基于数字信号处理的风电功率日周期性研究  

Study on day periodicity of wind farm output active power based on digital signal processing

作　　者：杨茂[1] 齐玥[1] 孙勇[2] 郑太一[2] 蔡宏毅 韩金釜 

机构地区：[1]东北电力大学微通电力研究室,吉林吉林132012 [2]吉林省电力有限公司调度中心,吉林长春130021 [3]国网黑龙江电力有限公司检修公司,黑龙江哈尔滨150090

出　　处：《电力系统保护与控制》2014年第17期107-112,共6页Power System Protection and Control

基　　金：国家重点基础研究发展计划项目(973计划)(2013CB228201);国家自然科学基金项目(51307017);吉林省产业技术研究与开发专项项目(JF2012C018);吉林省科技发展计划项目(20140520129JH);吉林市科技发展计划资助项目(2013625004)~~

摘　　要：风电功率具有波动性和间歇性,大规模风电并网对电网运行产生不利影响。主要对风电功率波动特性进行分析。基于数字信号处理,将风电功率数据作为数字信号进行处理。通过自相关系数分析发现风电功率数据具有一定的周期性。利用有限傅里叶分解提取日周期分量,并从能量角度分析了日周期分量在不同时间尺度和不同装机容量下的分布特性。日周期分量在风电功率中所占比例随时间和空间的不同发生变化。时间段越长日周期分量所占比例越小;随着风电场数量的增加,日周期分量所占比例将明显增加。Wind power is fluctuating and intermittent. Large scale wind power integration has an adverse impact on the power grid operation. This paper analyzes the characteristics of wind power fluctuations. It takes the wind power data as digital signal to process, based on digital signal processing. By means of analyzing autocorrelation coefficient, we find that fluctuation has a certain periodicity. Day periodicity component is extracted though finite Fourier decomposition. From the energy point of view, day periodicity component distribution is analyzed in different time scales and different installed capacity. The proportion of the periodic component changs with time and space of wind power. The longer the time period, the periodic component proportion is smaller. Along with the increase of the number of wind farms, periodic component proportion will increase signigicantly.

关 键 词：风电功率 波动特性 日周期分量 能量 分布特性 

分 类 号：TM614[电气工程—电力系统及自动化]