基于PR控制的海上风电场并网VSC-HVDC系统

提出了一种新的适用于海上风电场并网的新型高压直流输电(Voltage Source Converter based HVDC,VSC-HVDC)系统的比例谐振(Proportional Resonant,PR)控制策略。该方法充分利用PR控制器能够在αβ坐标系下对交流输入信号无静差控制的特点,将矢量控制策略下的有功电流和无功电流分量转换到αβ坐标系下进行调节,实现风电场和电网侧换流器维持直流电压稳定以及有功、无功功率的解耦控制。与常用的双闭环PI控制相比,该策略无需多次坐标变换和前馈解耦控制,且易于实现对系统谐波电流的补偿,降低了实现难度,提高了系统的鲁棒性和并网电能质量,为海上风电场并网VSC-HVDC系统提供了一种优化的控制方案。     

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.     

A comparison of methods for assessing power output in non‐uniform onshore wind farms

Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshore farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non‐uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. We show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.     

基于ADMM的风场两级分布式无功优化方法

由于风机的无功耗变,电网电压稳定性随着风力渗透的增加而降低.针对风电场接入的配电网系统无功优化调度问题,本文提出了一种基于ADMM算法的两级无功优化调度方法.与现有的无功优化控制方法相比,该方法采用两阶段优化结构实现分布式无功优化调度.此外,在分区概念下,不需要一致性协议来解决优化问题.该方法在控制设计中也考虑了各个风...     

Redefinition power curve for more accurate performance assessment of wind farms

The lack of accurate methods for assessment of the productive capacity of wind power plants is becoming a bottleneck in an increasingly commercialized wind power industry. In this article the inherent components of performance assessment are identified and analysed and ways of minimizing uncertainties on the components are investigated. The main components are identified as ‘site calibration’, ‘wind turbine sensitivity to flow variables’, ‘plant blockage effects’ and ‘uncertainty analysis’. Site calibration is the action of estimating the flow variables at the wind turbine position from measurements of these quantities at another (reference) position. The purpose of sensitivity analysis is to clarify which and how flow variables influence power output. Plant blockage effects refer to the power plant's influence on the reference measurements of flow variables. Finally, the component uncertainties and in turn the integrated uncertainty on the average productive capacity of the wind power plant are investigated. It is found that uncertainties can be reduced (1) by including several more flow variables in addition to hub‐height wind speed, (2) by carrying out site calibration with utmost care and by inclusion of more variables, (3) by taking plant blockage into consideration, (4) by aiming at ‘plant‐average’ power instead of looking only at individual machines and, possibly, (5) by introduction of remote‐sensing anemometer techniques. Copyright © 2000 John Wiley & Sons, Ltd.     

Resonant overvoltage assessment in offshore wind farms via a parametric black‐box wind turbine transformer model

The protection of offshore wind farms (OWFs) against overvoltages, especially resonant overvoltage, is of paramount importance because of poor accessibility and high repair costs. In this paper, we study how switching overvoltages at the wind turbine transformer (WTT) medium voltage (MV) side can lead to high overvoltages on the low voltage (LV) side. The effect of overvoltage protective devices is analyzed. A detailed model of an OWF row is developed in electromagnetic transients program–alternative transients program (EMTP‐ATP), including interconnecting cables, WTT, surge arresters and resistive–capacitive filters. A parameterized black‐box WTT model is obtained from measurements and is used for investigating the transfer of resonant overvoltages from the MV to the LV side. The model is capable of shifting systematically the frequencies and adjusting the transformer input impedance. Simulation results show that wind turbine energization in an OWF can lead to overvoltages on the LV terminals. The rate of rise of overvoltages (du/dt) is in the range of 300–500 pu/µs. It is found that resistive–capacitive filters should be installed on both MV and LV terminals of WTTs to decrease both resonant overvoltages and du/dt, which is unachievable by surge arrester alone. Copyright © 2014 John Wiley & Sons, Ltd.     

Wind model for low frequency power fluctuations in offshore wind farms

This paper investigates the correlation between the frequency components of the wind speed Power Spectral Density. The results extend an already existing power fluctuation model that can simulate power fluctuations of wind power on areas up to several kilometers and for time scales up to a couple of hours, taking into account the spectral correlation between different wind turbines. The modelling is supported by measurements from two large wind farms, namely Nysted and Horns Rev. Measurements from individual wind turbines and meteorological masts are used. Finally, the models are integrated into an aggregated model which is used for estimating some electrical parameters as power ramps and reserves requirements, showing a quite good agreement between simulations and measurement. The comparison with measurements generally show that the inclusion of the correlation between low frequency components is an improvement, but the effect is relatively small. The effect of including the low frequency components in the model is much more significant. Therefore, that aggregated model is useful in the power system planning and operation, e.g. regarding load following and regulation. Copyright © 2009 John Wiley & Sons, Ltd.     

