Generic Wind Turbine Research Articles

Evaluation of simple wind power forecasting methods applied to a long-term wind record from Scotland

We present an analysis of the ability to predict the power output from a nominal wind turbine or wind farm a few hours ahead using only locally available data – either the current and recent wind speed or power output. A third method combines the current state with knowledge of the long-term climatology. The wind speed data were taken from a 46-year long record of hourly readings at a Scottish coastal site and converted to power output and electricity production using a generic wind turbine power curve. The wind speed data or the calculated power output at a given time were used to predict the output a few hours ahead, either using persistence, a linear model, or a model based on the mean daily cycle extracted from the long-term record. Since many wind farm operators base their forecast on current wind speed or output measures alone, this analysis will provide some quantification of the quality of this approach, either to help them plan their operation or be able to put these simple methods in quantitative context of more complex methods.

Assessment of low‐frequency aeroacoustic emissions of a wind turbine under rapidly changing wind conditions based on an aero‐servo‐elastic CFD simulation

AbstractA meteorologically challenging situation that represents a demanding control task (rotational speed, pitch and yaw) for a wind turbine is presented and its implementation in a simulation is described. A high‐fidelity numerical process chain, consisting of the computational fluid dynamics (CFD) solver FLOWer, the multi‐body system (MBS) software SIMPACK and the Ffowcs Williams‐Hawkings code ACCO, is used. With it, the aerodynamic, servoelastic and aeroacoustic (<20 Hz) behaviour of a generic wind turbine during a meteorological event with strong and rapid changes in wind speed and direction is investigated. A precursor simulation with the meteorological model system PALM is deployed to generate realistic inflow data. The simulated strong controller response of the wind turbine and the resulting aeroelastic behaviour are analysed. Finally, the low‐frequency sound emissions are evaluated and the influence of the different operating and flow parameters during the variable inflow is assessed. It is observed that the wind speed and, linked to it, the rotational speed as well as the turbulence intensity are the main influencing factors for the emitted low‐frequency sound power of the wind turbine. Yawed inflow, on the other hand, has little effect unless it changes the operational mode to load reduction, resulting in a swap of the main emitter from the blades to the tower.

Impact of turbulent inflow and orography on the low-frequency noise sources of a wind turbine

A high-fidelity process chain is used to numerically investigate the low-frequency emissions from a generic wind turbine under turbulent inflow conditions. It consists of the Computational Fluid Dynamics (CFD) solver FLOWer, which is coupled to the multi-body simulation software SIMPACK to take unsteady aeroelastic effects into account. A realistic flow field for the complex terrain of Perdigão, Portugal is obtained by including the orography and vegetation in the simulation and using a precursor simulation with E-Wind to generate a site- and situation-specific inflow. The acoustic emissions are calculated with the Fflowcs-Williams-Hawkings (FW-H) acoustic solver ACCO. The simulations show that the tower emits noise caused by the blade-tower interaction (BTI) equally strong in all directions. To the sides of the turbine, this contribution is dominant, regardless of the turbulent inflow. The blades, on the other hand, emit significantly more noise under turbulent inflow, especially in streamwise direction, where they become the dominant source. The main noise mechanism here is the low-frequency part of the inflow turbulence (IT), followed by the BTI. The flow field in Perdigão causes additional large-scale variations in IT noise over time.

Extensive model validation for generic IEC 61400-27-1 wind turbine models

The aim of this paper is to demonstrate the usefulness, practical applicability, accuracy and reliability of Standard IEC 61400-27-1. The objective of this standard is to specify generic simulation models for the four main types of wind turbines, as well as procedures to validate them. Given that most of the works published and related to the validation of generic wind turbine models have applied a limited number of voltage dip tests to a single wind turbine, the present paper significantly widens the scope of these studies, conducting a total of 59 voltage dip field tests in 7 different wind turbines from 3 manufacturers. The Type 3 and Type 4 wind turbines, i.e., the doubly-fed and the full-scale converter wind turbines, respectively, are the two topologies analysed, since these comprise the vast majority of the market share for new wind turbines. The field measurements carried out on the actual wind turbines are compared to the simulation results of the corresponding IEC dynamic wind turbine models, and the IEC validation methodology is applied. Based on the results obtained, several comparative analyses are performed, and the reasons for differences in the accuracy of the behaviour of the wind turbine topologies considered are also analysed.

