1,721,046 research outputs found
A Study of the Impact of Pitch Misalignment on Wind Turbine Performance
No full textPitch angle control is the most common means of adjusting the torque of wind turbines. The verification of its correct function and the optimization of its control are therefore very important for improving the efficiency of wind kinetic energy conversion. On these grounds, this work is devoted to studying the impact of pitch misalignment on wind turbine power production. A test case wind farm sited onshore, featuring five multi-megawatt wind turbines, was studied. On one wind turbine on the farm, a maximum pitch imbalance between the blades of 4.5 ° was detected; therefore, there was an intervention for recalibration. Operational data were available for assessing production improvement after the intervention. Due to the non-stationary conditions to which wind turbines are subjected, this is generally a non-trivial problem. In this work, a general method was formulated for studying this kind of problem: it is based on the study, before and after the upgrade, of the residuals between the measured power output and a reliable model of the power output itself. A careful formulation of the model is therefore crucial: in this work, an automatic feature selection algorithm based on stepwise multivariate regression was adopted, and it allows identification of the most meaningful input variables for a multivariate linear model whose target is the power of the wind turbine whose pitch has been recalibrated. This method can be useful, in general, for the study of wind turbine power upgrades, which have been recently spreading in the wind energy industry, and for the monitoring of wind turbine performances. For the test case of interest, the power of the recalibrated wind turbine is modeled as a linear function of the active and reactive power of the nearby wind turbines, and it is estimated that, after the intervention, the pitch recalibration provided a 5.5% improvement in the power production below rated power. Wind turbine practitioners, in general, should pay considerable attention to the pitch imbalance, because it increases loads and affects the residue lifetime; in particular, the results of this study indicate that severe pitch misalignment can heavily impact power production
Mathematical methods for SCADA data mining of onshore wind farms: Performance evaluation and wake analysis
No full textSupervisory control and data acquisition (SCADA) systems have become widely diffuse in modern wind energy technology. The slowdown of new installations and the increasing percentage of energy entering the grid from renewable stochastic sources has diverted attention to the careful optimization of operating farms. Elaborating the complex data stream from SCADA systems into knowledge poses technological and scientific challenges. SCADA data analysis therefore lies at the crossroads of mechanical engineering, applied mathematics, statistics and physics. In the present work, mathematical methods are proposed for tackling the complexity of SCADA data. This idea is to elaborate simplified and more powerful data sets through one action: discretization of continuous quantities. The approach is employed for two very different issues: performance evaluation and wake effects analysis, which is investigated from the point of view of power losses, due to the difficulties associated with optimal turbine alignment with the wind. Two indexes for performance evaluation are formulated. Recurrent non-trivial orientation patterns of clusters of turbines are individuated, and the efficiency associated to them is analyzed. The methods are tested on two wind farms situated in southern Italy
Fault diagnosis of wind turbine gearboxes through temperature and vibration data
No full textGearbox faults are one of the most common and severe causes of energy losses in large wind turbine technology. Further, degradation of gearboxes is an elusive phenomenon by the point of view of diagnostics. Yet, nowadays the widespread diffusion of Supervisory Control And Data Acquisition (SCADA) control systems is a keystone for fault prevention. It is desirable to conjugate accuracy of the outputs with intuitiveness and reasonable computational cost. The present work deals with these issues: some methods are proposed for data mining of SCADA gearbox temperature and vibration measurements. In particular, a model based on Artificial Neural Networks (ANN) is proposed and its performances are compared against similar approaches in the literature. It arises that vibration analysis at the time scale of SCADA data is not effective for fault diagnosis, even if powered by the artificial intelligence of the ANN, while the proposed ANN model for gearbox temperatures is useful for early fault diagnosis. The method is tested on the data sets of a wind farm in southern Italy and it is shown that it is useful for the diagnosis of incoming faults to three out of nine wind turbines of the site
Fault diagnosis of wind turbine gearboxes through temperature and vibration data
No full textGearbox faults are one of the most common and severe causes of energy losses in large wind turbine technology. Further, degradation of gearboxes is an elusive phenomenon by the point of view of diagnostics. Yet, nowadays the widespread diffusion of Supervisory Control And Data Acquisition (SCADA) control systems is a keystone for fault prevention. It is desirable to conjugate accuracy of the outputs with intuitiveness and reasonable computational cost. The present work deals with these issues: some methods are proposed for data mining of SCADA gearbox temperature and vibration measurements. In particular, a model based on Artificial Neural Networks (ANN) is proposed and its performances are compared against similar approaches in the literature. It arises that vibration analysis at the time scale of SCADA data is not effective for fault diagnosis, even if powered by the artificial intelligence of the ANN, while the proposed ANN model for gearbox temperatures is useful for early fault diagnosis. The method is tested on the data sets of a wind farm in southern Italy and it is shown that it is useful for the diagnosis of incoming faults to three out of nine wind turbines of the site
Definition and interpretation of wind farm efficiency in complex terrain: A discussion
