Simulation of Typhoon-Driven Waves in the Yangtze Estuary with Multiple-Nested Wave Models

Typhoon-generated waves are simulated with two numerical wave models, the SWAN model for the coastal and Yangtze Estuary domain, nested within the WAVEWATCHIII （WW3） for the basin-scale East China Sea domain. Typhoon No. 8114 is chosen because it was very strong, and generated high waves in the Estuary. WW3 was implemented for the East China Sea coarse-resolution computational domain, to simulate the waves over a large spatial scale and provide boundary conditions for SWAN model simulations, implemented on a fine-resolution nested domain for the Yangtze Estuary area. The Takahashi wind model is applied to the simulation of the East China Sea scale （3-hourly） and Yangtze Estuary scale （1-hourly） winds. Simulations of significant wave heights in the East China Sea show that the highest waves are on the right side of the storm track, and maxima tend to occur at the eastern deep-water open boundary of the Yangtze Estuary. In the Yangtze Estuary, incoming swell is dominant over locally generated waves before the typhoon approaches the Estuary. As the typhoon approaches the Estuary, wind waves and swell coexist, and the wave direction is mainly influenced by the swell direction and the complex topography.

A hybrid model for numerical wave forecasting and its implementation-Ⅰ.The wind wave model

The authors make an endeavor to explain why a new hybrid wave model is here proposed when several such models have already been in operation and the so- called third generation wave modej is proving attractive. This part of the paper is devoted to the wind wave model. Both deep and shallow water models have been developed, the former being actually a special case of the latter when water depth is great. The deep water model is exceptionally simple in form. Significant wave height is the only prognostic variable. In comparison with the usual methods to compute the energy input and dissipations empirically or by 'tuning', the proposed model has the merit that the effects of all source terms are combined into one term which is computed through empirical growth relations for significant waves, these relations being, relatively speaking, easier and more reliable to obtain than those for the source terms in the spectral energy balance equation. The discrete part of the model and the implementation of the model as a whole will be discussed in the second part of the present paper.

A sensitivity study of the WRF model in offshore wind modeling over the Baltic Sea

Accurate wind modeling is important for wind resources assessment and wind power forecasting. To improve the WRF model configuration for the offshore wind modeling over the Baltic Sea, this study performed a sensitivity study of the WRF model to multiple model configurations, including domain setup,grid resolution, sea surface temperature, land surface data, and atmosphere-wave coupling. The simulated offshore wind was evaluated against LiDAR observations under different wind directions, atmospheric stabilities, and sea status. Generally, the simulated wind profiles matched observations, despite systematic underestimations. Strengthening the forcing from the reanalysis data through reducing the number of nested domains played the largest role in improving wind modeling. Atmosphere-wave coupling further improved the simulated wind, especially under the growing and mature sea conditions.Increasing the vertical resolution, and updating the sea surface temperature and the land surface information only had a slight impact, mainly visible during very stable conditions. Increasing the horizontal resolution also only had a slight impact, most visible during unstable conditions. Our study can help to improve the wind resources assessment and wind power forecasting over the Baltic Sea.

Development of wind-energy modeling technology and standards

To ensure the stable operation of power systems with large proportions of wind power,China has published a series of national,industry,and enterprise standards for wind power.The increase in the number of standards and the expansion of their application scope have given rise to a situation where multiple standards overlap and conflict with regard to the establishment of models and their applicability,resulting in unclear standard application scenarios.Therefore,it is imperative to analyze the development of wind-turbine and wind-farm modeling,along with the relevant standards.This paper presents the methods for wind-turbine modeling,the equivalent model of wind farms based on the general model of wind turbines,and the technical provisions and application scenarios involved in the relevant domestic and international standards.The adaptability of the relevant standards is examined.The results of this study are helpful for advancing wind power generation in China and ensuring the safe and stable operation of large-scale wind power systems.