Modeling wind turbine-related greenhouse gas payback times in Europe at high spatial resolution

An important metric for quantifying the greenhouse gas saving potential of wind turbine types is the greenhouse gas payback time. Previous studies revealed that wind speed and wind turbine size are negatively correlated with greenhouse gas payback times. However, so far, payback times were mostly estimated for wind turbine types with a hub height of less than 100 m and rated power below 2000 kW at coarse spatial resolution. It is unclear if the negative correlation with turbine size continues to hold at greater heights since, in general, the change in wind speed increase reduces with higher altitude. Thus, the hypothesis that the size of more giant wind turbine types is not negatively correlated with greenhouse gas payback times was tested. The main goal was to develop a high spatial-resolution atlas of European greenhouse gas payback times considering the small-scale wind resource variability for 33 generic wind turbine types. The greenhouse gas payback times were estimated by first calculating the average monthly energy yields for the wind turbine types with hub heights from 60 to160 m and rated power from 800 to 4200 kW at a 250 m × 250 m spatial resolution grid. Secondly, the wind turbine types’ anticipated greenhouse gas emissions were estimated based on their hub height and rotor diameter. The wind turbine type-related net greenhouse gas emissions were compared with the mean emissions of a natural gas-fired power plant (0.5 kg CO2,eq/kWh). It was found that wind turbine types with rated power and hub height of {2400 kW, 60 m} and {3600 kW, 80 m} have the shortest greenhouse gas payback times. The European median greenhouse gas payback time was estimated at 6.1 months including the wind turbine types with lowest payback times. In the hub height range of 60 to 160 m, the correlation between greenhouse gas payback times and hub height was found to be significantly positive.

Life cycle greenhouse gas emission from wind farms in reference to turbine sizes and capacity factors

This study analyzes the global warming potential (GWP) of wind power plants within an LCA framework. Therefore, secondary data from studies on wind turbines, which were published in the past 20 years were assessed. The data was categorized into three configurations, i.e. onshore single turbines, onshore wind farms and offshore wind farms. Within a multivariate analysis, featuring a linear regression model approach, the datasets retrieved from the literature were evaluated. The effect variable was the specific GWP, normalized to the function unit gCO2-equ/kWh electricity. Cause variables were (i) the capacity factor, (ii) the rated power and (iii) the annual energy yield (AEY), (iv) the hub height and (v) the rotor diameter. In a secondary part this study showed the quantity of uncertainty, which is present in LCA studies on wind turbines by evaluating generic wind turbine configurations, which were present in the ecoinvent database. Conclusively, a sensitivity analysis on the influence of the capacity factor on the GWP was conducted.For onshore single turbines and wind farms a negative correlation was observed between the turbine size and the GWP. A highly significant negative correlation was found between the AEY and the GWP. However, the AEY needed to be log-transformed first. Other cause variables were either collinear to the AEY or showed a weak correlation. For offshore wind turbines similar results could not be presented and none of the cause variable could explain the effect variable. The sample size was however low, as only few studies were conducted for offshore plants.The uncertainty analysis showed that generally low uncertainties are present during the modelling phase of the LCA of wind turbines, which suggests that the processes are well understood and documented. The sensitivity analysis on the capacity factor resulted in a non-linear, hyperbolic progression with respect to the GWP.

Spatio-temporal fusion neural network for multi-class fault diagnosis of wind turbines based on SCADA data

Abstract Numerous sensors have been deployed in different locations in components of wind turbines to continuously monitor the health status of the turbine system and accordingly, generate a large volume of operation data by the supervisory control and data acquisition (SCADA) system. Naturally, these sensory data are multivariate time series with high spatio-temporal correlations. It is still challenging to effectively model such correlations and then enable an accurate fault diagnosis. To this end, we proposed a new spatio-temporal fusion neural network (STFNN) for wind turbine fault diagnosis. Specifically, a multi-kernel fusion convolution neural network (MKFCNN) with multiple convolution kernels of different sizes is first designed to extract multi-scale spatial correlations among different variables. Then, we adopt the long short-term memory (LSTM) to further learn the temporal dependence of the learned spatial features. The proposed STFNN model provides an end-to-end fault diagnosis way, which can directly learn spatio-temporal dependency from the raw SCADA data and give the fault diagnosis result. The effectiveness and superiority of the proposed method are evaluated on a generic wind turbine benchmark simulation dataset and a SCADA dataset from a real wind farm. Both experimental results have indicated that the proposed method outperformed several compared methods.