TOPFARM: Multi‐fidelity optimization of wind farms

A wind farm layout optimization framework based on a multi‐fidelity optimization approach is applied to the offshore test case of Middelgrunden, Denmark as well as to the onshore test case of Stag Holt – Coldham wind farm, UK. While aesthetic considerations have heavily influenced the famous curved design of the Middelgrunden wind farm, this work focuses on demonstrating a method that optimizes the profit of wind farms over their lifetime based on a balance of the energy production income, the electrical grid costs, the foundations cost, and the cost of wake turbulence induced fatigue degradation of different wind turbine components. A multi‐fidelity concept is adapted, which uses cost function models of increasing complexity (and decreasing speed) to accelerate the convergence to an optimum solution. In the EU‐FP6 TOPFARM project, three levels of complexity are considered. The first level uses a simple stationary wind farm wake model to estimate the Annual Energy Production (AEP), a foundations cost model depending on the water depth and an electrical grid cost function dictated by cable length. The second level calculates the AEP and adds a wake‐induced fatigue degradation cost function on the basis of the interpolation in a database of simulations performed for various wind speeds and wake setups with the aero‐elastic code HAWC2 and the dynamic wake meandering model. The third level, not considered in this present paper, includes directly the HAWC2 and the dynamic wake meandering model in the optimization loop in order to estimate both the fatigue costs and the AEP. The novelty of this work is the implementation of the multi‐fidelity approach in the context of wind farm optimization, the inclusion of the fatigue degradation costs in the optimization framework, and its application on the optimal performance as seen through an economical perspective. Copyright © 2013 John Wiley & Sons, Ltd.     

State‐space representation of the wind flow model in wind farms

A dynamic model for the wind flow in wind farms is developed in this paper. The model is based on the spatial discretization of the linearized Navier–Stokes equation combined with the vortex cylinder theory. The spatial discretization of the model is performed using the finite difference method, which provides the state‐space form of the dynamic wind farm model. The model provides an approximation of the behavior of the flow in the wind farm and obtains the wind speed in the vicinity of each wind turbine. Afterwards, the model is validated using measurement data of Energy research Center of the Netherlands’ Wind turbine Test site in Wieringermeer in the Netherlands and by employing the outcomes of two other wind flow models. The end goal of this work is to present the wind farm flow model by ordinary differential equations, to be applied in wind farm control algorithms along with load and power optimizations. Copyright © 2013 John Wiley & Sons, Ltd.     

Model‐based receding horizon control of wind farms for secondary frequency regulation

In this study, we propose the use of model‐based receding horizon control to enable a wind farm to provide secondary frequency regulation for a power grid. The controller is built by first proposing a time‐varying one‐dimensional wake model, which is validated against large eddy simulations of a wind farm at startup. This wake model is then used as a plant model for a closed‐loop receding horizon controller that uses wind speed measurements at each turbine as feedback. The control method is tested in large eddy simulations with actuator disk wind turbine models representing an 84‐turbine wind farm that aims to track sample frequency regulation reference signals spanning 40 min time intervals. This type of control generally requires wind turbines to reduce their power set points or curtail wind power output (derate the power output) by the same amount as the maximum upward variation in power level required by the reference signal. However, our control approach provides good tracking performance in the test system considered with only a 4% derate for a regulation signal with an 8% maximum upward variation. This performance improvement has the potential to reduce the opportunity cost associated with lost revenue in the bulk power market that is typically associated with providing frequency regulation services. Copyright © 2017 John Wiley & Sons, Ltd.     

Nacelle anemometer measurement‐based extremum‐seeking wind turbine region‐2 control for improved convergence in fluctuating wind

For region‐2 operation of wind turbines in practice, the optimal torque gain can deviate from the nominal value because of the variations in turbine and wind conditions. The extremum‐seeking control (ESC) has shown its potential as a model‐free region‐2 control solution in some recent work; however, the ESC with rotor power feedback suffers from undesirable convergence under fluctuating wind. In this paper, we propose to use an estimated power coefficient as the objective function for the torque‐gain ESC, where the hub‐height free‐stream wind speed (FSWS) is estimated with the nacelle anemometer measurement on the basis of the so‐called nacelle transfer function (NTF) between the nacelle anemometer and met‐tower measurement. A sensitivity analysis is performed to quantify the impact of the wind speed estimation error on the estimation of power coefficient. An ESC integrated interregion switching scheme is proposed to avoid the load increase. Simulation results show that, compared with the power feedback‐based ESC, the proposed method can greatly improve the convergence rate of ESC under fluctuating wind, even under relatively large wind speed estimation error. Evaluation for the fatigue loads of wind turbine shows that the proposed control strategy induces mild increase of the wind turbine load.     

