Optimal placement of wind turbines within a wind farm considering multi-directional wind speed using two-stage genetic algorithm

Most wind turbines within wind farms are set up to face a pre-determined wind direction. However, wind directions are intermittent in nature, leading to less electricity production capacity. This paper proposes an algorithm to solve the wind farm layout optimization problem considering multi-angular (MA) wind direction with the aim of maximizing the total power generated on wind farms and minimizing the cost of installation. A two-stage genetic algorithm (GA) equipped with complementary sampling and uniform crossover is used to evolve a MA layout that will yield optimal output regardless of the wind direction. In the first stage, the optimal wind turbine layouts for 8 different major wind directions were determined while the second stage allows each of the previously determined layouts to compete and inter-breed so as to evolve an optimal MA wind farm layout. The proposed MA wind farm layout is thereafter compared to other layouts whose turbines have focused site specific wind turbine orientation. The results reveal that the proposed wind farm layout improves wind power production capacity with minimum cost of installation compared to the layouts with site specific wind turbine layouts. This paper will find application at the planning stage of wind farm.     

基于CFO的海上风电场微观选址优化算法研究

海上风电场用海面积有限,尾流影响比陆上大,微观选址是其规划设计的关键技术。传统优化算法大多采用离散化变量,使得潜在解空间减少到有限个,难以达到最优化的效果。为了提高海上风电场微观选址优化效率,文章提出了一种基于中心引力优化(CFO)算法的海上风电场微观选址方法。该算法使用实数编码,通过将微观选址优化的变量假设为天体,各个天体之间相互作用,达到平衡的原理,具有可能得到全局最优解和效率高的优点。使用该算法对海上风电场微观选址优化进行仿真,并与现有方法比较。结果表明,所提出的算法得到的排布方式发电量最高,并具有优化精度高、速度快和优化排布较为均匀的特点。该研究结果可以为实际工程应用提供参考。     

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...     

Active wake control: An approach to optimize the lifetime operation of wind farms

The wind turbines within a wind farm impact each other's power production and loads through their wakes. Wake control strategies, aiming to reduce wake effects, receive increasing interest by both the research community and the industry. A number of recent simulation studies with high fidelity wake models indicate that wake mitigation control is a very promising concept for increasing the power production of a wind farm and/or reducing the fatigue loading on wind turbines' components. The purpose of this paper is to study the benefits of wake mitigation control in terms of lifetime power production and fatigue loading on several existing full‐scale commercial wind farms with different scale, layouts, and turbine sizes. For modeling the wake interactions, Energy Research Centre of the Netherlands' FarmFlow software is used: a 3D parabolized Navier‐Stokes code, including a k‐? turbulence model. In addition, an optimization approach is proposed that maximizes the lifetime power production, thereby incorporating the fatigue loads into the optimization criterion in terms of a lifetime extension factor.     

Analysis and estimation of transient stability for a grid-connected wind turbine with induction generator

Increasing levels of wind energy in modern electrical power system is initiating a need for accurate analysis and estimation of transient stability of wind turbine generation systems. This paper investigates the transient behaviors and possible direct methods for transient stability evaluation of a grid-connected wind turbine with squirrel cage induction generator (SCIG). Firstly, by using an equivalent lump mass method, a three-mass wind turbine equivalent model is proposed considering both the blades and the shaft flexibility of the wind turbine drive train system. Combined with the detailed electromagnetic transient models of a SCIG, the transient behaviors of the wind turbine generation system during a three-phase fault are simulated and compared with the traditional models. Secondly, in order to quickly estimate the transient stability limit of the wind turbine generation system, a direct method based on normal form theory is proposed. The transient models of the wind turbine generation system including the flexible drive train model are derived based on the direct transient stability estimation method. A method of critical clearing time (CCT) calculation is developed for the transient stability estimation of the wind turbine generation system. Finally, the CCT at various initial mechanical torques for different dynamical models are calculated and compared with the trial and error method by simulation, when the SCIG stator terminal is subjected to a three-phase short-circuit fault. The results have shown the proposed method and models are correct and valid.     

