考虑相关性的风电场等值及概率潮流计算研究

发布时间：2018-08-08 15:49

【摘要】：随着风力发电技术日趋成熟,新建风电场趋于大型化和集中化,风电固有的随机性、波动性和相关性为电力系统安全运行带来巨大挑战。概率潮流是研究风电并网对系统运行影响的有力工具。针对含风电系统潮流计算问题,研究了单风电场内风机等值模型、多风电场间风速相关性模型及考虑相关性的概率潮流计算方法。提出了新的等值建模及概率潮流算法,为电力系统的经济调度以及安全分析提供了新的思路。为了在保证风机等值精度的基础上降低风电场仿真模型的复杂度,考虑到实际风电场内尾流效应及风机控制方式不同的情况,借鉴层次分析法的思想提出了两步分群法。考虑风电机组间尾流效应计算输入风速,根据机组桨距角动作情况进行初次分群,通过转子电流受扰曲线识别动态特性相近的风机实现再次分群。在保证风电机组功率输出特性和电压差恒定的基础上,进行风机和集电线路参数等值,得到了风电场多机等值模型。仿真算例表明,与传统等值方法相比,该模型能精确地反映风机初始运行点以及动态特性。多风电场间风速存在不同程度的相关性,选择最佳Copula函数是相关性建模的关键。采用非参数核密度估计风速边缘分布,在单一拟合度评价指标的基础上引入Copula熵作为相关性评价指标,提出一种基于熵权模糊综合评价的Copula函数优选方法。通过所优选的Copula函数进一步建立风电场出力相关性模型,以华北地区两个风电场为例验证模型的合理性。针对现有概率潮流计算方法存在计算精度和速度之间的矛盾,引入一种基于Nataf变换的概率潮流三点估计法。该方法能够有效的处理风电场间出力的相关性,并能在缩短计算时间的基础上保证计算精度。分别采用该方法与蒙特卡洛法对含多风电场的IEEE30节点系统进行概率潮流计算,将二者计算结果进行对比,验证了该方法的高效性和精确性。
[Abstract]:With the development of wind power generation technology, new wind farms tend to be large-scale and centralized. The inherent randomness, volatility and correlation of wind power bring great challenges to the safe operation of power system. Probabilistic power flow is a powerful tool to study the influence of wind power grid on system operation. Aiming at the problem of power flow calculation in wind power system with wind power, the equivalent model of wind turbine in a single wind farm, the model of wind speed correlation between multi-wind farms and the calculation method of probabilistic power flow considering the correlation are studied. A new equivalent modeling and probabilistic power flow algorithm is proposed, which provides a new idea for economic dispatch and security analysis of power system. In order to reduce the complexity of wind farm simulation model on the basis of ensuring the equivalent precision of wind turbine, considering the different wake effect and fan control mode in actual wind farm, a two-step clustering method is proposed for reference to the idea of analytic hierarchy process (AHP). Considering the wake effect of wind turbines, the input wind speed is calculated, and the initial grouping is carried out according to the pitch angle of the units, and the fan with similar dynamic characteristics is identified by the disturbance curve of rotor current. On the basis of ensuring the constant power output characteristics and voltage difference of wind turbine, the equivalent parameters of fan and collector circuit are obtained, and the equivalent model of wind farm is obtained. The simulation results show that compared with the traditional equivalence method, the model can accurately reflect the initial operating point and dynamic characteristics of the fan. There is different correlation between wind speed in multi-wind farms, and the key of correlation modeling is to select the best Copula function. The nonparametric kernel density is used to estimate the edge distribution of wind speed. On the basis of a single fitness evaluation index, Copula entropy is introduced as the correlation evaluation index, and a Copula function optimization method based on fuzzy comprehensive evaluation of entropy weight is proposed. The model of wind farm output correlation is further established by the selected Copula function. Two wind farms in North China are taken as examples to verify the rationality of the model. In view of the contradiction between the accuracy and speed of the existing probabilistic power flow calculation methods, a three-point estimation method of probabilistic power flow based on Nataf transform is introduced. This method can effectively deal with the correlation between wind farm forces and ensure the calculation accuracy on the basis of shortening the calculation time. The probabilistic power flow calculation of IEEE30 node system with multi-wind farm is carried out by using this method and Monte Carlo method respectively. The results of the two methods are compared to verify the efficiency and accuracy of the method.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM614;TM744

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