Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting

Wind power time series usually show complex dynamics mainly due to non-linearities related to the wind physics and the power transformation process in wind farms. This article provides an approach to the incorporation of observed local variables (wind speed and direction) to model some of these effects by means of statistical models. To this end, a benchmarking between two different families of varying-coefficient models (regime-switching and conditional parametric models) is carried out. The case of the offshore wind farm of Horns Rev in Denmark has been considered. The analysis is focused on one-step ahead forecasting and a time series resolution of 10 min. It has been found that the local wind direction contributes to model some features of the prevailing winds, such as the impact of the wind direction on the wind variability, whereas the non-linearities related to the power transformation process can be introduced by considering the local wind speed. In both cases, conditional parametric models showed a better performance than the one achieved by the regime-switching strategy. The results attained reinforce the idea that each explanatory variable allows the modelling of different underlying effects in the dynamics of wind power time series.

Comparing linear and non linear wind flow models

Assessing wind conditions on complex terrain has become a hard task as terrain complexity increases. That is why there is a need to extrapolate in a reliable manner some wind parameters that determine wind farms viability such as annual average wind speed at all hub heights as well as turbulence intensities. The development of these tasks began in the early 90´s with the widely used linear model WAsP and WAsP Engineering especially designed for simple terrain with remarkable results on them but not so good on complex orographies. Simultaneously non-linearized Navier Stokes solvers have been rapidly developed in the last decade through CFD (Computational Fluid Dynamics) codes allowing simulating atmospheric boundary layer flows over steep complex terrain more accurately reducing uncertainties. This paper describes the features of these models by validating them through meteorological masts installed in a highly complex terrain. The study compares the results of the mentioned models in terms of wind speed and turbulence intensity.

RANS simulations of wind flow at the Bolund experiment

As part of their development, the predictions of numerical wind flow models must be compared with measurements in order to estimate the uncertainty related to their use. Of course, the most rigorous such comparison is under blind conditions. The following paper includes a detailed description of three different wind flow models, all based on a Reynolds-averaged Navier-Stokes approach and two-equation k-ε closure, that were tested as part of the Bolund blind comparison (itself based on the Bolund experiment which measured the wind around a small coastal island). The models are evaluated in terms of predicted normalized wind speed and turbulent kinetic energy at 2 m and 5 m above ground level for a westerly wind direction. Results show that all models predict the mean velocity reasonably well; however accurate prediction of the turbulent kinetic energy remains achallenge.

Experimental and numerical study of wind flow behind windbreaks

The shelter effect of a windbreak protects aggregate piles and provides a reduction of particle emissions in harbours. RANS (Reynolds-averaged Navier–Stokes equations) simulations using three variants of k–ε (standard k–ε, RNG k–ε and realizable k–ε) turbulence closure models have been performed to analyse wind flow characteristics behind an isolated fence located on a flat surface without roughness elements. The performance of the three turbulence models has been assessed by wind tunnel experiments. Cases of fences with different porosities (φ) have been evaluated using wind tunnel experiments as well as numerical simulations. The aim is to determine an optimum porosity for sheltering effect of an isolated windbreak. A value of 0.35 was found as the optimum value among the studied porosities (φ=0, 0.1, 0.24, 0.35, 0.4, 0.5).

Quantifying the impacts of urban wind sheltering on the building energy consumption

Common building energy modeling approaches do not account for the influence of surrounding neighborhood on the energy consumption patterns. This thesis develops a framework to quantify the neighborhood impact on a building energy consumption based on the local wind flow. The airflow in the neighborhood is predicted using Computational Fluid Dynamics (CFD) in eight principal wind directions. The developed framework in this study benefits from wind multipliers to adjust the wind velocity encountering the target building. The input weather data transfers the adjusted wind velocities to the building energy model. In a case study, the CFD method is validated by comparing with on-site temperature measurements, and the building energy model is calibrated using utilities data. A comparison between using the adjusted and original weather data shows that the building energy consumption and air system heat gain decreased by 5% and 37%, respectively, while the cooling gain increased by 4% annually.

A method to correct the flow distortion of offshore wind data using CFD simulation and experimental wind tunnel tests

The assessment of wind energy resource for the development of deep offshore wind plants requires the use of every possible source of data and, in many cases, includes data gathered at meteorological stations installed at islands, islets or even oil platforms—all structures that interfere with, and change, the flow characteristics. This work aims to contribute to the evaluation of such changes in the flow by developing a correction methodology and applying it to the case of Berlenga island, Portugal. The study is performed using computational fluid dynamic simulations (CFD) validated by wind tunnel tests. In order to simulate the incoming offshore flow with CFD models a wind profile, unknown a priori, was established using observations from two coastal wind stations and a power law wind profile was fitted to the existing data (a=0.165). The results show that the resulting horizontal wind speed at 80 m above sea level is 16% lower than the wind speed at 80 m above the island for the dominant wind direction sector.