Modeling space‐time correlations of velocity fluctuations in wind farms

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 spatiotemporal 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 spatiotemporal structure of fluctuations in wind farms.     

Optimal operations for hydrogen-based energy storage systems in wind farms via model predictive control

Efficient energy production and consumption are fundamental points for reducing carbon emissions that influence climate change. Alternative resources, such as renewable energy sources (RESs), used in electricity grids, could reduce the environmental impact. Since RESs are inherently unreliable, during the last decades the scientific community addressed research efforts to their integration with the main grid by means of properly designed energy storage systems (ESSs). In order to highlight the best performance from these hybrid systems, proper design and operations are essential. The purpose of this paper is to present a so-called model predictive controller (MPC) for the optimal operations of grid-connected wind farms with hydrogen-based ESSs and local loads. Such MPC has been designed to take into account the operating and economical costs of the ESS, the local load demand and the participation to the electricity market, and further it enforces the fulfillment of the physical and the system's dynamics constraints. The dynamics of the hydrogen-based ESS have been modeled by means of the mixed-logic dynamic (MLD) framework in order to capture different behaviors according to the possible operating modes. The purpose is to provide a controller able to cope both with all the main physical and operating constraints of a hydrogen-based storage system, including the switching among different modes such as ON, OFF, STAND-BY and, at the same time, reduce the management costs and increase the equipment lifesaving. The case study for this paper is a plant under development in the north Norway. Numerical analysis on the related plant data shows the effectiveness of the proposed strategy, which manages the plant and commits the equipment so as to preserve the given constraints and save them from unnecessary commutation cycles.     

Dynamic models of wind farms with fixed speed wind turbines

The increasing wind power penetration on power systems requires the development of adequate wind farms models for representing the dynamic behaviour of wind farms on power systems. The behaviour of a wind farm can be represented by a detailed model including the modelling of all wind turbines and the wind farm electrical network. But this detailed model presents a high order model if a wind farm with high number of wind turbines is modelled and therefore the simulation time is long. The development of equivalent wind farm models enables the model order and the computation time to be reduced when the impact of wind farms on power systems is studied. In this paper, equivalent models of wind farms with fixed speed wind turbines are proposed by aggregating wind turbines into an equivalent wind turbine that operates on an equivalent wind farm electrical network. Two equivalent wind turbines have been developed: one for aggregated wind turbines with similar winds, and another for aggregated wind turbines under any incoming wind, even with different incoming winds.The proposed equivalent models provide high accuracy for representing the dynamic response of wind farm on power system simulations with an important reduction of model order and simulation time compare to that of the complete wind farm modelled by the detailed model.     

Fatigue distribution optimization for offshore wind farms using intelligent agent control

A novel control approach is proposed to optimize the fatigue distribution of wind turbines in a large‐scale offshore wind farm on the basis of an intelligent agent theory. In this approach, each wind turbine is considered to be an intelligent agent. The turbine at the farm boundary communicates with its neighbouring downwind turbines and organizes them adaptively into a wind delivery group along the wind direction. The agent attributes and the event structure are designed on the basis of the intelligent agent theory by using the unified modelling language. The control strategy of the intelligent agent is studied using topology models. The reference power of an individual wind turbine from the wind farm controller is re‐dispatched to balance the turbine fatigue in the power dispatch intervals. In the fatigue optimization, the goal function is to minimize the standard deviation of the fatigue coefficient for every wind turbine. The optimization is constrained such that the average fatigue for every turbine is smaller than what would be achieved by conventional dispatch and such that the total power loss of the wind farm is restricted to a few percent of the total power. This intelligent agent control approach is verified through the simulation of wind data from the Horns Rev offshore wind farm. The results illustrate that intelligent agent control is a feasible way to optimize fatigue distribution in wind farms, which may reduce the maintenance frequency and extend the service life of large‐scale wind farms. Copyright © 2012 John Wiley & Sons, Ltd.     

并网中小型风电系统最大功率跟踪控制

针对目前中小型风力发电系统发电效率低,提出了一种新型拓扑结构,即机侧采用三相PWM整流器,网侧采用单相PWM逆变器。在对永磁同步发电机数学模型和风力机最佳输出功率进行分析的基础上,采用转子磁链定向控制技术,实现对发电机输出的有功功率的控制,进而实现对风力发电机最大功率的跟踪控制;同时,在单相系统中引入"虚拟电路",使网侧单相变流电路参数可以转化到旋转坐标系下,实现无静差控制。通过仿真试验验证了控制策略的可行性。     

Large‐eddy simulations with extremum‐seeking control for individual wind turbine power optimization

