Simulation of aggregate wind farm short-term production variations

The variability of wind power production poses the greatest challenge in the integration of large-scale wind power in power systems. Furthermore, larger-scale penetration implies a wider geographical spreading of installed wind power, resulting in reduced variability and the smoothing effect of total power generation. Therefore, analysis of the impact of wind power variations on power system operation requires adequate modeling of aggregate power output from geographically dispersed wind farms. This paper analyzes different aspects of Markov chain Monte Carlo simulation methods for the synthetic generation of dependent wind power time series. However, testing indicates that these approaches do not adequately model the stochastic dependence between wind power time series in conjunction with individual persistence which is necessary to obtain realistic distributions of aggregate power output and total power variations. Consequently, a novel approach based on a modified second-order Markov chain Monte Carlo simulation is proposed. Simulation results show that this method obtains synthetic time series of aggregate wind power which very closely fit the original data, with respect to both the cumulative density function of total output power and the probability density function of power variations.     

Output power control for large wind power penetration in small power system

Nowadays, wind turbine generator (WTG) is increasingly required to provide control capabilities regarding output power. Under this scenario, this paper proposes an output power control of WTG using pitch angle control connected to small power systems. By means of the proposed method, output power control of WTG considering states of power system becomes possible, and in general both conflicting objectives of output power leveling and acquisition power increase are achieved. In this control approach, WTG is given output power command by fuzzy reasoning which has three inputs for average wind speed, variance of wind speed, and absolute average of frequency deviation. Since fuzzy reasoning is used, it is possible to define output power command corresponding to wind speed condition and changing capacity of power system momentarily. Moreover, high performance pitch angle control based on output power command is achieved by generalized predictive control (GPC). The simulation results by using actual detailed model for wind power system show the effectiveness of the proposed method.     

基于偏航尾流模型的风电场功率协同优化研究

为减小风电场尾流效应的影响,提升风电场整体发电量,提出一种基于偏航尾流模型的风电场功率协同优化方法。首先建立风电场偏航尾流模型,该模型包括用于计算单机组尾流速度分布的Jensen-Gaussian尾流模型、尾流偏转模型及多机组尾流叠加模型,对各机组风轮前来流风速进行求解;再根据来流风速计算风电场输出功率,并以风电场整体输出功率最大为优化目标,利用拟牛顿算法协同优化各机组轴向诱导因子和偏航角度。以4行4列方形布置的16台NREL-5 MW风电机组为对象进行仿真研究。结果表明,所提出的基于偏航尾流模型的风电场功率协同优化方法能显著提升风电场整体输出功率。     

Output power dispatch control for a wind farm in a small power system

Nowadays, a wind turbine generator (WTG) is required to provide control capabilities as the output power of WTG fluctuates. Under this scenario, this paper proposes an output power control method of a wind farm (WF) connected to a small power system using pitch angle control. In this control approach, the WF output power control is achieved by two control levels: central and local. In the central control, the WF output power command is determined by considering the frequency deviations and wind speeds using a fuzzy function. Then, the local output power commands for each of the WTGs are based on the proposed dispatch control. In the proposed dispatch control, the output commands of each WTG are determined by considering wind conditions for each of the WTGs. The simulation results by using an actual detailed model for the wind power system show the effectiveness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.     

基于加装叶尖小翼风电机组发电量提升试验研究

针对老旧风电场由于风电机组风轮和风资源未能很好匹配等原因导致的发电量不理想问题,提出一种基于加装叶尖小翼风电机组发电量提升方法,该方法在增加叶片扫掠面积的同时有效改善叶片的气动性能。通过加装叶尖小翼增加叶尖部分切向力,增加主轴扭矩从而提高风轮吸收功率,达到提升发电量的目的。基于风电场实际试验数据对提功增效效果进行分析,结果表明所提方法在满足安全性的前提下可有效提高机组输出功率,提升发电量。同时该方法成本低,展现了良好的性价比。     