Sensitivity of southern California wind energy to turbine characteristics

Using output from a high‐resolution meteorological simulation, we evaluate the sensitivity of southern California wind energy generation to variations in key characteristics of current wind turbines. These characteristics include hub height, rotor diameter and rated power, and depend on turbine make and model. They shape the turbine's power curve and thus have large implications for the energy generation capacity of wind farms. For each characteristic, we find complex and substantial geographical variations in the sensitivity of energy generation. However, the sensitivity associated with each characteristic can be predicted by a single corresponding climate statistic, greatly simplifying understanding of the relationship between climate and turbine optimization for energy production. In the case of the sensitivity to rotor diameter, the change in energy output per unit change in rotor diameter at any location is directly proportional to the weighted average wind speed between the cut‐in speed and the rated speed. The sensitivity to rated power variations is likewise captured by the percent of the wind speed distribution between the turbines rated and cut‐out speeds. Finally, the sensitivity to hub height is proportional to lower atmospheric wind shear. Using a wind turbine component cost model, we also evaluate energy output increase per dollar investment in each turbine characteristic. We find that rotor diameter increases typically provide a much larger wind energy boost per dollar invested, although there are some zones where investment in the other two characteristics is competitive. Our study underscores the need for joint analysis of regional climate, turbine engineering and economic modeling to optimize wind energy production. Copyright © 2012 John Wiley & Sons, Ltd.     

Urban wind energy conversion: The potential of ducted turbines

The prospects for urban wind power are discussed. A roof-mounted ducted wind turbine, which uses pressure differentials created by wind flow around a building, is proposed as an alternative to more conventional approaches. Outcomes from tests at model and prototype scale are described, and a simple mathematical model is presented. Predictions from the latter suggest that a ducted turbine can produce very high specific power outputs, going some way to offsetting its directional sensitivity. Further predictions using climate files are made to assess annual energy output and seasonal variations, with a conventional small wind turbine and a photovoltaic panel as comparators. It is concluded that ducted turbines have significant potential for retro-fitting to existing buildings, and have clear advantages where visual impact and safety are matters of concern.     

基于Matlab/Simulink的风力机性能仿真研究

随着风力发电技术的发展,变速风力发电技术成为了风力发电发展的趋势。风力机作为变速风力发电机组的重要部分,其性能影响到风力发电机组的整体性能。根据变速风力机的静态性能特点,采用Matlab／Simulink软件对其进行建模,并给变速风力发电机组风力机输入模拟变速风速进行仿真研究,给出了风力机的静态性能数据和仿真波形。结果表明：通过调节影响风力机性能的各因素,保持发电机的转速与主导风速之间特定的最优比例系数,使得风力机保持在最佳叶尖速比下运行,跟随变速风速可实现最大风能捕获;对变速风力机的静态性能研究建模方法是正确可行的。     

Identification-based prediction of wind park power generation

This paper approaches the problem of output power prediction for an off-shore wind park. To this end, a so called wind deficiency factor for each turbine and for each wind direction sector is identified using past data. This identification is done by using the effective wind speed concept that can establish a link between output power of each wind turbine and meteorological mast measures in terms of wind speed and direction. Based on forecast wind speed and direction, a wind park simulator that uses the previously-identified deficiency factors, computes future output power time evolutions. Numerical simulations show the feasibility of the proposed approach.     

Effects of inflow turbulence intensity and turbine arrangements on the power generation efficiency of large wind farms

In this study, we conduct a series of large‐eddy simulations (LESs) to study the impact of different incoming turbulent boundary layer flows over large wind farms, with a particular focus on the overall efficiency of electricity production and the evolution of the turbine wake structure. Five representative turbine placements in the large wind farm are considered, including an aligned layout and four staggered layouts with lateral or vertical offset arrangements. Four incoming flow conditions are used and arranged from the LESs of the ABL flow over homogeneous flat surfaces with four different aerodynamic roughness lengths (i.e., z0 = 0.5, 0.1, 0.01, and 0.0001 m), where the hub‐height turbulence intensity levels are about 11.1%, 8.9%, 6.8%, and 4.9%, respectively. The simulation results indicate that an enhancement in the inflow turbulence level can effectively increase the power generation efficiency in the large wind farms, with about 23.3% increment on the overall farm power production and up to about 32.0% increment on the downstream turbine power production. Under the same inflow condition, the change of the turbine‐array layouts can increase power outputs within the first 10 turbine rows, which has a maximum increment of about 26.5% under the inflow condition with low turbulence. By comparison, the increase of the inflow turbulence intensity facilitates faster wake recovery that raises the power generation efficiency of large wind farms than the adjustment of the turbine placing layouts.     

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.     

