-There are a multitude of studies completed and ongoing related to the cost of wind integration. However, the results are not easy to compare. An international forum for exchange of knowledge of power system impacts of wind power has been formed under the IEA Implementing Agreement on Wind Energy. IEA WIND R&D Task 25 on "Design and Operation of Power Systems with Large Amounts of Wind Power" produced a state-of-the-art report in October 2007, where the most relevant wind-power grid integration studies were analyzed, especially regarding methodologies and input data. This paper summarizes the results from 18 case studies, with discussion on differences in methodology as well as issues that have been identified to impact the cost of wind integration.Index Terms -grid integration, wind power, power system operation, reserve requirements.

This paper gives an evaluation of most of the commonly used models for predicting wind speed decrease (wake) downstream of a wind turbine. The evaluation is based on six experiments where free-stream and wake wind speed profiles were measured using a ship-mounted sodar at a small offshore wind farm. The experiments were conducted at varying distances between 1.7 and 7.4 rotor diameters downstream of the wind turbine. Evaluation of the models compares the predicted and observed velocity deficits at hub height. A new method of evaluation based on determining the cumulative momentum deficit over the profiles is described. Despite the apparent simplicity of the experiments, the models give a wide range of predictions. Overall, it is not possible to establish any of the models as having individually superior performance with respect to the measurements.

The economic feasibility of offshore wind power utilisation depends on the favourable wind conditions offshore as compared to sites on land. The higher wind speeds have to compensate the additional cost of offshore developments. However, not only the mean wind speed is different, but the whole flow regime, as can e.g. be seen in the vertical wind speed profile. The commonly used models to describe this profile have been developed mainly for land sites. Their applicability for wind power prediction at offshore sites is investigated using data from the measurement program Rødsand, located in the Danish Baltic Sea.Monin-Obukhov theory is often used for the description of the wind speed profile.From a given wind speed at one height, the profile is predicted using two parameters, Obukhov length and sea surface roughness. Different methods to estimate these parameters are discussed and compared. Significant deviations to Monin-Obukhov theory are found for near-neutral and stable conditions when warmer air is advected from land with a fetch of more than 30 km. The measured wind shear is larger than predicted.As a test application, the wind speed measured at 10 m height is extrapolated to 50 m height and the power production of a wind turbine at this height is predicted with the different models. The predicted wind speed is compared to the measured one and the predicted power output to the one using the measured wind speed. To be able to quantify the importance of the deviations from Monin-Obukhov theory, a simple correction method to account for this effect has been developed and is tested in the same way. 2IIVKRUH ZLQG UHVRXUFH /DQJH HW DO page 3 of 64The models for the estimation of the sea surface roughness were found to lead only to small differences. For the purpose of wind resource assessment even the assumption of a constant roughness was found to be sufficient. The different methods used to derive the Obukhov length L were found to differ significantly for near-neutral and stable atmospheric stratification. Here again the simplest method using only bulk measurements was found to be sufficient.For situations with near-neutral and stable atmospheric stratification and long (>30 km) fetch, the wind speed increase with height is larger than what is predicted from Monin-Obukhov theory for all methods to estimate L and z 0 . It is also found that this deviation occurs at wind speeds important for wind power utilisation, mainly at 5-9 ms -1 .The power output estimation has also been compared with the method of the resource estimation program WAsP. For the Rødsand data set the prediction error of WAsP is about 4%. For the extrapolation with Monin-Obukhov theory with different L and z 0 estimations it is 5-9%. The simple wind profile correction method, which has been developed, leads to a clear improvement of the wind speed and power output predictions. When the correction is applied, the error reduces to 2-5%.

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In this study, two different approaches to estimate the wind resource over the German Bight in the North Sea are compared: the mesoscale meteorological model MM5 and the wind resource assessment program WAsP. The dynamics of the atmosphere of the year 2004 was simulated with the MM5 model, with input from the NCEP global model, without directly utilizing measurement data. WAsP estimations were calculated on the basis of six measurement stations: three on islands, two offshore and one onshore. The annual mean wind speed at onshore, offshore and island sites is estimated by both models. The predictions are compared both with each other and with measured data. A spatial comparison of the wind resource calculated by the two models is made by means of a geographical information system. The results show that the accuracy of the WAsP predictions depends mainly on the measurement station used as input. Small differences are shown in the estimations performed by the three island stations, despite the large geographical distance between them. Compared with the measurements of the offshore sites, they seem to be suitable for estimating the offshore wind resource from measurements on land. The two offshore stations show differences when predicting each other's mean wind speed with the WAsP method, while the MM5 calculations show a similar deviation for both sites. The largest differences between the two models are found at distances of 5–50km from the coast. While in WAsP the increase occurs in the first 10km from the coast, MM5 models an increase due to coastal effects for at least 50km.  Copyright © 2006 John Wiley &Sons, Ltd.