Using temperature and state transitions to forecast wind speed

A major issue in forecasting wind speed is non‐linear variability. The probability distribution of wind speed series shows heavy tails, while there are frequent state transitions, in which wind speed changes by large magnitudes, over relatively short time periods. These so‐called large ramp events are one of the critical issues currently facing the wind energy community. Two forecasting algorithms are analyzed here. The first is a regression on lags, including temperature as a causal factor, with time‐varying parameters. The second augments the first using state transition terms. The main innovation in state transition models is that the cumulative density function from regressions on the states is used as a right‐hand side variable in the regressions for wind speed. These two methods are tested against a persistence forecast and several non‐linear models, using eight hourly wind speed series. On average, these two models produce the best results. The state transition model improves slightly over the regression. However, the improvement achieved by both models relative to the persistence forecast is fairly small. These results argue that there are limits to the accuracy that can be achieved in forecasting wind speed data. Copyright © 2007 John Wiley & Sons, Ltd.     

An estimation of the enhanced geothermal systems potential for the Iberian Peninsula

An estimation of the Enhanced Geothermal System's theoretical technical potential for the Iberian Peninsula is presented in this work. As a first step, the temperature at different depths (from 3500 m to 9500 m, in 1000 m steps) has been estimated from existing heat flow, temperature at 1000 m and temperature at 2000 m depth data. From the obtained temperature-at-depth data, an evaluation of the available heat stored for each 1 km thick layer between 3 and 10 km depth, under some limiting hypotheses, has been made. Results are presented as the net electrical power that could be installed, considering that the available thermal energy stored is extracted during a 30 year project life. The results are presented globally for the Iberian Peninsula and separately for Portugal (continental Portugal), Spain (continental Spain plus the Balearic Islands) and for each one of the administrative regions included in the study. Nearly 6% of the surface of the Iberian Peninsula, at a depth of 3500 m has a temperature higher than 150 °C. This surface increases to more than 50% at 5500 m depth, and more than 90% at 7500 m depth. The Enhanced Geothermal System's theoretical technical potential in the Iberian Peninsula, up to a 10 km depth (3 km–10 km) and for temperatures above 150 °C, expressed as potential installed electrical power, is as high as 700 GW_e, which is more than 5 times today's total electricity capacity installed in the Iberian Peninsula (renewable, conventional thermal and nuclear).     

Regime‐switching models and multiple causal factors in forecasting wind speed

This study evaluates two types of models for wind speed forecasting. The first is models with multiple causal factors, such as offsite readings of wind speed and meteorological variables. These can be estimated using either regressions or neural networks. The second is state transition and the closely related class of regime‐switching transition models. These are attractive in that they can be used to predict outlying fluctuations or large ramp events. The regime‐switching model uses a persistence forecast during periods of high wind speed, and regressions for low and intermediate speeds. These techniques are tested on three databases. Two main criteria are used to evaluate the outcomes, the number of high and low states than can be predicted correctly and the mean absolute percent error of the forecast. Neural nets are found to predict the state transitions somewhat better than logistic regressions, although the regressions do not do badly. Three methods all achieve about the same degree of forecast accuracy: multivariate regressions, state transition and regime‐switching models. If the states could be predicted perfectly, the regime‐switching model would improve forecast accuracy by an additional 2.5 to 3 percentage points. Analysis of the density functions of wind speed and the forecasting models finds that the regime‐switching method more closely approximates the distribution of the actual data. Copyright © 2009 John Wiley & Sons, Ltd.     