风向对广东海上风电场风机布置的影响

引入一个包含20台4 MW风力发电机组,风机布置采用规则几何构型的海上风电场理论模型,设计了两大类共4个不同的风机阵列,根据1991-2010年广东近海区域MERRA再分析资料,从海面风向的季节变化、扇区划分方式变化以及风向频率分布变化等三个方面开展数值试验研究。结果表明:平行四边形阵列比矩形阵列更具灵活性,能够适应更复杂的风向季节性偏转;风机布置需要更加细致的风向扇区划分方式,传统的16个风向扇区划分方式难以适应风机阵列最佳朝向的选择与调整;风机布置方案比选需要考虑风向频率分布的年际变动,通过敏感性试验识别更具稳定性的风机阵列。     

A novel control strategy approach to optimally design a wind farm layout

Recently wind energy has become one of the most important alternative energy sources and is growing at a rapid rate because of its renewability and abundancy. For the clustered wind turbines in a wind farm, significant wind power losses have been observed due to wake interactions of the air flow induced by the upstream turbines to the downstream turbines. One approach to reduce power losses caused by the wake interactions is through the optimization of wind farm layout, which determine the wind turbine positions and control strategy, which determine the wind turbine operations. In this paper, a new approach named simultaneous layout plus control optimization is developed. The effectiveness is studied by comparison to two other approaches (layout optimization and control optimization). The results of different optimizations, using both grid based and unrestricted coordinate wind farm design methods, are compared for both ideal and realistic wind conditions. Even though the simultaneous layout plus control optimization is theoretically superior to the others, it is prone to the local minima. Through the parametric study of crossover and mutation probabilities of the optimization algorithm, the results of the approach are generally satisfactory. For both simple and realistic wind conditions, the wind farm with the optimized control strategy yield 1–3 kW more power per turbine than that with the self-optimum control strategy, and the unrestricted coordinate method yield 1–2 kW more power per turbine than the grid based method.     

Evaluation of wind farm efficiency and wind turbine wakes at the Nysted offshore wind farm

Here, we quantify relationships between wind farm efficiency and wind speed, direction, turbulence and atmospheric stability using power output from the large offshore wind farm at Nysted in Denmark. Wake losses are, as expected, most strongly related to wind speed variations through the turbine thrust coefficient; with direction, atmospheric stability and turbulence as important second order effects. While the wind farm efficiency is highly dependent on the distribution of wind speeds and wind direction, it is shown that the impact of turbine spacing on wake losses and turbine efficiency can be quantified, albeit with relatively large uncertainty due to stochastic effects in the data. There is evidence of the ‘deep array effect’ in that wake losses in the centre of the wind farm are under‐estimated by the wind farm model WAsP, although overall efficiency of the wind farm is well predicted due to compensating edge effects. Copyright © 2010 John Wiley & Sons, Ltd.     

基于改进粒子群优化算法与风速分布回归函数法的复杂地形风电场优化布置方法

为了研究在复杂地形下的风力机优化排布方法,提出一种改进粒子群（PSO）优化方法,并借助风速回归函数解决一部分复杂地形所致的问题,对实际尾流效应设置约束条件,判断风能利用的最优方案,从而快速确定风力机具体安放坐标,通过Matlab建模仿真,并借助WAsP软件对改进PSO优化算法和传统方法进行对比验证。结果表明,改进粒子群（PSO）优化方法与传统方法相比,年发电量提高了近5.2%,且对复杂地形下的风电场优化布局效果较好。     

On wind turbine power performance measurements at inclined airflow

The average airflow inclination in complex terrain may be substantial. The airflow inclination affects wind turbine performance and also affects the cup anemometer being used in power performance measurements. In this article the overall dependence of the power curve on inclined airflow is analysed for its influence on both the wind turbine and the cup anemometer. The wind turbine performance analysis is based on results of measurements and theoretical calculations with the aeroelastic code HAWC coupled to a 3D actuator disc model for varying yaw angle. The cup anemometer analysis at inclined flow is based on an averaging of measured angular characteristics in a wind tunnel with the distribution of airflow inclination angles over time. The relative difference in annual energy production in terrain with inclined airflow compared with flat terrain is simulated for cup anemometers with theoretical optimal angular characteristics for two different definitions of wind speed, as well as for five commercial cup anemometers with measured angular characteristics. Copyright © 2004 John Wiley & Sons, Ltd.     