基于TPNT含风电场发输电组合系统可靠性评估

为克服含风电场可靠性评估中需已知风速分布函数的缺点,提出了一种基于三阶多项式正态变换(TPNT)的非序贯蒙特卡洛模拟法评估含风电场发输电系统的可靠性。在已知风速历史数据或风速分布函数的情况下,通过TPNT构建风速随机变量与标准正态分布变量的关系,进而利用标准正态分布函数的性质产生具有任意数量的具有指定相关性的风速样本,并应用于风电场接入的发输电系统可靠性计算中。通过算例分析验证了TPNT应用于发输电系统可靠性计算中的适用性。在此基础上,从风速相关性、额定容量、风资源强度和风电场位置四个角度分析了风电场接入对可靠性的影响。为含风电场发输电系统可靠性的评估提供了新思路。     

Application analysis of a superconducting fault current limiter-magnetic energy storage system for the wind farm

风力发电所面临的两大重要问题是低电压穿越能力弱和功率输出不稳定。为了同时解决这两个问题,我们提出了超导限流-储能系统,并进行了单机系统的仿真研究,证实了该方案的有效性。然而对于风电场的应用,目前尚无研究。本文将超导限流-储能系统的应用扩展到风电场,分析了其提高低电压穿越能力和稳定有功功率输出的机理,并进行了仿真研究。从仿真结果来看,超导限流-储能系统能够同时提高风电场所有风机的低电压穿越能力,并能有效地平滑整个风电场的有功输出功率。考虑不同风机的互补效应,将该系统应用于风力发电场与直接应用于单台风机相比,其储能量和功率输出的要求可以大大降低,从而可以有效地减少系统总成本,因而具有更好的应用前景。     

Prioritization of potential locations for harnessing wind energy to produce hydrogen in Afghanistan

Due to the devastating ecological effects and constrained reserves of fossil fuels, renewable energies are now globally accepted as viable alternative sources of energy. Among renewable energy sources, wind energy has become globally popular, primarily because wind farms can be rapidly built and easily maintained at a relatively low cost. Wind-powered hydrogen production is an effective solution for storing the excess energy output of wind farms. The hydrogen produced in this way can be used not only in fuel cells but also in cooling, oil, gas, and petrochemical fields. As a country devastated by war and instability, Afghanistan has major energy generation challenges and a substantially large power supply deficiency. However, there are good wind energy potentials in several parts of this country. There are also several hydrogen-consuming fields in Afghanistan that can benefit from hydrogen production from wind energy. This paper endeavored to distinguish the appropriate areas in Afghanistan for harvesting wind energy for hydrogen production using multi-criteria decision-making techniques. Eleven criteria were utilized to prioritize 20 Afghan provinces with wind energy potential. The Step-wise Weight Assessment Ratio Analysis (SWARA) was utilized to weight the criteria and Evaluation based on Distance from Average Solution (EDAS) were utilized to prioritize the provinces. Then, ARAS, TOPSIS, and VIKOR methods were used to validate the resultants. For criteria weighting with SWARA, “wind speed”, “wind power density” and “area of windy regions” with weights of 0.1423, 0.1356, and 0.1221 were introduced as the most significant criteria for this ranking. In all the rankings, Herat, Farah, and Jowzjan were identified as the top three most suitable provinces for wind power generation. The power output and hydrogen output to be achieved in Herat province using a 900-kW turbine were estimated to 2558.4 MW per year and 41.4 tons per year, respectively.     

Optimizing hybrid offshore wind farms for cost-competitive hydrogen production in Germany

Nearly 96% of the world's current hydrogen production comes from fossil-fuel-based sources, contributing to global greenhouse gas emissions. Hydrogen is often discussed as a critical lever in decarbonizing future power systems. Producing hydrogen using unsold offshore wind electricity may offer a low-carbon production pathway and emerging business model. This study investigates whether participating in an ancillary service market is cost competitive for offshore wind-based hydrogen production. It also determines the optimal size of a hydrogen electrolyser relative to an offshore wind farm. Two flexibility strategies for offshore wind farms are developed in this study: an optimal bidding strategy into ancillary service markets for offshore wind farms that build hydrogen production facilities and optimal sizing of Power-to-Hydrogen (PtH) facilities at wind farms. Using empirical European power market and wind generation data, the study finds that offshore-wind based hydrogen must participate in ancillary service markets to generate net positive revenues at current levels of wind generation to become cost competitive in Germany. The estimated carbon abatement cost of “green” hydrogen ranges between 187 EUR/tonCO₂e and 265 EUR/tonCO₂e. Allowing hydrogen producers to receive similar subsidies as offshore wind farms that produce only electricity could facilitate further cost reduction. Utilizing excess and intermittent offshore wind highlights one possible pathway that could achieve increasing returns on greenhouse gas emission reductions due to technological learning in hydrogen production, even under conditions where low power prices make offshore wind less competitive in the European electricity market.     