Simulating climate change and its effects on the wind energy resource of Ireland

We consider the impact of climate change on the wind energy resource of Ireland using an ensemble of Regional Climate Model (RCM) simulations. The RCM dynamically downscales the coarse information provided by the Global Climate Models (GCMs) and provides high resolution information, on a subdomain covering Ireland. The RCM used in this work is the Rossby Center's RCM (RCA3). The RCA3 model is evaluated by performing simulations of the past Irish climate, driven by European Center for Medium‐Range Weather Forecasts ERA‐40 data, and by comparing the output to observations. Results confirm that the output of the RCA3 model exhibits reasonable and realistic features as documented in the historical wind data record. For the investigation of the influence of the future climate under different climate scenarios, the Max Plank Institute's GCM, European Center Hamburg Model, is used to drive the RCA3 model. Simulations are run for a control period 1961‐2000 and future period 2021‐2060. The future climate was simulated using the four Intergovernmental Panel on Climate Change emission scenarios A1B, A2, B1 and B2. The results for the downscaled simulations show a substantial overall increase in the energy content of the wind for the future winter months and a decrease during the summer months. The projected changes for summer and winter were found to be statistically significant over most of Ireland. However, the projected changes should be viewed with caution since the climate change signal is of similar magnitude to the variability of the evaluation and control simulations. Copyright © 2011 John Wiley & Sons, Ltd.     

风力发电系统中组合风速的建模及仿真

在实验室进行风力发电系统模拟,风速模拟是其中重要的一个环节,正确的风速模型不仅可以反应风速实际变化情况,而且能给风力发电系统的模拟研究提供准确的参数。文章采用4分量组合风速模型,用Matlab/Simulink对组合风速进行建模仿真。仿真结果表明,该数学模型能够较精确地反映风速的实际突变性、渐变性及随机性等特点,适用于风力发电系统的模拟研究工作。     

Modeling of the dynamics of wind to power conversion including high wind speed behavior

This paper proposes and validates an efficient, generic and computationally simple dynamic model for the conversion of the wind speed at hub height into the electrical power by a wind turbine. This proposed wind turbine model was developed as a first step to simulate wind power time series for power system studies. This paper focuses on describing and validating the single wind turbine model, and is therefore neither describing wind speed modeling nor aggregation of contributions from a whole wind farm or a power system area. The state‐of‐the‐art is to use static power curves for the purpose of power system studies, but the idea of the proposed wind turbine model is to include the main dynamic effects in order to have a better representation of the fluctuations in the output power and of the fast power ramping especially because of high wind speed shutdowns of the wind turbine. The high wind speed shutdowns and restarts are represented as on–off switching rules that govern the output of the wind turbine at extreme wind speed conditions. The model uses the concept of equivalent wind speed, estimated from the single point (hub height) wind speed using a second‐order dynamic filter that is derived from an admittance function. The equivalent wind speed is a representation of the averaging of the wind speeds over the wind turbine rotor plane and is used as input to the static power curve to get the output power. The proposed wind turbine model is validated for the whole operating range using measurements available from the DONG Energy offshore wind farm Horns Rev 2. Copyright © 2015 John Wiley & Sons, Ltd.     

Restructuring and generation of electrical energy in the Iberian Peninsula

Portugal and Spain are on the threshold of the creation of an Iberian electricity market. In order to help its development, the power of the electric interconnection between the countries has been increased and market mechanisms designed to resolve congestion, should it arise. A system of joint supply for the Iberian Peninsula will lead to single price for the whole area except at times when the interconnection is saturated, in which case prices will be somewhat higher in the importing zone. In the medium term, the hope is that both systems will have very similar generating equipment and that their variable costs will equalize due to the substitution of the most obsolete equipment with combined cycle power stations, and to the increase of exchange capacity. The coming into effect of this market will bring about improvements in the security and efficiency of supply in both countries. There will also be some obstacles to overcome, such as, for example, the current regulatory frame deficiencies on power generation, the contacts which exist at present in Portugal between the producers and the National Electricity Network, the asymmetry of the distribution channels in each country, the differences in rates and the limited capacity for exchange.     