Optimal positioning of wind turbines on Gökçeada using multi‐objective genetic algorithm

This paper addresses the problem of optimal placement of wind turbines in a farm on Gokçeada Island located at the north‐east of Aegean Sea bearing full potential of wind energy generation. A multi‐objective genetic algorithm approach is employed to obtain optimal placement of wind turbines by maximizing the power production capacity while constraining the budget of installed turbines. Considering the speed and direction history, wind with constant intensity from a single direction is used during optimization. This study is based on wake deficit model mainly because of its simplicity, accuracy and fast calculation time. The individuals of the Pareto optimal solution set are evaluated with respect to various criteria, and the best configurations are presented. In addition to best placement layouts, results include objective function values, total power output, cost and number of turbines for each configuration. Copyright © 2009 John Wiley & Sons, Ltd.     

Quantification of power losses due to wind turbine wake interactions through SCADA,meteorological and wind LiDAR data

Power production of an onshore wind farm is investigated through supervisory control and data acquisition data, while the wind field is monitored through scanning light detection and ranging measurements and meteorological data acquired from a met‐tower located in proximity to the turbine array. The power production of each turbine is analysed as functions of the operating region of the power curve, wind direction and atmospheric stability. Five different methods are used to estimate the potential wind power as a function of time, enabling an estimation of power losses connected with wake interactions. The most robust method from a statistical standpoint is that based on the evaluation of a reference wind velocity at hub height and experimental mean power curves calculated for each turbine and different atmospheric stability regimes. The synergistic analysis of these various datasets shows that power losses are significant for wind velocities higher than cut‐in wind speed and lower than rated wind speed of the turbines. Furthermore, power losses are larger under stable atmospheric conditions than for convective regimes, which is a consequence of the stability‐driven variability in wake evolution. Light detection and ranging measurements confirm that wind turbine wakes recover faster under convective regimes, thus alleviating detrimental effects due to wake interactions. For the wind farm under examination, power loss due to wake shadowing effects is estimated to be about 4% and 2% of the total power production when operating under stable and convective conditions, respectively. However, cases with power losses about 60‐80% of the potential power are systematically observed for specific wind turbines and wind directions. Copyright © 2017 John Wiley & Sons, Ltd.     

Reliability-based topology optimization for offshore wind farm collection system

An optimization framework for global optimization of the cable layout topology for offshore wind farm (OWF) is presented. The framework designs and compares closed-loop and radial layouts for the collection system of OWFs. For the former, a two-stage stochastic optimization program based on a mixed integer linear programming (MILP) model is developed, while for the latter, a hop-indexed full binary model is used. The purpose of the framework is to provide a common base for assessing both designs economically, using the same underlying contingency treatment. A discrete Markov model is implemented for calculating the cable failure probability, useful for estimating the time under contingency for multiple power generation scenarios. The objective function supports simultaneous optimization of (i) initial investment (network topology and cable sizing), (ii) total electrical power loss costs and (iii) operation costs due to energy curtailment from cable failures. Constraints are added accounting for common engineering aspects. The applicability of the full method is demonstrated by tackling three differently sized real-world OWFs. Results show that (i) the profitability of either topology type depends strongly on the project size and wind turbine rating. Closed loop may be a competitive solution for large-scale projects where large amounts of energy are potentially curtailed. (ii) The stochastic model presents low tractability to tackle large-scale instances, increasing the required computing time and memory resources. (iii) Strategies must be adopted in order to apply stochastic optimization for modern OWFs, intending analytically or numerically simplification of mathematical models.     

Coordinated control of TCPS and SMES for frequency regulation of interconnected restructured power systems with dynamic participation from DFIG based wind farm

Among the several wind generation technologies, variable-speed wind turbines utilizing doubly fed induction generators (DFIG) are gaining momentum in the power industry. Increased penetration of these wind turbine generators displaces conventional synchronous generators which results in erosion of system frequency. With this assertion, the paper analyzes the dynamic participation of DFIG for frequency control of an interconnected two-area power system in restructured competitive electricity market. Frequency control support function responding proportionally to frequency deviation is proposed to take out the kinetic energy of wind turbine for improving the frequency response of the system. Impacts of varying wind penetration in the system and varying active power support from DFIG on frequency control have been investigated. The presence of thyristor controlled phase shifter (TCPS) in series with the tie-line and Superconducting Magnetic Energy Storage (SMES) at the terminal of one area in conjunction with dynamic active power support from DFIG results in optimal transient performance for PoolCo transactions. Integral gains of AGC loop and parameters of TCPS and SMES are optimized through craziness-based particle swarm optimization (CRPSO) in order to have optimal transient responses of area frequencies, tie-line power deviation and DFIG parameters.