The impact of urban wind environments on natural ventilation

The aim of this paper is to illustrate the impact of urban wind environments when assessing the availability of natural ventilation. A numerical study of urban airflow for a complex of five building blocks located at the University of Reading, UK is presented. The computational fluid dynamics software package ANSYS was used to simulate six typical cases of urban wind environments and the potential for natural ventilation assessed. The study highlights the impact of three typical architectural forms (street canyons, semi-enclosures and courtyards) on the local wind environment. Simulation results have also been compared with experimental data collected from six locations on the building complex. The study demonstrates that ventilation strategies formed using regional weather data, may have a propensity to over-estimate the potential for natural ventilation and cooling, due to the impact of urban form which creates a unique microclimate. Characteristics of urban wind flow patterns are presented as a guideline and can be used to assess the design and performance of natural or hybrid ventilation and the opportunity for passive cooling.

Examination of wind storms over Central Europe with respect to circulation weather types and NAO phases

The occurrence of wind storms in Central Europe is investigated with respect to large-scale atmospheric flow and local wind speeds in the investigation area. Two different methods of storm identification are applied for Central Europe as the target region: one based on characteristics of large-scale flow (circulation weather types, CWT) and the other on the occurrence of extreme wind speeds. The identified events are examined with respect to the NAO phases and CWTs under which they occur. Pressure patterns, wind speeds and cyclone tracks are investigated for storms assigned to different CWTs. Investigations are based on ERA40 reanalysis data. It is shown that about 80% of the storm days in Central Europe are connected with westerly flow and that Central European storm events primarily occur during a moderately positive NAO phase, while strongly positive NAO phases (6.4% of all days) account for more than 20% of the storms. A storm occurs over Central Europe during about 10% of the days with a strong positive NAO index. The most frequent pathway of cyclone systems associated with storms over Central Europe leads from the North Atlantic over the British Isles, North Sea and southern Scandinavia into the Baltic Sea. The mean intensity of the systems typically reaches its maximum near the British Isles. Differences between the characteristics for storms identified from the CWT identification procedure (gale days, based on MSLP fields) and those from extreme winds at Central European grid points are small, even though only 70% of the storm days agree. While most storms occur during westerly flow situations, specific characteristics of storms during the other CWTs are also considered. Copyright © 2009 Royal Meteorological Society

A pragmatic Bayesian approach to wind field retrieval

The ERS-1 Satellite was launched in July 1991 by the European Space Agency into a polar orbit at about 800 km, carrying a C-band scatterometer. A scatterometer measures the amount of backscatter microwave radiation reflected by small ripples on the ocean surface induced by sea-surface winds, and so provides instantaneous snap-shots of wind flow over large areas of the ocean surface, known as wind fields. Inherent in the physics of the observation process is an ambiguity in wind direction; the scatterometer cannot distinguish if the wind is blowing toward or away from the sensor device. This ambiguity implies that there is a one-to-many mapping between scatterometer data and wind direction. Current operational methods for wind field retrieval are based on the retrieval of wind vectors from satellite scatterometer data, followed by a disambiguation and filtering process that is reliant on numerical weather prediction models. The wind vectors are retrieved by the local inversion of a forward model, mapping scatterometer observations to wind vectors, and minimising a cost function in scatterometer measurement space. This thesis applies a pragmatic Bayesian solution to the problem. The likelihood is a combination of conditional probability distributions for the local wind vectors given the scatterometer data. The prior distribution is a vector Gaussian process that provides the geophysical consistency for the wind field. The wind vectors are retrieved directly from the scatterometer data by using mixture density networks, a principled method to model multi-modal conditional probability density functions. The complexity of the mapping and the structure of the conditional probability density function are investigated. A hybrid mixture density network, that incorporates the knowledge that the conditional probability distribution of the observation process is predominantly bi-modal, is developed. The optimal model, which generalises across a swathe of scatterometer readings, is better on key performance measures than the current operational model. Wind field retrieval is approached from three perspectives. The first is a non-autonomous method that confirms the validity of the model by retrieving the correct wind field 99% of the time from a test set of 575 wind fields. The second technique takes the maximum a posteriori probability wind field retrieved from the posterior distribution as the prediction. For the third technique, Markov Chain Monte Carlo (MCMC) techniques were employed to estimate the mass associated with significant modes of the posterior distribution, and make predictions based on the mode with the greatest mass associated with it. General methods for sampling from multi-modal distributions were benchmarked against a specific MCMC transition kernel designed for this problem. It was shown that the general methods were unsuitable for this application due to computational expense. On a test set of 100 wind fields the MAP estimate correctly retrieved 72 wind fields, whilst the sampling method correctly retrieved 73 wind fields.