Simulating the future wind energy resource of Ireland using the COSMO‐CLM model

We consider the impact of climate change on the wind energy resource of Ireland using an ensemble of regional climate model (RCM) simulations. The RCM used in this work is the Consortium for Small‐scale Modelling–climate limited‐area modelling (COSMO‐CLM) model. The COSMO‐CLM model was evaluated by performing simulations of the past Irish climate, driven by European Centre for Medium‐Range Weather Forecasts ERA‐40 data, and comparing the output with observations. For the investigation of the influence of the future climate under different climate scenarios, the Max Planck Institute's global climate model, ECHAM5, was used to drive the COSMO‐CLM model. Simulations are run for a control period 1961–2000 and future period 2021–2060. To add to the number of ensemble members, the control and future simulations were driven by different realizations of the ECHAM5 data. The future climate was simulated using the Intergovernmental Panel on Climate Change emission scenarios, A1B and B1. The research was undertaken to consolidate, and as a continuation of, similar research using the Rossby Centre's RCA3 RCM to investigate the effects of climate change on the future wind energy resource of Ireland. The COSMO‐CLM projections outlined in this study agree with the RCA3 projections, with both showing substantial increases in 60 m wind speed over Ireland during winter and decreases during summer. The projected changes of both studies were found to be statistically significant over most of Ireland. The agreement of the COSMO‐CLM and RCA3 simulation results increases our confidence in the robustness of the projections. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluating the impact of wind induced roughness change and tidal range on extrapolation of offshore vertical wind speed profiles

Wind energy resource estimation frequently requires extrapolation of wind speeds from typical measurement heights to turbine hub‐heights. However, this extrapolation is uncertain, and this uncertainty is exacerbated in the offshore environment by the effect of the dynamic surface (i.e. surface roughness and height respond to wind speed or vary over time). This paper examines the impact of roughness variations and small tidal ranges on mean predicted wind speeds in near‐neutral conditions. Roughness variations offshore are in the range 0.002 and 0.00002 m. This range of roughnesses gives a difference in predicted wind speed extrapolated from 10 to 50 m of less than 8%. For a more typical range of 0.0005 tp 0.00005 m, the difference will be smaller (～3%). With a tidal range of 4 m the difference in mean wind speed extrapolated from 10 to 50 m height is about 1%. Copyright © 2001 John Wiley & Sons, Ltd.     

Copula-based joint distribution analysis of wind speed and wind direction: Wind energy development for Hong Kong

Accurate and reliable assessment of wind energy potential has important implication to the wind energy industry. Most previous studies on wind energy assessment focused solely on wind speed, whereas the dependence of wind energy on wind direction was much less considered and documented. In this paper, a copula-based method is proposed to better characterize the direction-related wind energy potential at six typical sites in Hong Kong. The joint probability density function (JPDF) of wind speed and wind direction is constructed by a series of copula models. It shows that Frank copula has the best performance to fit the JPDF at hilltop and offshore sites while Gumbel copula outperforms other models at urban sites. The derived JPDFs are applied to estimate the direction-related wind power density at the considered sites. The obtained maximum direction-related wind energy density varies from 41.3 W/m² at an urban site to 507.9 W/m² at a hilltop site. These outcomes are expected to facilitate accurate micro-site selection of wind turbines, thereby improving the economic benefits of wind farms in Hong Kong. Meanwhile, the developed copula-based method provides useful references for further investigations regarding direction-related wind energy assessments at various terrain regions. Notably, the proposed copula-based method can also be applied to characterize the direction-related wind energy potential somewhere other than Hong Kong.     

Projected changes in wind speed and its energy potential in China using a high‐resolution regional climate model

Following its commitment to Paris Agreement in 2015, China has started to explore potential renewable energy solutions with low carbon emissions to mitigate global warming. Though wind energy is one of the most cost‐effective solutions and has been favored for climate policy development around the world, its high sensitivity to climate change raises some critical issues for the long‐term effectiveness in providing sustainable energy supply. Particularly, how wind speed and its energy potential in China will change in the context of global warming is still not well understood. In this paper, we simulate the near‐surface wind speed over China using the PRECIS regional climate modeling system under different RCP emission scenarios for assessing the possible changes in wind speed and wind energy availability over China throughout the 21^st century. Overall, the PRECIS model can reasonably reproduce the mesoscale climatological near‐surface wind speed and directions as documented in reanalysis data across most regions of China, while some local discrepancies are reported in the southwestern regions. In the future, the annual mean wind speed would be decreasing in most regions of China, except for a slightly increase in the southeast. The expected changes in wind speed are characterized with different amplitudes and rates under different RCP emission scenarios. The changes in the spatial distribution of wind speed seem to be sensitive for RCP climate emission scenarios, especially in the late 21^st century. The spatiotemporal changes in wind energy potential exhibit a similar behavior to those in near‐surface wind speed, but the magnitudes of these changes are larger. In general, the wind power density is expected to increase by over 5% in winter in the major wind fields in China (ie, Northwest, Northcentral and Northeast), while significant decreases (by about 6% on average) are projected for other seasons (ie, spring, summer and autumn). By contrast, the wind energy potential in the northeast would increase over most months in the year, especially in winter and summer. The results of this research are of great importance for understanding where and to what extent the wind energy can be utilized to contribute renewable energy system development in China in support of its long‐term climate change mitigation commitment.     