Application of a new wind driving force model in soil wind erosion area of northern China

The shear stress generated by the wind on the land surface is the driving force that results in the wind erosion of the soil.It is an independent factor influencing soil wind erosion.The factors related to wind erosivity,known as submodels,mainly include the weather factor(WF)in revised wind erosion equation(RWEQ),the erosion submodel(ES)in wind erosion prediction system(WEPS),as well as the drift potential(DP)in wind energy environmental assessment.However,the essential factors of WF and ES contain wind,soil characteristics and surface coverings,which therefore results in the interdependence between WF or ES and other factors(e.g.,soil erodible factor)in soil erosion models.Considering that DP is a relative indicator of the wind energy environment and does not have the value of expressing wind to induce shear stress on the surface.Therefore,a new factor is needed to express accurately wind erosivity.Based on the theoretical basis that the soil loss by wind erosion(Q)is proportional to the shear stress of the wind on the soil surface,a new model of wind driving force(WDF)was established,which expresses the potential capacity of wind to drive soil mass in per unit area and a period of time.Through the calculations in the typical area,the WDF,WF and DP are compared and analyzed from the theoretical basis,construction goal,problem-solving ability and typical area application;the spatial distribution of soil wind erosion intensity was concurrently compared with the spatial distributions of the WDF,WF and DP values in the typical area.The results indicate that the WDF is better to reflect the potential capacity of wind erosivity than WF and DP,and that the WDF model is a good model with universal applicability and can be logically incorporated into the soil wind erosion models.

Evaluation of a Micro-scale Wind Model's Performance over Realistic Building Clusters Using Wind Tunnel Experiments

The simulation performance over complex building clusters of a wind simulation model（Wind Information Field Fast Analysis model, WIFFA） in a micro-scale air pollutant dispersion model system（Urban Microscale Air Pollution dispersion Simulation model, UMAPS） is evaluated using various wind tunnel experimental data including the CEDVAL（Compilation of Experimental Data for Validation of Micro-Scale Dispersion Models） wind tunnel experiment data and the NJU-FZ experiment data（Nanjing University-Fang Zhuang neighborhood wind tunnel experiment data）. The results show that the wind model can reproduce the vortexes triggered by urban buildings well, and the flow patterns in urban street canyons and building clusters can also be represented. Due to the complex shapes of buildings and their distributions, the simulation deviations/discrepancies from the measurements are usually caused by the simplification of the building shapes and the determination of the key zone sizes. The computational efficiencies of different cases are also discussed in this paper. The model has a high computational efficiency compared to traditional numerical models that solve the Navier–Stokes equations, and can produce very high-resolution（1–5 m） wind fields of a complex neighborhood scale urban building canopy（～ 1 km ×1km） in less than 3 min when run on a personal computer.

Model of DFIG Wind Farm and Study on Its LVRT Capability

As a typical clean and renewable energy, wind power is becoming more and more widely used in electrical industry. However, its characteristics of random and intermittent have brought serious problems to the power system, such as voltage fluctuation and insufficient reactive power. Based on the K-means clustering algorithm, this paper classifies the doubly-fed induction generators （DFIG） according to the operation of propeller pitch angle control. At the same time, to obtain the optimal parameter, advanced particle swarm optimization （PSO） is used. Then the dynamic model of DFIG under the network fault condition is built. What is more, the role that crowbar circuit plays in low voltage ride through （LVRT） is discussed. Finally, simulations in DigSILENT verify the model.

Improvement of wind field hindcasts for tropical cyclones

This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the cross-calibrated multi-platform （CCMP） reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data.

Influences of affiliated components and train length on the train wind

The induced airfl w from passing trains,which is recognized as train wind,usually has adverse impacts on people in the surroundings,i.e.,the aerodynamic forces generated by a high-speed train＇s wind may act on the human body and endanger the safety of pedestrians or roadside workers.In this paper,an improved delayed detached eddy simulation（IDDES） method is used to study train wind.The effects of the affiliate components and train length on train wind are analyzed.The results indicate that the aff liated components and train length have no effect on train wind in the area in front of the leading nose.In the downstream and wake regions,the longitudinal train wind becomes stronger as the length of the train increases,while the transverse train wind is not affected.The presence of affiliate components strengthens the train wind in the near fiel of the train because of strong fl w solid interactions but has limited effects on train wind in the far field.

