Validation of the dynamic wake meander model for loads and power production in the Egmond aan Zee wind farm

An Extended Pattern Search (EPS) method is developed to optimize the layout and turbine geometry for offshore floating wind power systems. The EPS combines a deterministic pattern search with stochastic extensions. Three advanced models are incorporated: (1) a cost model considering investment and lifetime costs of a floating offshore wind farm comprised of WindFloat platforms; (2) a wake propagation and interaction model able to determine the reduced wind speeds downstream of rotating blades; and (3) a power model to determine power produced at each rotor, and includes a semi-continuous, discrete turbine geometry selection to optimize the rotor radius and hub height of individual turbines. The objective function maximizes profit by minimizing cost, minimizing wake interactions, and maximizing power production. A multidirectional, multiple wind speed case is modeled which is representative of real wind site conditions. Layouts are optimized within a square solution space for optimal positioning and turbine geometry for farms containing a varying number of turbines. Resulting layouts are presented; optimized layouts are biased towards dominant wind directions. Preliminary results will inform developers of best practices to include in the design and installation of offshore floating wind farms, and of the resulting cost and power production of wind farms that are computationally optimized for realistic wind conditions.

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Field experiment for open-loop yaw-based wake steering at a commercial onshore wind farm in Italy

10.5194/wes-2020-80 ◽

2020 ◽

Author(s):

Bart M. Doekemeijer ◽

Stefan Kern ◽

Sivateja Maturu ◽

Stoyan Kanev ◽

Bastian Salbert ◽

...

Keyword(s):

Field Experiment ◽

Wind Farm ◽

Wind Farms ◽

Power Production ◽

Field Trials ◽

Open Loop ◽

Onshore Wind ◽

Power Maximization ◽

Energy Gains ◽

Turbine Arrays

Abstract. The concept of wake steering in wind farms for power maximization has gained significant popularity over the last decade. Recent field trials described in the literature demonstrate the real potential of wake steering on commercial wind farms, but also show that wake steering does not yet consistently lead to an increase in energy production for all inflow conditions. Moreover, a recent survey among experts shows that validation of the concept remains the largest barrier for adoption currently. In response, this article presents the results of a field experiment investigating wake steering in three-turbine arrays at an onshore wind farm in Italy. This experiment was performed as part of the European CL-Windcon project. The measurements show increases in power production of up to 35 % for two-turbine interactions and up to 16 % for three-turbine interactions. However, losses in power production are seen for various regions of wind directions too. In addition to the gains achieved through wake steering at downstream turbines, more interesting to note is that a significant share in gains are from the upstream turbines, showing an increased power production of the yawed turbine itself compared to baseline operation for some wind directions. Furthermore, the surrogate model, while capturing the general trends of wake interaction, lacks the details necessary to accurately represent the measurements. This article supports the notion that further research is necessary, notably on the topics of wind farm modeling and experiment design, before wake steering will lead to consistent energy gains in commercial wind farms.

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Comparison of Different Time Series Methods for Short-Term Forecasting of Wind Power Production

ASME 2010 4th International Conference on Energy Sustainability, Volume 2 ◽

10.1115/es2010-90270 ◽

2010 ◽

Cited By ~ 1

Author(s):

Gong Li ◽

Jing Shi

Keyword(s):

Wind Power ◽

Wind Farm ◽

Mean Squared Error ◽

Network Models ◽

Absolute Error ◽

Power Production ◽

Model Parameters ◽

Short Term ◽

Bp Network ◽

Persistence Model

Reliable short-term predictions of the wind power production are critical for both wind farm operations and power system management, where the time scales can vary in the order of several seconds, minutes, hours and days. This comprehensive study mainly aims to quantitatively evaluate and compare the performances of different Box & Jenkins models and backpropagation (BP) neural networks in forecasting the wind power production one-hour ahead. The data employed is the hourly power outputs of an N.E.G. Micon 900-kilowatt wind turbine, which is installed to the east of Valley City, North Dakota. For each type of Box & Jenkins models tested, the model parameters are estimated to determine the corresponding optimal models. For BP network models, different input layer sizes, hidden layer sizes, and learning rates are examined. The evaluation metrics are mean absolute error and root mean squared error. Besides, the persistence model is also employed for purpose of comparison. The results show that in general both best performing Box & Jenkins and BP models can provide better forecasts than the persistence model, while the difference between the Box & Jenkins and BP models is actually insignificant.

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A Study of the Impact of Pitch Misalignment on Wind Turbine Performance

Machines ◽

10.3390/machines7010008 ◽

2019 ◽

Vol 7 (1) ◽

pp. 8 ◽

Cited By ~ 6

Author(s):

Davide Astolfi

Keyword(s):

Wind Turbine ◽

Wind Turbines ◽

Power Output ◽

Wind Farm ◽

Reactive Power ◽

Power Production ◽

Test Case ◽

Before And After ◽

Input Variables ◽

The Impact

Pitch 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.