基于链式分配策略的风氢耦合系统设计与控制

针对风力发电“弃风”电量耦合制氢问题,提出一种基于链式分配策略的风氢耦合系统。首先建立能表征弃风电量与质子交换膜电解槽主要特性的风氢耦合拓扑电路结构,围绕高降压比交错Buck变换器及其控制方法构建风氢耦合系统,并提出多堆质子交换膜电解槽风氢耦合系统链式功率分配策略。最后通过算例仿真验证该系统可提升弃风利用率和系统可靠性,可有效解决弃风电量水电解制氢耦合控制与功率分配问题。     

基于新能源发电的电解水制氢直流电源研究

利用新能源发电进行电解水制氢是实现新能源就地消纳和氢能利用的重要途径,以匹配电解水制氢工作特性的制氢电源为研究对象,通过分析质子交换膜电解槽电解电流、温度与电解槽端口电压、能量效率、制氢速度之间的关系,得出制氢电源需具备输出低电流纹波、输出大电流、宽范围电压输出的特性。为满足新能源电解制氢系统需求,提出一种基于Y型三相交错并联LLC拓扑结构的制氢电源方案,该方案谐振腔三相交错并联输出,满足电解槽大电流低纹波工作特性,并采用脉冲频率控制实现谐振软开关,提高变换效率。最后,搭建仿真模型和6 kW模块化实验样机,验证所提出方案的合理性与可行性。     

考虑电转气消纳风电的电-气综合能源系统两阶段鲁棒协同调度

针对传统随机规划方法和区间优化方法处理风电出力不确定性的不足之处,该文提出含电转气设备的电力-天然气综合能源系统两阶段鲁棒协同调度模型,并考虑天然气网络运行约束对燃气轮机和电转气设备调度出力及备用配置的影响。模型以风电基准场景下系统的日前调度运行成本及最劣风电场景下实时调度成本之和为目标函数,建立具max-min结构的双层优化模型,并在主/子问题求解框架下采用列约束生成（C&CG）方法进行求解。最后,在Matlab平台下构建仿真算例验证所提鲁棒协同调度模型的有效性。     

Hydrogen production from idle generation capacity of wind turbines

This paper is concerned with the hydrogen production from wind energy. It is motivated by the new regulations for wind farms that compel them to operate normally with idle generation capacity. The idea is to use the excess wind power to produce hydrogen. The operation of a proposed system configuration, which essentially consists in incorporating an electrolyzer between the electronic converters of a conventional wind turbine, is analyzed. In particular, the control requirements to simultaneously achieve the grid and electrolyzer specifications are investigated. In this context, a control strategy for the different operating modes of the system is developed.     

风电场接入电力系统最佳接入点选择

分析了风力发电的特性,建立了基于双馈感应风力发电机(Doubly-Fed Induction Generator,DFIG)的风力发电系统的动态数学模型。利用MATLAB/Simulink仿真软件,对风电场接入典型电力系统的接入点选择进行了仿真。仿真结果表明,通过合理选择风电场的接入点,可以减小风电场对电力系统的影响。     

应用STATCOM提高风电场的电压稳定性

风能具有随机性和间歇性,大规模风电场接入电网时会对系统的稳定性产生一定的影响。建立了风力发电机组模型,仿真分析了利用STATCOM改善风电场（由变桨距定速异步感应发电机组成）的静态和暂态稳定性。仿真结果表明,STATCOM可以有效地改善风电场的稳定性,在系统故障后提供无功支撑,提高了风电场的低电压穿越能力。     