An estimation method of soil wind erosion in Inner Mongolia of China based on geographic information system and remote sensing

Studies of wind erosion based on Geographic Information System（GIS） and Remote Sensing（RS） have not attracted sufficient attention because they are limited by natural and scientific factors.Few studies have been conducted to estimate the intensity of large-scale wind erosion in Inner Mongolia,China.In the present study,a new model based on five factors including the number of snow cover days,soil erodibility,aridity,vegetation index and wind field intensity was developed to quantitatively estimate the amount of wind erosion.The results showed that wind erosion widely existed in Inner Mongolia.It covers an area of approximately 90×104 km2,accounting for 80% of the study region.During 1985–2011,wind erosion has aggravated over the entire region of Inner Mongolia,which was indicated by enlarged zones of erosion at severe,intensive and mild levels.In Inner Mongolia,a distinct spatial differentiation of wind erosion intensity was noted.The distribution of change intensity exhibited a downward trend that decreased from severe increase in the southwest to mild decrease in the northeast of the region.Zones occupied by barren land or sparse vegetation showed the most severe erosion,followed by land occupied by open shrubbery.Grasslands would have the most dramatic potential for changes in the future because these areas showed the largest fluctuation range of change intensity.In addition,a significantly negative relation was noted between change intensity and land slope.The relation between soil type and change intensity differed with the content of Ca CO3 and the surface composition of sandy,loamy and clayey soils with particle sizes of 0–1 cm.The results have certain significance for understanding the mechanism and change process of wind erosion that has occurred during the study period.Therefore,the present study can provide a scientific basis for the prevention and treatment of wind erosion in Inner Mongolia.

An Extreme Value Analysis of Wind Speed over the European and Siberian Parts of Arctic Region

Multiyear observed time series of wind speed for selected points of the Arctic region (data of station network from the Kola Peninsula to the Chukotka Peninsula) are used to highlight the important peculiarities of wind speed extreme statistics. How largest extremes could be simulated by climate model (the INM-CM4 model data from the Historical experiment of the CMIP5) is also discussed. Extreme value analysis yielded that a volume of observed samples of wind speeds are strictly divided into two sets of variables. Statistical properties of one population are sharply different from another. Because the common statistical conditions are the sign of identity of extreme events we therefore hypothesize that two groups of extreme wind events adhere to different circulation processes. A very important message is that the procedure of selection can be realized easily based on analysis of the cumulative distribution function. The authors estimate the properties of the modelled extremes and conclude that they consist of only the samples, adhering to one group. This evidence provides a clue that atmospheric model with a coarse spatial resolution does not simulate special mechanism responsible for appearance of largest wind speed extremes. Therefore, the tasks where extreme wind is needed cannot be explicitly solved using the output of climate model. The finding that global models are unable to capture the wind extremes is already well known, but information that they are members of group with the specific statistical conditions provides new knowledge. Generally, the implemented analytical approach allows us to detect that the extreme wind speed events adhere to different statistical models. Events located above the threshold value are much more pronounced than representatives of another group (located below the threshold value) predicted by the extrapolation of law distributions in their tail. The same situation is found in different areas of science where the data referring to the same nomenclature are adhering to different statistical models. This result motivates our interest on our ability to detect, analyze, and understand such different extremes.

