpose of this paper is to present a power deficit analysis based on offshore wind farm measurements with respect to the atmospheric stability classification. The result is used to validate wind farm prediction models under different inflow and atmospheric stability conditions

In this paper, wake interaction between two wind turbines is analyzed using experimental and numerical approaches. Full-scale wake measurements are conducted at Tjæreborg wind farm and are obtained using a continuous wave lidar mounted on the back of the nacelle of a 2MW NM80 turbine. Numerical analyses are conducted for two double wake cases characterized by different turbine spacing, using the in-house EllipSys3D flow solver. Large Eddy Simulation and Actuator Line technique are used for modeling the rotor and the flow field. 10-minute average streamwise velocity and turbulence level are compared, and good agreement is seen between the measurements and the computations despite of a lateral offset and other discrepancies due to uncertainties on the measured inflow conditions and lidar mounting alignment.

A wind farm optimization framework is presented in detail and demonstrated on two test cases: 1) Middelgrunden and 2) Stags Holt/Coldham. A detailed flow model describing the instationary flow within a wind farm is used together with an aeroelastic model to determine production and fatigue loading of wind farm wind turbines. Based on generic load cases, the wind farm production and fatigue evaluations are subsequently condensed in a large pre-calculated database for rapid calculation of lifetime equivalent loads and energy production in the optimization loop.. The objective function defining the optimization problem includes elements as energy production, turbine degradation, operation and maintenance costs, electrical grid costs and foundation costs. The objective function is optimized using a dedicated multi fidelity approach with the locations of individual turbines in the wind farm spanning the design space. . The results are over all satisfying and are giving some interesting insights on the pros and cons of the design choices. They show in particular that the inclusion of the fatigue loads costs give rise to some additional details in comparison with pure power based optimization. The Middelgrunden test case resulted in an improvement of the financial balance of 2.1 M€ originating from a very large increase in the energy production value of 9.3 M€ mainly counterbalanced by increased electrical grid costs. The Stags Holt/Coldham test case resulted in an improvement of the financial balance of 3.1 M€.&nbsp

Turbulence time series are needed for wind turbine load simulation. The multivariate Fourier simulation method often used for this purpose is extended for inhomogeneous and non-stationary processes of general probability distribution. This includes optional conditional simulation matching simulated series to field measurements at selected points. A probability model for the application of turbine wind loads is discussed, and finally the technique for non-stationary processes is illustrated by turbulence simulation during a front passage.

A coherent wind speed and wind direction change (ECD) load case is defined in the wind turbine standard. This load case is an essential extreme load case that e.g. may be design driving for flap defection of active stall controlled wind turbines. The present analysis identifies statistically the magnitudes of a joint gust event defined by a simultaneously wind speed- and direction change in order to obtain an indication of the validity of the magnitudes specified in the IEC code. The analysis relates to pre-specified recurrence periods and is based on full-scale wind field measurements. The wind speed gust amplitude, occurring simultaneously with a wind direction change, corresponds well to the recommended ECD value of 15 m/s, except for the complex terrain case, where estimated extreme wind speed gust amplitudes are seen to exceed the IEC value with approximately 50%. The estimated extreme wind direction gust amplitudes associated with the investigated European sites are low compared to the recommended IEC- values. However, these values, as function of the mean wind speed, are difficult to validate thoroughly due to the limited number of fully correlated measurements.

The vast majority of wind turbines are today erected in wind farms. As a consequence, wake generated loads are becoming more and more important. We present a new experimental technique to measure the instantaneous wake deficit directly, thus allowing us to quantify the wake meandering as well as the instantaneous wake expansion expressed in a meandering frame of reference. The experimental results are subsequently used in a preliminary verification of the basic conjecture of a wake meandering model that essentially considers the wake as a passive tracer.

This study reports structural dynamic characteristics obtained experimentally from an extensive testing campaign on a 34m long wind turbine blade mounted on a test-rig under laboratory conditions. Further, these experimental results have been compared with analog numerical results obtained from a very detailed FE model of the same blade using 3D solid elements. Both an undamaged and a damaged blade are investigated, and it is observed that the natural frequencies of the first few modes of the blade change very little due to a significant artificial damage imposed in trailing edge, whereas the mode shapes - especially if decomposed into the flapwise, edgewise and torsional components - contain information which might be helpful for detecting and localizing wind turbine blade damages.

Current state of the art wind power plant (WPP) controllers operate wind turbines (WTs) independently as individual machines, thus dispatching the WTs’ set points in an equal manner to all of them. To achieve optimal WPP control, three aspects need to be addressed: • Maximizing the yield (power production) balanced against turbine mechanical loading and electricity price • Enhancing WPP capability to provide ancillary services (primary, secondary, and tertiary reserves), and • Reducing operating costs (i.e. reduced fatigue load degradation of WTs and O&M requirement) over the lifetime of the WPP. The goal of TotalControl is to move the WPP controller design philosophy from individual optimization of WT operation to a coordinated optimization of the overall WPP performance. The TotalControl project aims to achieve this by developing and validating advanced integrated WPP/WT control schemes conditioned on grid demands and wind turbine fatigue damage limits. For developing and testing of the different WPP controllers, a range of high-fidelity and medium-fidelity simulation models are used. These models are already available in the consortium, but will be thoroughly validated against full-scale measurements in the Lillgrund WPP. Due to the complexity and multi-scale nature of WPP flow dynamics, the high-fidelity CFD-based models are very expensive in simulation time, e.g. requiring supercomputing, and therefore not well suited as control design models.

Quantifying accurately wind turbine wakes is a key aspect of wind farm economics in large wind farms. This research compares three engineering wake models with power production data from the Horns Rev and Lillgrund offshore wind farms. Single and multiple wake cases are investigated to verify the performance of the models in different conditions. The simulations reveal that the three wake models have similar behaviours for both wind farms although the turbine spacing and the turbulence intensity are different. The results prove the robustness of the models to provide accurate power predictions when the simulations are averaged over wind direction sectors of 30. However, all models significantly underpredict the power production of a single row of wind turbines using narrow sectors of 3 or 5. This discrepancy is discussed and justified by the wind direction uncertainty included in the datasets.