Flexible non-linear predictive models for large-scale wind turbine diagnostics

Wind Energy ◽  
2016 ◽  
Vol 20 (5) ◽  
pp. 753-764 ◽  
Author(s):  
Martin Bach-Andersen ◽  
Bo Rømer-Odgaard ◽  
Ole Winther
2021 ◽  
Author(s):  
Norberto Sánchez-Cruz ◽  
Jose L. Medina-Franco

<p>Epigenetic targets are a significant focus for drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment of cancer and the increasing availability of chemogenomic data related to epigenetics. This data represents a large amount of structure-activity relationships that has not been exploited thus far for the development of predictive models to support medicinal chemistry efforts. Herein, we report the first large-scale study of 26318 compounds with a quantitative measure of biological activity for 55 protein targets with epigenetic activity. Through a systematic comparison of machine learning models trained on molecular fingerprints of different design, we built predictive models with high accuracy for the epigenetic target profiling of small molecules. The models were thoroughly validated showing mean precisions up to 0.952 for the epigenetic target prediction task. Our results indicate that the herein reported models have considerable potential to identify small molecules with epigenetic activity. Therefore, our results were implemented as freely accessible and easy-to-use web application.</p>


Author(s):  
Xu Pei-Zhen ◽  
Lu Yong-Geng ◽  
Cao Xi-Min

Background: Over the past few years, the subsynchronous oscillation (SSO) caused by the grid-connected wind farm had a bad influence on the stable operation of the system and has now become a bottleneck factor restricting the efficient utilization of wind power. How to mitigate and suppress the phenomenon of SSO of wind farms has become the focus of power system research. Methods: This paper first analyzes the SSO of different types of wind turbines, including squirrelcage induction generator based wind turbine (SCIG-WT), permanent magnet synchronous generator- based wind turbine (PMSG-WT), and doubly-fed induction generator based wind turbine (DFIG-WT). Then, the mechanisms of different types of SSO are proposed with the aim to better understand SSO in large-scale wind integrated power systems, and the main analytical methods suitable for studying the SSO of wind farms are summarized. Results: On the basis of results, using additional damping control suppression methods to solve SSO caused by the flexible power transmission devices and the wind turbine converter is recommended. Conclusion: The current development direction of the SSO of large-scale wind farm grid-connected systems is summarized and the current challenges and recommendations for future research and development are discussed.


2021 ◽  
Vol 13 (11) ◽  
pp. 2074
Author(s):  
Ryan R. Reisinger ◽  
Ari S. Friedlaender ◽  
Alexandre N. Zerbini ◽  
Daniel M. Palacios ◽  
Virginia Andrews-Goff ◽  
...  

Machine learning algorithms are often used to model and predict animal habitat selection—the relationships between animal occurrences and habitat characteristics. For broadly distributed species, habitat selection often varies among populations and regions; thus, it would seem preferable to fit region- or population-specific models of habitat selection for more accurate inference and prediction, rather than fitting large-scale models using pooled data. However, where the aim is to make range-wide predictions, including areas for which there are no existing data or models of habitat selection, how can regional models best be combined? We propose that ensemble approaches commonly used to combine different algorithms for a single region can be reframed, treating regional habitat selection models as the candidate models. By doing so, we can incorporate regional variation when fitting predictive models of animal habitat selection across large ranges. We test this approach using satellite telemetry data from 168 humpback whales across five geographic regions in the Southern Ocean. Using random forests, we fitted a large-scale model relating humpback whale locations, versus background locations, to 10 environmental covariates, and made a circumpolar prediction of humpback whale habitat selection. We also fitted five regional models, the predictions of which we used as input features for four ensemble approaches: an unweighted ensemble, an ensemble weighted by environmental similarity in each cell, stacked generalization, and a hybrid approach wherein the environmental covariates and regional predictions were used as input features in a new model. We tested the predictive performance of these approaches on an independent validation dataset of humpback whale sightings and whaling catches. These multiregional ensemble approaches resulted in models with higher predictive performance than the circumpolar naive model. These approaches can be used to incorporate regional variation in animal habitat selection when fitting range-wide predictive models using machine learning algorithms. This can yield more accurate predictions across regions or populations of animals that may show variation in habitat selection.


Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2287
Author(s):  
Kaina Qin ◽  
Shanshan Wang ◽  
Zhongjian Kang

With the rapid increase in the proportion of the installed wind power capacity in the total grid capacity, the state has put forward higher and higher requirements for wind power integration into the grid, among which the most difficult requirement is the zero-voltage ride through (ZVRT) capability of the wind turbine. When the voltage drops deeply, a series of transient processes, such as serious overvoltage, overcurrent, or speed rise, will occur in the motor, which will seriously endanger the safe operation of the wind turbine itself and its control system, and cause large-scale off-grid accident of wind generator. Therefore, it is of great significance to improve the uninterrupted operation ability of the wind turbine. Doubly fed induction generator (DFIG) can achieve the best wind energy tracking control in a wide range of wind speed and has the advantage of flexible power regulation. It is widely used at present, but it is sensitive to the grid voltage. In the current study, the DFIG is taken as the research object. The transient process of the DFIG during a fault is analyzed in detail. The mechanism of the rotor overcurrent and DC bus overvoltage of the DFIG during fault is studied. Additionally, the simulation model is built in DIgSILENT. The active crowbar hardware protection circuit is put into the rotor side of the wind turbine, and the extended state observer and terminal sliding mode control are added to the grid side converter control. Through the cooperative control technology, the rotor overcurrent and DC bus overvoltage can be suppressed to realize the zero-voltage ride-through of the doubly fed wind turbine, and ensure the safe and stable operation of the wind farm. Finally, the simulation results are presented to verify the theoretical analysis and the proposed control strategy.


Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3598
Author(s):  
Sara Russo ◽  
Pasquale Contestabile ◽  
Andrea Bardazzi ◽  
Elisa Leone ◽  
Gregorio Iglesias ◽  
...  

New large-scale laboratory data are presented on a physical model of a spar buoy wind turbine with angular motion of control surfaces implemented (pitch control). The peculiarity of this type of rotating blade represents an essential aspect when studying floating offshore wind structures. Experiments were designed specifically to compare different operational environmental conditions in terms of wave steepness and wind speed. Results discussed here were derived from an analysis of only a part of the whole dataset. Consistent with recent small-scale experiments, data clearly show that the waves contributed to most of the model motions and mooring loads. A significant nonlinear behavior for sway, roll and yaw has been detected, whereas an increase in the wave period makes the wind speed less influential for surge, heave and pitch. In general, as the steepness increases, the oscillations decrease. However, higher wind speed does not mean greater platform motions. Data also indicate a significant role of the blade rotation in the turbine thrust, nacelle dynamic forces and power in six degrees of freedom. Certain pairs of wind speed-wave steepness are particularly unfavorable, since the first harmonic of the rotor (coupled to the first wave harmonic) causes the thrust force to be larger than that in more energetic sea states. The experiments suggest that the inclusion of pitch-controlled, variable-speed blades in physical (and numerical) tests on such types of structures is crucial, highlighting the importance of pitch motion as an important design factor.


2014 ◽  
Vol 670-671 ◽  
pp. 964-967
Author(s):  
Shu Hua Bai ◽  
Hai Dong Yang

Nowadays, energy crisis is becoming increasingly serious. Coal, petroleum, natural gas and other fossil energy tend to be exhausted due to the crazy exploration. In recent decades, several long lasting local wars broke out in large scale in Mideast and North Africa because of the fighting for the limited petroleum. The reusable green energy in our life like enormous wind power, solar power, etc is to become the essential energy. This article is to conduct a comparative exploration of mini wind turbine, with the purpose of finding a good way to effectively deal with the energy crisis.


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