基于SCADA数据的风电机组运行状态评估方法研究

发布时间：2018-03-22 18:24

本文选题：SCADA数据　切入点：风电并网　出处：《华北电力大学》2014年硕士论文　论文类型：学位论文

【摘要】：当前，风电大规模并网使风力发电对电网影响越来越大，导致其他电源需要更高的调节能力来保证电网的调度运行和电网的故障水平与稳定性等。科学评价并网风电机组的运行状况，对完成大规模安全风力发电稳定并网运行拥有很大的科学意义。本文主要从风电功率特性的研究、风电机组性能评估模型的建立以及风电弃风电量评估模型的建立几个方面，进行了并网风电机组运行状态评估，开展了以下工作：（1）基于研究风电机组并网运行的基本原理，分析了并网风电机组运行基本信息，主要包括风电机组基本结构、基本类型和工作原理以及在线状态监测基本参量、主要部件的故障机理等；（2）针对并网风电机组的功率特性，提出了风电功率量化指标分析及利用正态分布函数拟合风电功率min级分量概率密度分布研究方法。主要包括：第一，，定义量化指标，并从差分时间尺度和风电场装机容量两个方面分析风电波动的特性；第二，选用二次滚动平均法分析风电场输出功率的min级分量，同时利用正态分布函数拟合min级分量概率密度分布，研究不同装机容量风电场和选择不同滚动窗口时风电功率min分量的概率分布；（3）考虑到风电机组本身运行的性能特性，研究并网运行风电机组性能的评估模型。在常规模糊数学评判模型基础上，首先，通过灰色系统理论获取指标权值，并引入变权理论对偏离指标进行修正；然后，采用劣化度指标建立隶属函数，建立基于SCADA（Supervisory Control and Data Acquisition）数据的风电机组性能状态评估模型，并通过实例验证；（4）提出弃风电量的评估模型。该方法是基于SCADA实时监测数据，对风速进行修正，计算风电场实际功率，从而确定风电场的理论发电量，并根据实际发电量，得到风电场的弃风电量。以上研究成果可应用于风电机组并网运行状态评估，将为风电并网提供理论参考，保证并网风力发电机组的高可靠性，对实现风电机组大规模并网具有重要的科学实用价值和研究意义。
[Abstract]:At present, wind power generation is becoming more and more important to the power grid because of the large-scale grid connection of wind power. Therefore, other power sources need higher regulation ability to ensure the dispatching operation of the power network and the fault level and stability of the power network, etc. Scientific evaluation of the operation status of grid-connected wind turbines, It is of great scientific significance to complete the stable grid operation of large-scale safe wind power generation. This paper mainly focuses on the research of wind power characteristics, the establishment of wind turbine performance evaluation model and the establishment of wind power abandoned wind power evaluation model. The operation status of grid-connected wind turbine is evaluated, and the following work is carried out:. 1) based on the study of the basic principle of wind turbine grid connected operation, the basic information of wind turbine operation is analyzed, including the basic structure, basic type and working principle of wind turbine unit, and the basic parameters of on-line condition monitoring. Failure mechanism of main components; 2) aiming at the power characteristic of grid-connected wind turbine, the paper puts forward a method to analyze the quantization index of wind power and to fit the probability density distribution of min component of wind power by normal distribution function. The main contents are as follows: firstly, the quantization index is defined. The characteristics of wind power fluctuation are analyzed from two aspects: difference time scale and wind farm installed capacity. Secondly, the min stage component of wind farm output power is analyzed by using the quadratic rolling average method. At the same time, the probability density distribution of min stage component is fitted by normal distribution function, and the probability distribution of wind power min component under different installed capacity wind farm and different rolling window is studied. Considering the performance characteristics of wind turbine, the evaluation model of wind turbine performance in grid-connected operation is studied. On the basis of conventional fuzzy mathematics evaluation model, the index weights are obtained by grey system theory. The variable weight theory is introduced to modify the deviation index, and then the membership function is established by using the deterioration degree index, and the performance evaluation model of wind turbine based on SCADA(Supervisory Control and Data requirements data is established, and the model is verified by an example. This method is based on the real-time monitoring data of SCADA, modifies the wind speed, calculates the actual power of the wind farm, and determines the theoretical power generation of the wind farm. Get the abandoned wind power from the wind farm. The above research results can be applied to the evaluation of wind turbine grid-connected operation status, which will provide a theoretical reference for wind power grid connection and ensure the high reliability of grid-connected wind turbine. It has important scientific and practical value and research significance for realizing large-scale grid connection of wind turbine.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM315

【参考文献】