A Wake Detector for Wind Farm Control

The paper describes an observer capable of detecting the impingement on a wind turbine rotor of the wake of an upstream machine. The observer estimates the local wind speed and turbulence intensity on the left and right parts of the rotor disk. The estimation is performed based on blade loads measured by strain gages or optical fibers, sensors which are becoming standard equipment on many modern machines. A lower wind speed and higher turbulence intensity on one part of the rotor, possibly in conjunction with other information, can then be used to infer the presence of a wake impinging on the disk. The wake state information is useful for wind plant control strategies, as for example wake deflection by active yawing. In addition, the local wind speed estimates may be used for a rough evaluation of the vertical wind shear

High-resolution periodic mode shapes identification for wind turbines

The stability analysis of in-operation wind turbines is a very important topic, that has received considerable attention in the last years. Many identification algorithms have been developed to estimate frequencies and damping ratios, but very few papers have been dedicated to the mode shapes. The knowledge of high-resolution mode shapes could be exploited for several applications including model validation, accurate description of the vibratory content of a machine and spatially-accurate damage detection. In this work, we will present a procedure to compute the high-resolution periodic mode shapes of a wind turbine, and apply it to a high-fidelity wind turbine model. The results show that this methodology is able to identify the first low-damped modes of the system with good accuracy

Wake center position tracking using downstream wind turbine hub loads

Having an improved awareness of the flow within a wind farm is useful for power harvesting maximization, load minimization and design of wind farm layout. Local flow information at each wind turbine location can be obtained by using the response of the wind turbines, which are consequently used as distributed sensors. This paper proposes the use of hub loads to track the position of wakes within a wind farm. Simulation experiments conducted within a high-fidelity aeroservoelastic environment demonstrate the performance of the new method

A MIMO periodic ARX identification algorithm for the Floquet stability analysis of wind turbines

The paper presents a new stability analysis approach applicable to wind turbines. At first, a reduced order periodic model is identified from response time histories, and then stability is assessed using Floquet theory. The innovation of the proposed approach is in the ability of the algorithm to simultaneously consider multiple response time histories, for example in the form of measurements recorded both on the rotor and in the stand still system. As each different measurement carries a different informational content on the system, the simultaneous use of all available signals improves the quality and robustness of the analysis

Simultaneous observation of wind shears and misalignments from rotor loads

A wind turbine is used in this paper as a sensor to measure the wind conditions at the rotor disk. In fact, as any anisotropy in the wind will lead to a specific signature in the machine response, by inverting a response model one may infer its generating cause, i.e. the wind. Control laws that exploit this knowledge can be used to enhance the performance of a wind turbine or a wind power plant. This idea is used in the present paper to formulate a linear implicit model that relates wind states and rotor loads. Simulations are run in both uniform and turbulent winds, using a high-fidelity aeroservoleastic wind turbine model. Results demonstrate the ability of the proposed observer in detecting the horizontal and vertical wind misalignments, as well as the vertical and horizontal shears

Wind shear estimation and wake detection by rotor loads - First wind tunnel verification

The paper describes a simple method for detecting presence and location of a wake affecting a downstream wind turbine operating in a wind power plant. First, the local wind speed and shear experienced by the wind turbine are estimated by the use of rotor loads and other standard wind turbine response data. Then, a simple wake deficit model is used to determine the lateral position of the wake with respect to the affected rotor. The method is verified in a boundary layer wind tunnel using two instrumented scaled wind turbine models, demonstrating its effectiveness

Detection of rotor imbalance, including root cause, severity and location

This paper presents a new way of detecting imbalances on wind turbine rotors, by using a harmonic analysis of the rotor response in the fixed frame. The method is capable of distinguishing among different root causes of the imbalance. In addition, the imbalance severity and location, i.e. the affected blade, can be identified. The automatic classification of the imbalance problem is obtained by using a neural network. The performance of the method is illustrated with the help of different fault scenarios, within a high-fidelity simulation environment

A new approach in the monitoring of the phytosanitary conditions of forests: the case of oak and beech stands in the Sicilian Regional Parks

L'obiettivo del presente studio è stato quello di esaminare lo stato fitosanitario delle quercete e faggete dei tre Parchi Regionali Siciliani (Parco dell'Etna, Parco delle Madonie, Parco dei Nebrodi). Lo studio è stato condotto individuando delle aree di saggio, popolamenti forestali omogenei sotto l'aspetto floristico, ecologico e fitosanitario. Complessivamente sono state delimitate 81 aree di saggio, di cui 54 quercete e 27 faggete. La condizione fitosanitaria di ogni essenza arborea all'interno della rispettiva area di saggio è stata espressa con un indice numerico denominato “classe fitosanitaria” (PC). I popolamenti di quercia hanno mostrato un elevato grado di sofferenza, con alberi sintomatici nell’85% delle aree di saggio. I popolamenti di faggio hanno mostrato una situazione di maggiore stabilità, ad eccezione delle faggete del parco dei Nebrodi che apparivano molto degradate. Sul genere Quercus, sono stati osservati sintomi di infezioni di patogeni fungini comuni nelle foreste delle aree temperate e Mediterranee, quali Biscogniauxia mediterranea, Polyporus sp., Fistulina hepatica, Mycrosphaera alphitoides ed Armillaria sp., mentre su faggio sono state osservate infezioni di Biscogniauxia nummularia, Fomes fomentarius e Neonectria radicicola. Sono state altresì individuate 22 aree che vengono proposte come aree di saggio permanenti dello stato fitosanitario delle foreste nei tre parchi.The objective of this study was to investigate the health conditions of oak and beech stands in the three Regional Parks of Sicily (Etna, Madonie and Nebrodi). A total of 81 sampling areas were investigated, 54 in oak stands and 27 in beech stands. The phytosanitary conditions of each tree within the respective sampling area was expressed with a synthetic index namely phytosanitary class (PC). Oak stands showed severe symptoms of decline, with 85% of the sampling areas including symptomatic trees. In general, beech stands were in better condition, with the exception of Nebrodi Park, where trees showed severe symptoms of decline. On oak trees, infections of fungal pathogens were also observed, including Biscogniauxia mediterranea, Polyporus sp., Fistulina hepatica, Mycrosphaera alphitoides and Armillaria sp. By contrast, on beech trees Biscogniauxia nummularia, Fomes fomentarius and Neonectria radicicola were recognized. Furthermore, twenty-two permanent sampling areas were delimited with the aim of monitoring regularly the health conditions of forests in these three parks