Hydrodynamics of the Itapocu river and the Barra Velha lagoon estuarine system, SC, Brazil

A hydrodynamic characterization of the Itapocu river and Barra Velha lagoon estuarine system was carried out with the objective of evaluating how the current regime in this area is affected by astronomical and meteorological tides and the river discharge. Meteorological, water level and current velocity and direction data were gathered hourly during a twenty-day period, from 22-July until 10-August, 2004. Current meters were positioned at the inlet, at the entrance of the north and south lagoons and at the lower estuary of the river along with a tide gauge. The estuarine system showed distinct current behavior among the different sectors within the estuary, responding to the different forcings. The strongest currents were observed at the inlet while the weakest values were observed at the northern lagoon, a location that showed little dynamic. The general flow was ebb-dominated flux, in response to fluvial discharge, even during local wind water set-up event.

A sensitivity study of the WRF model in wind simulation for an area of high wind energy

The performance of the Weather Research and Forecast (WRF) model in wind simulation was evaluated under different numerical and physical options for an area of Portugal, located in complex terrain and characterized by its significant wind energy resource. The grid nudging and integration time of the simulations were the tested numerical options. Since the goal is to simulate the near-surface wind, the physical parameterization schemes regarding the boundary layer were the ones under evaluation. Also, the influences of the local terrain complexity and simulation domain resolution on the model results were also studied. Data from three wind measuring stations located within the chosen area were compared with the model results, in terms of Root Mean Square Error, Standard Deviation Error and Bias. Wind speed histograms, occurrences and energy wind roses were also used for model evaluation. Globally, the model accurately reproduced the local wind regime, despite a significant underestimation of the wind speed. The wind direction is reasonably simulated by the model especially in wind regimes where there is a clear dominant sector, but in the presence of low wind speeds the characterization of the wind direction (observed and simulated) is very subjective and led to higher deviations between simulations and observations. Within the tested options, results show that the use of grid nudging in simulations that should not exceed an integration time of 2 days is the best numerical configuration, and the parameterization set composed by the physical schemes MM5–Yonsei University–Noah are the most suitable for this site. Results were poorer in sites with higher terrain complexity, mainly due to limitations of the terrain data supplied to the model. The increase of the simulation domain resolution alone is not enough to significantly improve the model performance. Results suggest that error minimization in the wind simulation can be achieved by testing and choosing a suitable numerical and physical configuration for the region of interest together with the use of high resolution terrain data, if available.

Analysis of Forest Effects in Wind Farm Performance

The objective of the thesis is to analyze the behaviour of the wind flow when it is passing beside the forest. To complete this analysis, a parametric study was done based upon generalized situations. Some abacus have been made, which are related to forest and wind characteristics. The abacus were compared with a particular real case, namely Alexandrovo (Bulgaria), where it was concluded that the applicability of the abacus in projects with complex terrain is low and they must be used, from a quantitative point of view, for flat terrain, being hc the most important parameter.

Genetic clusters and sex-biased gene flow in a unicolonial Formica ant.

BACKGROUND: Animal societies are diverse, ranging from small family-based groups to extraordinarily large social networks in which many unrelated individuals interact. At the extreme of this continuum, some ant species form unicolonial populations in which workers and queens can move among multiple interconnected nests without eliciting aggression. Although unicoloniality has been mostly studied in invasive ants, it also occurs in some native non-invasive species. Unicoloniality is commonly associated with very high queen number, which may result in levels of relatedness among nestmates being so low as to raise the question of the maintenance of altruism by kin selection in such systems. However, the actual relatedness among cooperating individuals critically depends on effective dispersal and the ensuing pattern of genetic structuring. In order to better understand the evolution of unicoloniality in native non-invasive ants, we investigated the fine-scale population genetic structure and gene flow in three unicolonial populations of the wood ant F. paralugubris. RESULTS: The analysis of geo-referenced microsatellite genotypes and mitochondrial haplotypes revealed the presence of cryptic clusters of genetically-differentiated nests in the three populations of F. paralugubris. Because of this spatial genetic heterogeneity, members of the same clusters were moderately but significantly related. The comparison of nuclear (microsatellite) and mitochondrial differentiation indicated that effective gene flow was male-biased in all populations. CONCLUSION: The three unicolonial populations exhibited male-biased and mostly local gene flow. The high number of queens per nest, exchanges among neighbouring nests and restricted long-distance gene flow resulted in large clusters of genetically similar nests. The positive relatedness among clustermates suggests that kin selection may still contribute to the maintenance of altruism in unicolonial populations if competition occurs among clusters.