Wind models for simulation of power fluctuations from wind farms

Addressing short-term wind and wind turbine power fluctuations is fundamental in order to understand the nature of turbulence and of the mechanical loads to which wind turbines are subjected. This work is an experimental study of wind and power fluctuations at on onshore wind farm in Italy. Four wind turbines having 2 MW of rated power each are studied through time-resolved data. The sampling frequency is of the order of the Hz. This wind farm has been selected because there are two orders of magnitude of inter-turbine distance (3 and 7 rotor diameters) and therefore it is possible to study different levels of wake interactions recovery. The power curve at short time scales is studied and the inertia of the wind turbines, with respect to the wind fluctuations, is observed in the form of hysteresis of the power curve. Subsequently, the distribution of the wind and power variations is studied on several time scales and different features of the distributions are observed for downstream wind turbines with respect to upstream ones. The two-point statistics of power and wind-power is shown to be responsive to the wake regime to which wind turbines are subjected. This can suggest new approaches for wake control strategies.

2004

The thesis first presents the basics influences of wind power on the power system stability and quality by pointing out the main power quality issues of wind power in a small-scale case and following, the expected large-scale problems are introduced. Secondly, a dynamic wind turbine model that supports power quality assessment of wind turbines is presented. Thirdly, an aggregate wind farm model that support power quality and stability analysis from large wind farms is presented. The aggregate wind farm model includes the smoothing of the relative power fluctuation from a wind farm compared to a single wind turbine. Finally, applications of the aggregate wind farm model to the power systems are presented. The power quality and stability characteristics influenced by large-scale wind power are illustrated with three cases. In this thesis, special emphasis has been given to appropriate models to represent the wind acting on wind farms. The wind speed model to a single wind turbine includes turbulence and tower shadow effects from the wind and the rotational sampling turbulence due to the rotation of the blades. In a park scale, the wind speed model to the wind farm includes the spatial coherence between different wind turbines. Here the wind speed model is applied to a constant rotational speed wind turbine/farm, but the model is suitable to variable speed wind turbine/farm as well. The cases presented here illustrate the influences of the wind power on the power system quality and stability. The flicker and frequency deviations are the main power quality parameters presented. The power system stability concentrates on the voltage stability and on the power system oscillations. From the cases studied, voltage and the frequency variations were smaller than expected from the large-scale wind power integration due to the low spatial correlation of the wind speed. The voltage quality analysed in a Brazilian power system and in the Nordel power system from connecting large amount of wind power showed very small voltage variations. The frequency variations analysed from the Nordel showed also small variations in the frequency but it also showed that the wind turbines excites the power system in the electromechanical modes. Concerning the stability analysis, the study cases showed that large-scale wind power modifies the voltage stability of the power system and can cause power oscillations. It is showed here that the reactive power from the wind farms is the key factor on the voltage stability problem. During continuous operation, the distributed wind power variations did not give any problems to the power system stability concerning the power oscillations. v

7th International Workshop on Large Scale …, 2008

In this paper, the impact of the wind time variability and the spatial smoothing effect in mountainous complex terrains, usually taken as 1/sqrt(N) for fast fluctuations, is studied. The dimension of the regions, the type of electrical clustering of large numbers of wind turbines and the local meteorological effects are addressed and conclusions drawn on selected experimental case studies.

2001

A dynamic model of the wind farm Hagesholm has been imple-mented in the dedicated power system simulation program DIgSILENT. The wind farm consists of six 2MW NM2000/72 wind turbines from NEG-Micon. The model has been verified using simultaneous power ...

Wind Energy, 2018

An analytical model for the streamwise velocity space-time correlations in turbulent flows is derived and applied to the special case of velocity fluctuations in large wind farms. The model is based on the Kraichnan-Tennekes random sweeping hypothesis, capturing the decorrelation in time while including a mean wind velocity in the streamwise direction. In the resulting model, the streamwise velocity space-time correlation is expressed as a convolution of the pure space correlation with an analytical temporal decorrelation kernel. Hence, the spatio-temporal structure of velocity fluctuations in wind farms can be derived from the spatial correlations only. We then explore the applicability of the model to predict spatiotemporal correlations in turbulent flows in wind farms. Comparisons of the model with data from a large eddy simulation of flow in a large, spatially periodic wind farm are performed, where needed model parameters such as spatial and temporal integral scales and spatial correlations are determined from the large eddy simulation. Good agreement is obtained between the model and large eddy simulation data showing that spatial data may be used to model the full temporal structure of fluctuations in wind farms.

Power Systems, IEEE Transactions on, 2007

In this paper a wind park dynamic model is presented together with a base methodology for its application to power system studies. This detailed wind generation model addresses the wind turbine components and phenomena more relevant to characterize the power quality of a grid connected wind park, as well as the wind park response to the grid fast perturbations, e.g. low voltage ride through fault. The developed model was applied to the operating conditions of the selected sets of wind turbine experimental benchmark data from Azores and Alsvik wind parks, both for steady and transient operation of the grid. The results show a fairly good agreement in the relevant range of frequencies and indicate the model may be used as a tool for power system studies.

Every passing day wind energy becomes more indispensable part of power systems. So this increasing require the analysis of wind turbine impact on the grid. In this study, possible effect of wind turbine which is connected to Turkish distribution grid are analyzed. Distribution grid system is modeled with NEPLAN power system analysis simulator program. Finally, results are presented.

Electric Power Systems Research, 2010

In this paper, we develop a simulation procedure to generate realistic, synthetic wind speed variates for wind parks. These wind variates are defined by their marginal Weibull distributions and their auto-and cross-correlations only. In order to deal with these two types of correlation simultaneously, a vector autoregressive (VAR) model is used. Power output variates are obtained by applying the nonlinear turbine power curves to the correlated wind speed samples. The complete procedure is illustrated through a numerical example with a few turbines. A comparison is established between real wind time series from a wind park and synthetic wind variates simulated with similar, estimated underlying parameters.

European Wind Energy …, 2004

Dynamic models of wind farms for power system studies are at present not a standard feature of many software tools, but are being developed by research institutes, universities and commercial entities. Accurate dynamic wind farm models are critical; hence model validation is a key issue and taken up by IEA Wind R&D Annex 21. This international working group includes participants from nine countries, and has since start-up in 2002 developed a systematic approach for model benchmark testing. This paper present this methodology, including example benchmark test results, but also gives an overview of the various wind farm models now being available from both Annex partners and external entities.

2007 IEEE Lausanne Power Tech, 2007