Large‐eddy simulations of the flow past an array of three aligned turbines have been performed. The study is focused on below rated (Region 2) wind speeds. The turbines are controlled through the generator torque gain, as usually done in Region 2. Two operating strategies are considered: (i) preset individual optimum torque gain based on a model for the power coefficient (baseline case) and (ii) real‐time optimization of torque gain for maximizing each individual turbine power capture during operation. The real‐time optimization is carried out through a model‐free approach, namely, extremum‐seeking control. It is shown that ESC is capable of increasing the power production of the array by 6.5% relative to the baseline case. The extremum‐seeking control reduces the torque gain of the downstream turbines, thus increasing the angular speed of the blades. This results in improved aerodynamics near the tip of the blade that is the portion contributing mostly to the torque and power. In addition, an increase in angular speed leads to a larger entrainment in the wake, which also contributes to provide additional available power downstream. It is also shown that the tip speed ratio may not be a reliable performance indicator when the turbines are in waked conditions. This may be a concern when using optimal parameter settings, determined from isolated turbine models, in applications with waked turbines. Copyright © 2017 John Wiley & Sons, Ltd.     

Coordinated control of series‐connected offshore wind park based on matrix converters

Optimization and reliability are two important aspects in design and operation of wind parks either for offshore as for onland emplacements. However, offshore locations demand conscientious effort in optimizing the size and the weight of each component in the energy conversion system because of the high investment and maintenance costs related with the supporting structures and transportation respectively. Achieving these two objectives requires the combination of different optimization stages, which consider a suitable design of the entire conversion system with innovative and more e?cient power electronic devices, optimized topology of the offshore grid and customized control strategies for optimizing the operation of the park. This paper presents an energy conversion concept for wind turbines on the basis of a reduced matrix converter (RMC) that will enable series direct current architecture in offshore wind parks thus preventing the need for offshore platforms. The RMC is built with bidirectional semiconductors that give reduced losses because of both superior topology and more e?cient semiconductors. The proposed conversion topology is tested in stationary state and transient operation. In addition to operational features of the concept, control and operation of a wind park with several turbines are presented. Dynamic operation of the turbine as well as the high‐voltage direct current transmission line effects are considered. Three types of models are therefore developed. First, an accurate and detailed model for analyzing one single turbine with the converter operated at high‐frequency switching is presented. This model considers a new modulation for the RMC. A second and simpli?ed model is used for small signal analysis. This model permits to simulate several series‐connected cluster during transient. Finally, an optimal direct current load ?ow model is used for evaluating stationary state operation. Results show the technical feasibility of the proposed concept and their advantages over conventional topologies. The paper also discusses the technological challenges that this type of offshore grid architecture will bring. Copyright © 2011 John Wiley & Sons, Ltd.     

Windstorm risk assessment for offshore wind farms in the North Sea

The North Sea is becoming increasingly attractive to wind energy developers and investors, with 38 wind farms belonging to five different countries and representing over€35 billion of assets. Concerns about offshore wind turbines being damaged by extreme windstorms pose a challenge to insurers, investors and regulators. Catastrophe modeling can adequately quantify the risk. In this study, a Monte Carlo simulation approach is used to assess the number of turbines that buckle using maximum wind speeds reaching each wind farm. Damage assessment is undertaken for each wind farm using a log‐logistic damage function and a left‐truncated Weibull distribution. The risk to offshore wind power in the North Sea is calculated using an exceedance probability (EP) curve for the portfolio of wind farms. The European Union Solvency II directive requires insurance companies to hold sufficient capital to guard against insolvency. The solvency capital requirement (SCR) is based on a value‐at‐risk measure calibrated to a 99.5% confidence level over a 1‐year time horizon. The SCR is estimated at €0.049 billion in the case of yawing turbines. Simulations are repeated for different climate change scenarios. If wind speeds grow by 5% and the frequency of storms increases by 40%, the SCR is seen to rise substantially to €0.264 billion. Relative to the total value of assets, the SCR is 0.14% compared with 0.08% for European property, confirming that these wind farm assets represent a relatively high risk. Furthermore, climate change could increase the relative SCR to levels as high as 0.75%.     

Analysis of axial‐induction‐based wind plant control using an engineering and a high‐order wind plant model

Wind turbines are typically operated to maximize their performance without considering the impact of wake effects on nearby turbines. Wind plant control concepts aim to increase overall wind plant performance by coordinating the operation of the turbines. This paper focuses on axial‐induction‐based wind plant control techniques, in which the generator torque or blade pitch degrees of freedom of the wind turbines are adjusted. The paper addresses discrepancies between a high‐order wind plant model and an engineering wind plant model. Changes in the engineering model are proposed to better capture the effects of axial‐induction‐based control shown in the high‐order model. Copyright © 2015 John Wiley & Sons, Ltd.