风电场代表年风速计算方法的分析

在对风电场进行风资源评估时,常采用气象站与测风塔的相关关系,将现场测风数据订正为一套反映风电场长期平均水平的代表性数据进行风资源分析,而对代表年风速订正是否合理是影响风资源评估误差的重要因素。文章以内蒙古地区某风电场风资源分析为例,探讨采用常规方法和改进方法对代表年风速的订正所产生的误差情况,结果表明,通过改进方法进行修正得到的代表年平均风速的变化规律与气象站多年的变化规律一致,此方法弥补了常规方法中的一些不确定因素对代表年修正结果的影响,减小了误差范围。     

The influence of the wind speed profile on wind turbine performance measurements

To identify the influence of wind shear and turbulence on wind turbine performance, flat terrain wind profiles are analysed up to a height of 160 m. The profiles' shapes are found to extend from no shear to high wind shear, and on many occasions, local maxima within the profiles are also observed. Assuming a certain turbine hub height, the profiles with hub‐height wind speeds between 6 m s^?1 and 8 m s^?1 are normalized at 7 m s^?1 and grouped to a number of mean shear profiles. The energy in the profiles varies considerably for the same hub‐height wind speed. These profiles are then used as input to a Blade Element Momentum model that simulates the Siemens 3.6 MW wind turbine. The analysis is carried out as time series simulations where the electrical power is the primary characterization parameter. The results of the simulations indicate that wind speed measurements at different heights over the swept rotor area would allow the determination of the electrical power as a function of an ‘equivalent wind speed’ where wind shear and turbulence intensity are taken into account. Electrical power is found to correlate significantly better to the equivalent wind speed than to the single point hub‐height wind speed. Copyright © 2008 John Wiley & Sons, Ltd.     

Evaluation of SAR wind retrieval algorithms in offshore areas of the Korean Peninsula

The method of extracting offshore wind field from SAR satellite images for offshore wind resource assessment shows some discrepancies in the calculated wind speed depending on which of the CMOD algorithms is used. This paper compared different algorithms, such as CMOD_IFR2, CMOD4, CMOD5, in order to find the suitable CMOD algorithm for the southern offshore area of the Korean Peninsula, which belongs to the zone influenced by the archipelago, by calculating the relative errors with reference to the Korea wind map of representative weather days by season. The result is that CMOD-IFR2 shows a tendency towards excessive estimation of wind speed, while CMOD4 shows the lowest RMSE values of wind speed differences with respect to the Korea wind map. Based on this result, we have concluded that, for the southern offshore area of the Korean Peninsula which belongs to the medium-range wind speed zone, CMOD4 is the suitable algorithm.     

Low wind speed turbines and wind power potential in Minnesota, USA

Wind power development in Minnesota largely has been focused in the “windy” southwestern part of the state. This research evaluates the additional power that potentially could be generated via low wind speed turbines, particularly for areas of the state where there has been comparatively little wind energy investment. Data consist of 3 years (2002–2004) of wind speed measurements at 70–75 m above ground level, at four sites representing the range of wind speed regimes (Classes 2–5) found in Minnesota. Power estimates use three configurations of the General Electric 1.5-MW series turbine that vary in rotor diameter and in cut-in, cut-out, and rated speeds. Results show that lower cut-in, cut-out, and rated speeds, and especially the larger rotor diameters, yield increases of 15–30% in wind power potential at these sites. Gains are largest at low wind speed (Class 2) sites and during the summer months at all four sites. Total annual wind power at each site shows some year-to-year variability, with peaks at some sites partially compensating for lulls at others. Such compensation does not occur equally in all years: when large-scale atmospheric circulation patterns are strong (e.g., 2002), the four sites show similar patterns of above- and below-average wind power, somewhat reducing the ability of geographic dispersion to mitigate the effects of wind speed variability.     

