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基于IKLIEP−四分位模型的风电场异常数据识别算法 被引量:4
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作者 杨茂 张书天 +2 位作者 王天硕 杨硕 赵辉 《高电压技术》 EI CAS CSCD 北大核心 2023年第7期2952-2960,共9页
风电场功率数据中包含大量异常数据,难以反映风电场真实的风能情况,会影响风电功率预测的精度,从而影响电网决策。针对该问题,通过分析风电场异常数据特征,将其分为堆积型和分散型,并基于时间序列变点检测理论,将密度比是否为恒值作为... 风电场功率数据中包含大量异常数据,难以反映风电场真实的风能情况,会影响风电功率预测的精度,从而影响电网决策。针对该问题,通过分析风电场异常数据特征,将其分为堆积型和分散型,并基于时间序列变点检测理论,将密度比是否为恒值作为剔除堆积型异常数据的判断准则,采用改进Kullback Leibler重要性估计程序(improved Kullback Leibler importance estimation program,IKLIEP)剔除堆积型异常数据;再采用四分位法剔除分散型异常数据。最后将所提方法应用于国内蒙西某130.5 MW的风电场,实验结果表明所提方法能够更有效地识别并剔除异常数据,平均识别率提高了6.19%,误识别率降低了2.92%,验证了所提方法的有效性。 展开更多
关键词 改进Kullback Leibler重要性估计程序 时间序列变点检测 密度比 四分位 风电场 异常数据
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Change Point Detection and Trend Analysis for Time Series
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作者 Hong Zhang Stephen Jeffrey John Carter 《Chinese Journal of Chemical Physics》 SCIE EI CAS CSCD 2022年第2期399-406,I0004,共9页
Trend analysis and change point detection in a time series are frequent analysis tools.Change point detection is the identification of abrupt variation in the process behaviour due to natural or artificial changes,whe... Trend analysis and change point detection in a time series are frequent analysis tools.Change point detection is the identification of abrupt variation in the process behaviour due to natural or artificial changes,whereas trend can be defined as estimation of gradual departure from past norms.We analyze the time series data in the presence of trend,using Cox-Stuart methods together with the change point algorithms.We applied the methods to the nearsurface wind speed time series for Australia as an example.The trends in near-surface wind speeds for Australia have been investigated based upon our newly developed wind speed datasets,which were constructed by blending observational data collected at various heights using local surface roughness information.The trend in wind speed at 10 m is generally increasing while at 2 m it tends to be decreasing.Significance testing,change point analysis and manual inspection of records indicate several factors may be contributing to the discrepancy,such as systematic biases accompanying instrument changes,random data errors(e.g.accumulation day error)and data sampling issues.Homogenization technique and multiple-period trend analysis based upon change point detections have thus been employed to clarify the source of the inconsistencies in wind speed trends. 展开更多
关键词 Time series Change point detection Trend analysis Wind speed HOMOGENIZATION
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