A Multiscale Spatio-Temporal Convolutional Deep Belief Network for Sensor Fault Detection of Wind Turbine.

Sensor fault detection of wind turbines plays an important role in improving the reliability and stable operation of turbines. The supervisory control and data acquisition (SCADA) system of a wind turbine provides promising insights into sensor fault detection due to the accessibility of the data and the abundance of sensor information. However, SCADA data are essentially multivariate time series with inherent spatio-temporal correlation characteristics, which has not been well considered in the existing wind turbine fault detection research. This paper proposes a novel classification-based fault detection method for wind turbine sensors. To better capture the spatio-temporal characteristics hidden in SCADA data, a multiscale spatio-temporal convolutional deep belief network (MSTCDBN) was developed to perform feature learning and classification to fulfill the sensor fault detection. A major superiority of the proposed method is that it can not only learn the spatial correlation information between several different variables but also capture the temporal characteristics of each variable. Furthermore, this method with multiscale learning capability can excavate interactive characteristics between variables at different scales of filters. A generic wind turbine benchmark model was used to evaluate the proposed approach. The comparative results demonstrate that the proposed method can significantly enhance the fault detection performance.

Fault transient response of generic Type 3 wind turbine models: Limitations and extension of the validation methodology

Generic wind turbine (WT) models have amply demonstrated their capabilities for power system stability studies. These models, developed by the IEC and the WECC, can adapt their behavior to any actual WT with the adjustment of a limited number of parameters and reduced computational time. However, these generic models present certain limitations, especially during transient periods when a voltage dip begins and ends, the emulation of which is addressed differently by each guideline (IEC and WECC). The current validation methodology, proposed by the same IEC Standard that defines their models, dismisses transient periods for validation purposes, which involves a considerable information loss. In order to overcome this limitation, the current work studies in detail the consequences of the different modeling guidelines in transient emulation by comparing the response of the IEC and WECC models with field data obtained from a real Type 3 WT. To this end, six test cases performed with different voltage dips characteristics and loads on the real Type 3 WT are used. Furthermore, an extension of the current validation methodology to transient periods, which are currently neglected, is proposed in the present work.

An Update to the National Renewable Energy Laboratory Baseline Wind Turbine Controller

The National Renewable Energy Laboratory’s 5-MW wind turbine model is well established as an industry standard and is often used as a comparison model, or a model on which to build upon. Though effective, the legacy controller for the 5-MW wind turbine uses a simple algorithm that is not up to date with many industry standards. Additionally, as the research community has advanced into fast-paced development cycles, as systems engineering tools such as Wind-Plant Integrated System Design & Engineering Model (WISDEM ®) [1] are employed, and as a greater focus on controls co-design practices is encouraged, demand for a generic wind turbine controller has arisen. This work presents updates for the NREL 5-MW controller to a more modern control architecture, and establishes a generic tuning framework that can be easily adapted to various wind turbines. Based on initial results, the updated generic controller eases the automatic tuning process while maintaining or improving the performance of the legacy NREL 5-MW controller.

Improved Generic Model of Variable Speed Wind Turbines for Dynamic Studies

Fast growth of wind power generation and its contribution in power systems dynamic performance has highlighted the importance of developing generic models for wind turbines. Following the former efforts, an enhanced version of standard generic wind turbine model is proposed in this article. The enhancements are aimed to make the model applicable for unbalanced Root Mean Square (RMS), short-term frequency stability, and low-voltage ride-through (LVRT) studies. Moreover, fidelity of the overall responses of the model is increased. To achieve these goals, five new blocks are designed and added to the base model and three existing blocks are modified. The new blocks are negative-sequence generator/converter model, inertial controller, LVRT controller, dc-link and the Line Side Converter (LSC), and the natural flux models. Responses of the enhanced model are compared with the results of both the base model and a detailed model, and validity of the proposed model is verified by different transient scenarios.

Field validation of a standard Type 3 wind turbine model implemented in DIgSILENT-PowerFactory following IEC 61400-27-1 guidelines

Transient stability analyses are one of the key tools used to ensure grid stability and safeguard security of electricity supply, as well as to comply with different countries grid interconnection agreements. Transmission and distribution system operators require validated wind turbine models to perform these studies. This is becoming increasingly important in current power systems because wind energy penetration is constantly expanding, and its integration has a significant impact on power grid planning and operation. The definition of generic wind turbine models by international standard IEC 61400-27-1, first released in February 2015, aims to deal with this issue. Therefore, since the validation process of the most widely used model defined by this standard and one of the most technically advanced, the generic type 3 wind turbine, i.e., the doubly-fed induction generator, has only been conducted using non-specialised software tools in the field of electrical engineering, the present paper addresses the validation process of this WT when simulated in one of the leading electric power system analysis software tools: DIgSILENT-PowerFactory. The model is subjected to voltage dips of varying magnitude and duration, under both full and partial load conditions. The results are compared to field measurement data according to IEC 61400-27-1 guidelines, and validation errors are estimated.