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Wind Farm Power Production Assessment: Introduction of a New Actuator Disc Method and Comparison with Existing Models in the Context of a Case Study

Applied Sciences ◽

10.3390/app9030431 ◽

2019 ◽

Vol 9 (3) ◽

pp. 431 ◽

Cited By ~ 2

Author(s):

Nikolaos Simisiroglou ◽

Heracles Polatidis ◽

Stefan Ivanell

Keyword(s):

Wind Farm ◽

Power Production ◽

Offshore Wind ◽

Offshore Wind Farm ◽

Actuator Disc ◽

Power Deficit ◽

The Given ◽

Method Show ◽

Do So

The aim of the present study is to perform a comparative analysis of two actuator disc methods (ACD) and two analytical wake models for wind farm power production assessment. To do so, wind turbine power production data from the Lillgrund offshore wind farm in Sweden is used. The measured power production for individual wind turbines is compared with results from simulations, done in the WindSim software, using two ACD methods (ACD (2008) and ACD (2016)) and two analytical wake models widely used within the wind industry (Jensen and Larsen wake models). It was found that the ACD (2016) method and the Larsen model outperform the other method and model in most cases. Furthermore, results from the ACD (2016) method show a clear improvement in the estimated power production in comparison to the ACD (2008) method. The Jensen method seems to overestimate the power deficit for all cases. The ACD (2016) method, despite its simplicity, can capture the power production within the given error margin although it tends to underestimate the power deficit.

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Design Analysis of Critical Concepts Influence Wind Farm Production and Efficiency

International Journal of Engineering Research in Africa ◽

10.4028/www.scientific.net/jera.40.136 ◽

2018 ◽

Vol 40 ◽

pp. 136-150

Author(s):

Naima Charhouni ◽

Mohammed Sallaou ◽

Khalifa Mansouri

Keyword(s):

Wind Turbines ◽

Wind Farm ◽

Production Efficiency ◽

Wind Farms ◽

Power Production ◽

Separation Distance ◽

Design Analysis ◽

Offshore Wind ◽

Farm Production ◽

Wind Farm Design

Wind farm deficiency caused by wake turbine interactions has received an important attention by scientific researchers in recent years. However the quality of power production is strongly depends on wind turbines location from others. In this regard, this paper proposes a comprehensive design analysis of crucial concepts that aid to plan for an efficient wind farm design. Indeed, the wake modeling problem is addressed in this analysis by comparing three models with available measured data gotten from literature. A configuration of wind turbines placement within the offshore wind farm as a function of separation distance is investigated in this study considering four wind farms layout. In addition to these elements, four rotor diameters size are evaluated as critical concept for wind turbine selection and production .The results obtained demonstrate that it is complicated to make a balance between three conflicted objectives related to the power production, efficiency and surface land area required for wind farm as a function of these crucial concepts.

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Wind Farm Loads under Wake Redirection Control

Energies ◽

10.3390/en13164088 ◽

2020 ◽

Vol 13 (16) ◽

pp. 4088

Author(s):

Stoyan Kanev ◽

Edwin Bot ◽

Jack Giles

Keyword(s):

Large Scale ◽

Wind Farm ◽

Wind Farms ◽

Power Production ◽

Power Gain ◽

Main Obstacle ◽

Depth Analysis ◽

Wake Effects ◽

Fatigue Loads ◽

Positive Effect

Active wake control (AWC) is a strategy for operating wind farms in such a way as to reduce the wake effects on the wind turbines, potentially increasing the overall power production. There are two concepts to AWC: induction control and wake redirection. The former strategy boils down to down-regulating the upstream turbines in order to increase the wind speed in their wakes. This has generally a positive effect on the turbine loading. The wake redirection concept, which relies on intentional yaw misalignment to move wakes away from downstream turbines, has a much more prominent impact and may lead to increased loading. Moreover, the turbines are typically not designed and certified to operate at large yaw misalignments. Even though the potential upsides in terms of power gain are very interesting, the risk for damage or downtime due to increased loading is seen as the main obstacle preventing large scale implementation of this technology. In order to provide good understanding on the impacts of AWC on the turbine loads, this paper presents the results from an in-depth analysis of the fatigue loads on the turbines of an existing wind farm. Even though for some wind turbine components the fatigue loads do increase for some wind conditions under yaw misalignment, it is demonstrated that the wake-induced loading decreases even more so that the lifetime loads under AWC are generally lower.

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