摘要
基于实测风电数据的风电功率波动特性分析能提高电网调度等部门对风力发电电源特性的认识,缓解风电并网给系统带来的不利影响。由于风电数据常常涉及到不同数据采集方法,因此有必要分析风电数据采集方法对风电功率波动特性分析的影响。本文根据东北某风电场的实测功率数据,通过间隔取点法和间隔平均值法获得不同功率数据序列进行风电功率波动特性分析。算例分析表明,不同的数据采集方法会对风电功率波动特性分析产生影响,且间隔取点法下的风电功率数据适用于风电功率预测,间隔平均值法下的风电功率数据适用于风电功率波动的概率密度特性分析。
The analysis of wind power fluctuation based on measured wind power data can improve the understanding of the electrical source characteristics of wind power generation to some departments such as power dispatching center, and alleviate the adverse effects caused by the wind power grid - connected. Because of the wind power data often involve in different data acquisition methods, therefore, it is necessary to analyze the influence of wind power data acquisition methods on the analysis of wind power fluctuation characteristics. This paper uses the measured power data of a wind farm in Northeast China, achieves different power data series by interval point method and interval average value method for wind power fluctuation analysis. Simulation results proved different data acquisition methods can influence the conclusion of wind power fluctuation analysis, data obtained by interval point method is suit for the analysis of probability density characteristics of wind power fluctuation, and data obtained by interval average value method is suit for wind power prediction.
出处
《电力大数据》
2017年第9期65-70,共6页
Power Systems and Big Data
关键词
风电功率波动特性
数据采集方法
概率密度特性
风电功率预测
wind power fluctuation characteristics
data acquisition methods
probability density characteristics
wind power prediction