Fault-Ride Trough Validation of IEC 61400-27-1 Type 3 and Type 4 Models of Different Wind Turbine Manufacturers

The participation of wind power in the energy mix of current power systems is progressively increasing, with variable-speed wind turbines being the leading technology in recent years. In this line, dynamic models of wind turbines able to emulate their response against grid disturbances, such as voltage dips, are required. To address this issue, the International Electronic Commission (IEC) 61400-27-1, published in 2015, defined four generic models of wind turbines for transient stability analysis. To achieve a widespread use of these generic wind turbine models, validations with field data are required. This paper performs the validation of three generic IEC 61400-27-1 variable-speed wind turbine model topologies (type 3A, type 3B and type 4A). The validation is implemented by comparing simulation results with voltage dip measurements performed on six different commercial wind turbines based on field campaigns conducted by three wind turbine manufacturers. Both IEC validation approaches, the play-back and the full system simulation, were implemented. The results show that the generic full-scale converter topology is accurately adjusted to the different real wind turbines and, hence, manufacturers are encouraged to the develop generic IEC models.

Implementation of IEC 61400-27-1 Type 3 Model: Performance Analysis under Different Modeling Approaches

Forecasts for 2023 position wind energy as the third-largest renewable energy source in the world. This rapid growth brings with it the need to conduct transient stability studies to plan network operation activities and analyze the integration of wind power into the grid, where generic wind turbine models have emerged as the optimal solution. In this study, the generic Type 3 wind turbine model developed by Standard IEC 61400-27-1 was submitted to two voltage dips and implemented in two simulation tools: MATLAB/Simulink and DIgSILENT-PowerFactory. Since the Standard states that the responses of the models are independent of the software used, the active and reactive power results of both responses were compared following the IEC validation guidelines, finding, nevertheless, slight differences dependent on the specific features of each simulation software. The behavior of the generic models was assessed, and their responses were also compared with field measurements of an actual wind turbine in operation. Validation errors calculated were comprehensively analyzed, and the differences in the implementation processes of both software tools are highlighted. The outcomes obtained help to further establish the limitations of the generic wind turbine models, thus achieving a more widespread use of Standard IEC 61400-27-1.

Field Validation of Generic Type 4 Wind Turbine Models Based on IEC and WECC Guidelines

The generic wind turbine models developed in recent years by the International Electrotechnical Commission (IEC) and the Western Electricity Coordinated Council (WECC) are intended to meet the needs of public, standard, and relatively simple (small number of parameters and computational requirements) wind turbine and wind farm models used to conduct transient stability analysis. Moreover, the full-scale converter wind turbine technology referred to as Type 4 by IEC and WECC, is increasingly used in current power systems due to its control benefits. Hence, the development of this generic model has become a priority. This study presents the validation of two generic Type 4 wind turbine models, which have been developed in accordance with the IEC and WECC guidelines, respectively. Field data collected from a real wind turbine located in a Spanish wind farm was used to validate both generic Type 4 wind turbine models following the IEC validation guidelines. Ten different test cases are considered, varying not only the depth and duration of the faults but also the load of the wind turbine. The parameters of the models were kept constant for all the simulation cases, aiming to evaluate the accuracy of the models when facing different voltage dips.

Development and assessment of second generation WTG models in an open source platform

Currently, there is a substantial demand for mathematical models of wind power generators in power system simulation tools. This can be explained by two factors: (i) wind now contributes a significant part of the power produced in different power systems around the world; (ii) one requirement to design an intelligent renewable power infrastructure is to rely on accurate and open models to simulate the different components of an electric power system (EPS). This article presents the development and implementation of second-generation generic wind turbine generators (WTGs) models in the Power System Toolbox (PST)—open source software for power system transient simulation. The evaluation of these models is performed using simulation studies on two test systems: a single machine infinite bus (SMIB) system, and the IEEE 68-Bus system. Transient stability and small signal analysis are performed using Type-3 and Type-4 wind turbines models to assess the performance of such models.