A method to predict typhoon waves

The presented method for numerical typhoon wave prediction is composed of a scheme for real time pressure forecasts, a marine wind numerical model and a typhoon wave numerical model. In the Northwest Pacific Ocean and China seas where water depth is over 20 m, a hybrid wave model [Wen Shengchang, Zhang Dacuo, Chen Bobal and Guo Peifang. 1989, Acta Oceanologica Sinica, 8 (1), 1～14; Zhang Dacuo, Wu Zengmao,Jiang Decai, Wang Wei, Chen Bobai, Tat Weitao, Wen Shengchang, Xu Qichun and Guo Peifaug. 1992, Acta Oceanologica Sinica, 11 (2), 157～178] is employed with 1°×1°grids, while in the South China Sea and East China Sea where typhoon frequently appears, the WAM model (WAMDI Group. 1988, Journal of Physical Oceanography, 18, 1755～1810) of shallow water version is embedded with (1 /4 )°×(1 /4)°grids. The boundary condition at the open boundary of the WAM model is provided by the hybrid model. After 3 a of testing forecasts(Yang Chuncheng, Dai Mingrui and Zhang Dacuo. 1992, International Symposium on Tropical Cyclone Disasters, October 12～16, Beijing, 404～409 ) and improvement, this system was put into operational use on the forecasting computer network of National Marine Environment Forecast Center of China in June, 1993. The wave predictions of 22 typhoon events show that the system is stable and prompt, and the forecast results are satisfactory. This system provides reliable numerical products for the disaster-prevention forecasts. The product is broadcasted in CCTV News at every noon.

Wind speed model based on kernel density estimation and its application in reliability assessment of generating systems

An accurate probability distribution model of wind speed is critical to the assessment of reliability contribution of wind energy to power systems. Most of current models are built using the parametric density estimation(PDE) methods, which usually assume that the wind speed are subordinate to a certain known distribution(e.g. Weibull distribution and Normal distribution) and estimate the parameters of models with the historical data. This paper presents a kernel density estimation(KDE) method which is a nonparametric way to estimate the probability density function(PDF) of wind speed. The method is a kind of data-driven approach without making any assumption on the form of the underlying wind speed distribution, and capable of uncovering the statistical information hidden in the historical data. The proposed method is compared with three parametric models using wind data from six sites.The results indicate that the KDE outperforms the PDE in terms of accuracy and flexibility in describing the longterm wind speed distributions for all sites. A sensitivity analysis with respect to kernel functions is presented and Gauss kernel function is proved to be the best one. Case studies on a standard IEEE reliability test system(IEEERTS) have verified the applicability and effectiveness of the proposed model in evaluating the reliability performance of wind farms.

Mapping the Wind Hazard of Global Tropical Cyclones with Parametric Wind Field Models by Considering the Effects of Local Factors

Tropical cyclones(TCs) cause catastrophic loss in many coastal areas of the world. TC wind hazard maps can play an important role in disaster management. A good representation of local factors reflecting the effects of spatially heterogeneous terrain and land cover is critical to evaluation of TC wind hazard. Very few studies, however,provide global wind hazard assessment results that consider detailed local effects. In this study, the wind fields of historical TCs were simulated with parametric models in which the planetary boundary layer models explicitly integrate local effects at 1 km resolution. The topographic effects for eight wind directions were quantified over four types of terrain(ground, escarpment, ridge, and valley),and the surface roughness lengths were estimated from a global land cover map. The missing TC parameters in the best track datasets were reconstructed with local regression models. Finally, an example of a wind hazard map in the form of wind speeds under a 100-year return period and corresponding uncertainties was created based on a statistical analysis of reconstructed historical wind fields over seven of the world's ocean basins.

Model-based and Fuzzy Logic Approaches to Condition Monitoring of Operational Wind Turbines

It is common for wind turbines to be installed in remote locations on land or offshore, leading to difficulties in routine inspection and maintenance. Further, wind turbines in these locations are often subject to harsh operating conditions. These challenges mean there is a requirement for a high degree of maintenance. The data generated by monitoring systems can be used to obtain models of wind turbines operating under different conditions, and hence predict output signals based on known inputs. A model-based condition monitoring system can be implemented by comparing output data obtained from operational turbines with those predicted by the models, so as to detect changes that could be due to the presence of faults. This paper discusses several techniques for model-based condition monitoring systems: linear models, artificial neural networks, and state dependent parameter "pseudo" transfer functions.The models are identified using supervisory control and data acquisition(SCADA) data acquired from an operational wind firm. It is found that the multiple-input single-output state dependent parameter method outperforms both multivariate linear and artificial neural network-based approaches. Subsequently, state dependent parameter models are used to develop adaptive thresholds for critical output signals. In order to provide an early warning of a developing fault, it is necessary to interpret the amount by which the threshold is exceeded, together with the period of time over which this occurs. In this regard, a fuzzy logic-based inference system is proposed and demonstrated to be practically feasible.