Stochastic generation of hourly mean wind speed data

Use of wind speed data is of great importance in civil engineering, especially in structural and coastal engineering applications. Synthetic data generation techniques are used in practice for cases where long wind speed data are required. In this study, a new wind speed data generation scheme based upon wavelet transformation is introduced and compared to the existing wind speed generation methods namely normal and Weibull distributed independent random numbers, the first- and second-order autoregressive models, and the first-order Markov chain. Results propose the wavelet-based approach as a wind speed data generation scheme to alternate the existing methods.     

风道式风力发电机迎风及调速方法

为降低风道式风力发电机的成本,提出了一种风力发电机迎风及调速方法。在风道装置始终正对风向的条件下,由于偏心机构和凸轮机构的共同作用,在风速低时,风轮正对着风向,在风速超限时,风轮相应侧偏,以限制风轮转速。基于空气动力学基本理论,推导出其结构参数的表达式,并叙述了各结构参数的选取原则。该方法可有效地起到大风限速的作用,提高风力发电机工作的稳定性。该调速机构结构简单、成本低,安装维护方便。     

Operation and coordinated control of fixed and variable speed wind farms

This paper will describe the possibilities of coordinated control and management for different wind farm concepts to guarantee that operational set points of active and reactive power, specified by the Spanish transmission system operator (TSO), are reached. This coordinated control has been designed and implemented by a hierarchical and robust control structured from a central control level to each wind farm control board and finally to an individual wind turbine level. This article will demonstrate that both technologies, fixed and variable speed based wind farms can contribute to power and voltage control. In particular, this paper will deal with the use of under-load tap changing transformers in the point of common coupling of the wind farm with the grid, and the reactive power compensation by means of convectional mechanical switched capacitors enhancing the integration of the fixed speed wind farms in the power system.     

Low wind speed events: persistence and frequency

Over the last decades, wind energy industry has been growing with an increasing rate. This is highly relevant to the need of new wind farm site selection with certain standards such as high wind potential and accessibility. Even in windy areas, low wind speed persistence can be characterized as an extreme (non‐frequent) atmospheric condition for the electricity network as it can lead to low or no energy production. The current work is focused on the estimation of the duration and the frequency of occurrence of low wind speed events using the principles of extreme value theory. The two methods used are the ‘intensity given duration’ and the ‘duration given intensity’ that lead to the same point from different perspectives. The data used is derived from a 10 year, hindcast, high‐resolution database developed by the Atmospheric Modeling and Weather Forecasting Group of the University of Athens. The great potential and multinational interest concerning energy applications in the North Sea has led to its selection as a study area. The outcome of the study includes the development of intensity–duration–frequency curves as well as a comparison between the two methodologies adopted. Based on these, the largest period of no energy production for a preselected probability of occurrence is estimated for the area of interest. The results of this work could be potentially supportive for studying the regional climatology. Such information can be included in risk assessment techniques and can be applied among others for energy activities. Copyright © 2017 John Wiley & Sons, Ltd.     

Estimation of turbulence intensity using rotor effective wind speed in Lillgrund and Horns Rev-I offshore wind farms

Turbulence characteristics of the wind farm inflow have a significant impact on the energy production and the lifetime of a wind farm. The common approach is to use the meteorological mast measurements to estimate the turbulence intensity (TI) but they are not always available and the turbulence varies over the extent of the wind farm. This paper describes a method to estimate the TI at individual turbine locations by using the rotor effective wind speed calculated via high frequency turbine data.The method is applied to Lillgrund and Horns Rev-I offshore wind farms and the results are compared with TI derived from the meteorological mast, nacelle mounted anemometer on the turbines and estimation based on the standard deviation of power. The results show that the proposed TI estimation method is in the best agreement with the meteorological mast. Therefore, the rotor effective wind speed is shown to be applicable for the TI assessment in real-time wind farm calculations under different operational conditions. Furthermore, the TI in the wake is seen to follow the same trend with the estimated wake deficit which enables to quantify the turbulence in terms of the wake loss locally inside the wind farm.