Compliance of a Generic Type 3 WT Model with the Spanish Grid Code

The expansion of wind power around the world poses a new challenge that network operators must overcome, namely the integration of this renewable energy source into the grid. Comprehensive analyses involving time-domain simulations must be carried out to plan network operation and ensure power supply. In light of the above, and with the aim of extending the use of the wind turbine models developed by Standard IEC 61400-27-1 and assessing their performance according to national grid code requirements, an IEC Type 3 wind turbine model has been submitted for the first time to Spanish grid code PO 12.3. Indeed, there is a lack of studies submitting generic wind turbine models to national grid code requirements. The model’s behavior is compared with field measurements of an actual Gamesa G52 machine and with its detailed simulation model. The outcomes obtained have been comprehensively analyzed and the results of the validation criteria highlight that several modeling modifications, in the cases of non-compliance, must be implemented in the IEC-developed Type 3 model in order to comply with PO 12.3. Nevertheless, the results also show that when the transformer inrush current is not considered, the reactive power response of the generic Type 3 WT model meets the validation criteria, thus complying with Spanish PO 12.3.

Exploring technologically, temporally and geographically-sensitive life cycle inventories for wind turbines: A parameterized model for Denmark

In life cycle assessments of wind turbines and, more generally, of Renewable Energy Systems (RES), environmental impacts are usually normalized by electricity production to express their performance per kilowatt-hour. For most RES, manufacture and installation dominate the impacts. Hence, results are sensitive to parameters governing both impacting phases and electricity production. Most available studies present the environmental performance of generic wind turbines with assumed fixed values for sensitive parameters (e.g. electricity production) that often vary between studies and fail to reflect specificities of wind farm projects. This study presents an approach to build a comprehensive parameterized model that generates unique wind turbine life cycle inventories conditioned by technologically, temporally and geographically-sensitive parameters. This approach allows for the characterization of the carbon footprint of five sets of turbines in Denmark, where wind power is highly developed. The analysis shows disparities even between turbines of similar power output, mostly explained by the service time, load factor and components weights but also by background processes (evolution of electricity mix and recycled steel content). Project-specific inventories with technologically, temporally and geographically-sensitive parameters are essential for supporting RES development projects. Such inventories are especially important to evaluate highly-renewable electricity mixes, such as that of Denmark.

Simulation of transient gusts on the NREL 5 MW wind turbine using the URANS solver THETA

Abstract. A procedure to propagate longitudinal transient gusts through a flow field by using the resolved-gust approach is implemented in the URANS solver THETA. Both the gust strike of a 1−cos⁡() gust and an extreme operating gust following the IEC 61400-1 standard are investigated on the generic NREL 5 MW wind turbine at rated operating conditions. The impact of both gusts on pressure distributions, rotor thrust, rotor torque, and flow states on the blade are examined and quantified. The flow states on the rotor blade before the gust strike at maximum and minimum gust velocity are compared. An increased blade loading is detectable in the pressure coefficients and integrated blade loads. The friction force coefficients indicate the dynamic separation and re-attachment of the flow during the gust. Moreover, a verification of the method is performed by comparing the rotor torque during the extreme operating gust to results of FAST rotor code.

Dynamic modeling of wind turbines. Experimental tuning of a multibody model

This work is part of a research project funded by the Italian Ministry of the University and Research (MIUR), under the call for "National Interest Research Projects 2015 (PRIN 2015)", titled "Smart Optimized Fault Tolerant WIND turbines (SOFTWIND)".Within this project, the research unit of the University of Perugia (UniPG) aims to develop dynamic modeling and simulation methodologies and fatigue behavior evaluation ones for wind turbine as a whole. The development of these methodologies will be aimed at predicting the life of generic wind turbines, also providing important and fundamental parameters for optimizing their control, aimed at reducing the failures of these machines.In the present paper, a small turbine, developed at the Department of Engineering of the University of Perugia, will be analyzed. The multibody modeling technique adopted and the experimental activity conducted in the wind tunnel of UniPG, needed for the tuning of the model, will be described.The analysis of both model behavior and experimental data has allowed for the definition of a robust multibody modeling technique that adopts a freeware code (NREL - FAST), universally considered to be a reference in this field.The goodness of the model guarantees the capabilities of the simulation environment to analyze the real load scenario and the fatigue behavior of this kind of device.