A NOVEL DRIVING STRATEGY FOR DYNAMIC SIMULATION OF HOISTING ROPE WITH TIME-VARYING LENGTH

A simulation method for investigating the vibration behavior of hoisting rope with time-varying length is improved.By previously creating markers in the MSC.ADAMS software package,the parametric model of the rope wound along helix is established based on the concentrated-mass theory with multi-degree of freedom(multi-DOF).A novel driving strategy,cooperating fixed joints with angle sensors under the control of driving script,is proposed to substitute conventional contact force.Researching on the hoisting rope in the sinking winch mechanism,an equivalent discretization model is obtained with complicated boundary conditions considered.The differential equations of motion of the hoisting system are formulated employing Lagrange’s equation and numerically solved using Runge–Kutta method.The simulation indicates that the horizontal swing is decreased in principle and the simulation with 800 discrete ropes is not performed more than 61 min.Therefore,this feasible strategy could not only guarantee the accuracy but also promote simulation efficiency and stability.The motion curves exported from ADAMS simulation coincide with one in numerical simulation,which validates both the numerical model and the driving strategy.

Wind farm polymerization influences on security and economic operation in power system based on Copula function

Wind speed dependences on different areas in a wind farm have influences on security and economic operation in power system.In order to simulate the correlation of wind speed series between different positions,this paper applies Copula function and rank correlation matrix methods to measure the coherence of wind speed in a wind farm.The correlated wind sample space is established.According to active power output characteristics of wind turbines,the polymerization model in a wind farm can be achieved.Monte Carlo optimal power flow is applied to IEEE-30 and IEEE-300 bus systems based on the principle of energy saving dispatching.The study shows that the accuracy of outputs is improved,thus reducing the fluctuation ranges in unit generating costs and power flow in branches while considering wind speed polymerization.This approach provides a new method to improve the effectiveness of energy saving dispatching and system operation arrangement.Results have been tested to be effective.

Universal generating function based probabilistic production simulation for wind power integrated power systems

According to the demand of sustainable development and low-carbon electricity, it is important to develop clean resources and optimize scheduling generation mix. Firstly, a novel method for probabilistic production simulation for wind power integrated power systems is proposed based on universal generating function(UGF), which completes the production simulation with the chronological wind power and load demand. Secondly,multiple-period multiple-state wind power model and multiple-state thermal unit power model are adopted, and both thermal power and wind power are coordinately scheduled by the comprehensive cost including economic cost and environmental cost. Furthermore, the accommodation and curtailment of wind power is synergistically considered according to the available regulation capability of conventional generators in operation. Finally, the proposed method is verified and compared with conventional convolution method in the improved IEEE-RTS 79 system.

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.

Gain-scheduling control of a floating offshore wind turbine above rated wind speed

This paper presents an application of gain-scheduling(GS) control techniques to a floating offshore wind turbine on a barge platform for above rated wind speed cases. Special emphasis is placed on the dynamics variation of the wind turbine system caused by plant nonlinearity with respect to wind speed. The turbine system with the dynamics variation is represented by a linear parameter-varying(LPV) model, which is derived by interpolating linearized models at various operating wind speeds. To achieve control objectives of regulating power capture and minimizing platform motions, both linear quadratic regulator(LQR) GS and LPV GS controller design techniques are explored. The designed controllers are evaluated in simulations with the NREL 5 MW wind turbine model, and compared with the baseline proportional-integral(PI) GS controller and non-GS controllers. The simulation results demonstrate the performance superiority of LQR GS and LPV GS controllers, as well as the performance trade-off between power regulation and platform movement reduction.