集群风电场出力统计指标建模与应用

发布时间：2018-01-03 22:03

本文关键词：集群风电场出力统计指标建模与应用　出处：《电力自动化设备》2015年12期 　论文类型：期刊论文

【摘要】：基于概率统计理论,建立单个风电场与集群风电场出力的中心矩关系模型。从风电出力概率分布特性的角度,引入描述风电出力"分布形状"的2个统计学指标——偏度和峰度。基于集群风电出力均值、标准差、偏度和峰度4个统计性指标,构建表征集群风电出力概率分布的皮尔逊族模型,模拟集群风电场出力时序数据,进而得到集群风电场出力曲线。基于对区域典型风电集群历史出力数据的分析,根据经验建立风电场间相关系数与风电场间距离的指数关系模型,并给出区域风电场各阶标准差与平均出力之间的近似多项式关系模型,降低了计算核心指标所需数据维度。对福建省集群风电场进行实例应用分析,结果验证了所提集群风电场模型的准确性和实用性。
[Abstract]:Based on the theory of probability and statistics, a model of the central moment relationship between a single wind farm and a cluster wind farm is established, from the point of view of the probability distribution characteristics of the wind power output. This paper introduces two statistical indexes to describe the "distribution shape" of wind power output, namely bias and kurtosis, based on four statistical indexes: mean value, standard deviation, deviation and kurtosis. The Pearson family model, which is used to characterize the probability distribution of cluster wind power output, is constructed to simulate the cluster wind farm output time series data. Based on the analysis of the historical output data of regional typical wind power cluster, the exponential relationship model between the correlation coefficient of wind farm and the distance between wind farm and wind farm is established according to the experience. The approximate polynomial relation model between the standard deviation of each order and the average output force of regional wind farm is given, which reduces the data dimension required to calculate the core index. The example of cluster wind farm in Fujian Province is analyzed. The results verify the accuracy and practicability of the proposed cluster wind farm model.
【作者单位】：南京工程学院电力工程学院;东南大学电气工程学院;国网江苏省电力公司检修分公司南京分部;国网福建省电力有限公司经济技术研究院;国网江苏省电力公司南通供电公司;
【基金】：国家科技支撑计划项目(2013BAA01B02) 江苏省自然科学基金资助项目(BK20130742) 南京工程学院校级科研基金资助项目(YKJ201316)~~
【分类号】：TM614
【正文快照】： 0引言由于受到自然特性、地理环境、风电场自身条件等因素影响,风电出力表现出随机波动性。随着大规模风电并网,风电集群的波动特性研究对于电力系统运行和规划意义重大,引起了广泛的关注和研究兴趣,国内外针对风电出力特性[1]、调峰特性[2]、并网影响性[3-4]、随优化调度[5]

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