No full textThe exploitation of wind turbines in complex terrain has recently been growing. The comprehension of wind flow, especially in the downstream area, is by itself a challenging task in complex terrain: Even more so, it is difficult to account for the mixing between terrain effects and the wake interactions between nearby turbines. Efficiency is one of the simplest and meaningful metrics for quantifying the impact of wakes on wind farm production, but its definition is well established basically only for offshore wind farms. In this work, the definition of wind farm efficiency is, therefore, discussed, based on the critical points arising in complex terrain, where there can be at the same time a considerable variation of free wind flow along the layout and a directional distortion of the wakes, induced by the terrain. In this work, operational data of a test case wind farm sited in a very complex terrain, featuring 17 multimegawatt wind turbines, are elaborated and inspire a discussion and a novel definition of efficiency, that restores in the complex terrain case the meaning of the efficiency
FAULT PREVENTION AND DIAGNOSIS THROUGH SCADA TEMPERATURE DATA ANALYSIS OF AN ONSHORE WIND FARM
No full textWind turbines, due to the distribution of the source, are an energy conversion system having low density on the territory, whose operational behaviour and production on the short term strongly depends on the stochastic nature of wind. They therefore need accurate assessment prior installation and careful condition monitoring in the operative phase. In the present work, smart post processing of Supervisory Control And Data Acquisition (SCADA) control system data sets is employed for fault prevention and diagnosis through the analysis of the temperatures of the machines. Automatic routines are developed for monitoring the evolution of all the temperature SCADA channels against power production. The methods are tested on an onshore wind farm sited in southern Italy, where nine turbines with 2 MW rated power are installed. The tests are performed both ex post and in real time: it is shown that in the former case, a major mechanical problem is detected, and in the latter case a significant problem to the cooling system is identified before compromising turbine functionality
Wind Turbine Power Curve Upgrades: Part II
No full textWind turbine power upgrades have recently become a debated topic in wind energy research. Their assessment poses some challenges and calls for devoted techniques: some reasons are the stochastic nature of the wind and the multivariate dependency of wind turbine power. In this work, two test cases were studied. The former is the yaw management optimization on a 2 MW wind turbine; the latter is a comprehensive control upgrade (pitch, yaw, and cut-out) for 850 kW wind turbines. The upgrade impact was estimated by analyzing the difference between the post-upgrade power and a data-driven simulation of the power if the upgrade did not take place. Therefore, a reliable model for the pre-upgrade power of the wind turbines of interest was needed and, in this work, a principal component regression was employed. The yaw control optimization was shown to provide a 1.3% of production improvement and the control re-powering provided 2.5%. Another qualifying point was that, for the 850 kW wind turbine re-powering, the data quality was sufficient for an upgrade estimate based on power curve analysis and a good agreement with the model result was obtained. Summarizing, evidence of the profitability of wind turbine power upgrades was collected and data-driven methods were elaborated for power upgrade assessment and, in general, for wind turbine performance control and monitoring
Combined Heat and Power Plant and District Heating and Cooling Network: A Test-Case in Italy with Integration of Renewable Energy
No full textThe 2012 European energy efficiency directive supported the development of cogeneration combined heat and power (CHP) and district heating and cooling (DHC) networks, stressing the benefits of a more efficient energy supply, the exploitation of recovered heat, and renewable resources, in terms of fuel consumption and avoided costs/emissions. Policy decisions play a crucial role: technical and environmental feasibility of CHP is clear and well demonstrated, whereas economic issues (fuel prices, incentives, etc.) may influence its actual application. In this framework, the introduction of low-carbon technologies and the exploitation of renewable energies are profitable interventions to be applied on existing plants. This work focuses on a small CHP plant, installed in the 90 s and located within a research facility in Italy, designed to supply electricity and heat/cool through a district network. On the basis of monitored consumption of electricity, heating, and cooling, energy fluxes have been analyzed and an assessment was performed to get a management profile enhancing both operational and economic parameters. The integration of renewable energies, i.e., solar-powered systems for supporting the existing devices, has been evaluated, thus resulting in a hybrid trigeneration plant. Results demonstrate how the useful synergy between CHP and DHC can not only be profitable from the economic point of view, but it can also create conditions to considerably boost the integral deployment of primary energy sources, improving fuel diversity and then facing the challenge of climate change toward sustainable energy networks in the future
Numerical and experimental methods for wake analysis in complex terrains
No full textThe assessment of power output quality of wind farms operating in complex terrains is extremely challenging. Complex terrains actually provide a very difficult testing ground, which stresses to the limit techniques that are well established for the offshore case. Actual turbine performances are the result of the intertwining of complex wind flow, wake effects and control system response to these non-trivial phenomena. On these grounds, the present work aims at a numerical and experimental investigation of a wind farm sited in Italy on a very complex terrain. This test case is particularly valuable because the terrain is very steep, with high slopes (up to 60%) even nearby the turbines; also the layout is complex and large. In the present work, a subcluster of turbines is analysed: they represent an interesting testing ground of wake interactions and terrain effects, because of the slopes in their proximity, of the inter-turbine distance of around 2.5 rotor diameters, and of the orientation of the cluster with respect to the most frequent wind direction distribution. For these reasons, a numerical and experimental analysis of this subcluster is performed, through Computational Fluid Dynamics (CFD) techniques on one side, and SCADA data analysis on the other side. Particular attention is devoted to the effects of complex flow on machine capability of optimally following meandering wind direction. It is shown that modeling the free flow is not enough to capture the trend of wind intensity and direction and, in particular, the combination of wakes and terrain effects is fundamental, in order to encode the main features of the directional behaviour of the turbines
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