风电场风功率实时预测效果综合评价方法

超短期风电功率预测对含大规模风电的电力系统安全经济运行有着重要意义。但目前对预测结果的评价均停留在常规统计学指标上,缺乏合理的评价体系来评价某特定风电场所选取预测模型的优劣。简述了目前风电功率预测结果评价指标的不足,提出一种基于预测误差评价和预报考核等指标的风电场输出功率实时预测效果评估方法,为不同地区风电场根据其风电输出功率变化的特点,选择预测模型以及风电场输出功率预测效果的工程检验提供依据。最后,利用吉林省某风电场实测数据,采用该评估方法对不同预测模型的实时预测结果进行分析评价,实现了该风电场不同预测模型间的择优,验证了该评价方法的指导价值。     

基于电池储能系统和双重扩展卡尔曼滤波的风能发电智能调度技术研究

风能等新能源发电系统在供电体系中的占比越来越大,但其随机性和波动性问题,将风力发电厂输出的电力直接向电网调度会造成安全隐患。为了解决这一问题,基于电池储能系统提出了一种风能发电智能调度技术,该技术以风力发电动力学模型和电池储能系统状态模型为基础,利用双重扩展卡尔曼滤波算法实现了风能发电系统的稳定输出。以某地风速实测数据和电网需求功率为参考,对不同算法的输出功率预测值进行了仿真分析和实验对比。结果表明：提出的改进算法预测的风速值误差相比于传感器观测值平均误差降低了28%以上,可以更准确地提供发电系统输出功率;提出的智能调度技术可以使电压波动幅度降低60%以上,系统整体输出功率稳定在参考功率附近,误差不超过2%,有一定的实用意义。     

Fuzzy copula model for wind speed correlation and its application in wind curtailment evaluation

Wind parks always produce diverse percentages of their nominal power at the same time, leading to a concern about correlation between wind speeds. The assessments of wind speed correlation have been particularly focused on probabilistic modeling of aleatory uncertainty. However, poor historical data, imprecise parameter estimation and incomplete knowledge of wind speeds lead to another type of uncertainty, possibilistic uncertainty, which requires an explicit analysis. Therefore, a fuzzy copula model is firstly proposed to express the possibilistic uncertainty of wind speed correlation. The advantage of the proposed model is that the copula parameters can be interval numbers, triangular or trapezoidal fuzzy numbers based on the wind speed data and subjective judgment of decision makers. For estimating copula parameters, a complete decision rule and interval estimation method is developed based on cumulative probability and probability distributions of correlated wind speeds. The effectiveness of the proposed model is validated by the application in wind curtailment evaluation while a method is developed to evaluate and quantify wind curtailment in a hybrid power system involving different types of generation. The results demonstrate that the proposed model and method are capable of describing the possibilistic uncertainty and evaluating its effect on wind curtailment. Compared with previous research, the proposed model develops a new universal parameter estimation method and selection rule to provide more interval results, by calculating the membership function of copula parameters and wind curtailment. System planners and operators can apply the fuzzy results to various topics like reserve capacity evaluation or real-time dispatch depending on their level of risk tolerance.     

Optimization of wind turbine micro-siting for reducing the sensitivity of power generation to wind direction

In the optimization of wind turbine micro-siting of wind farms, the major target is to maximize the total energy yield. But considering from the aspect of the power grid, the sensitivity of wind power generation to varying incoming wind direction is also an essential factor. However, most existing optimization approaches on wind turbine micro-siting are focused on increasing the total power yield only. In this paper, by employing computational fluid dynamics and the virtual particle model for the simulation of turbine wake flow, a sensitivity index is proposed to quantitatively evaluate the variation of power generation under varying wind direction. Typical turbine layouts obtained by existing power optimization approaches are evaluated for stability. Results indicate that regularly arranged turbine layouts are not suitable for stable power production. Based on solutions from the power optimization, a second-stage optimization using Particle Swarm Optimization algorithm is presented. The proposed optimization method adjusts the positions of the turbines locally, aiming at increasing the stability of wind farm power generation without damaging its advantage of high power yield. Case studies on flat terrain and complex terrain both demonstrate the effectiveness of the present local adjustment optimization method.     

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.