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文章摘要
基于动态时间规整的负荷主要生产时段特征提取方法
A Method of Extracting the Main Production Period Based on Dynamic Time Warping
Received:April 02, 2020  Revised:April 10, 2020
DOI:10.19753/j.issn1001-1390.2023.08.009
中文关键词: 生产时段  动态时间规整  负荷特征  辨识
英文关键词: main production period, Dynamic Time Warping (DTW), load characteristics, recognition
基金项目:
Author NameAffiliationE-mail
tangwei* State Grid Sichuan Electric Power Research Institute tangwei38030821@163.com 
Luo Xiaoyi State Grid Sichuan Electric Power Company luoxy@sc.sgcc.com.cn 
Teng Yufei State Grid Sichuan Electric Power Research Institute yfteng2011@163.com 
Li Jian University of Electronic Science and Technology of China leejian@uestc.edu.cn 
Jin Dan State Grid Sichuan Electric Power Research Institute jind0429@sc.sgcc.com.cn 
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中文摘要:
      针对经济活跃程度和复工复产重要评估依据中负荷主要生产时段提取偏差大的问题,文章提出了基于动态时间规整(DTW)的负荷主要生产时段特征提取方法,通过构建参考负荷曲线,将测试负荷曲线与参考负荷曲线进行时间维度的伸缩变换,达到测试与参考负荷曲线间的最佳映射,进而实现了测试负荷主要生产时段的测算。文章以西南某区域典型商业负荷功率数据为案例进行负荷主要生产时间段提取,分析了异常测量数据对动态时间规整算法辨识主要生产时段的影响,实验结果证明了文章所提方法在辨识主要生产时段方面的有效性和准确性。
英文摘要:
      The production period is one of the main characteristics in the evaluation of economic activity level and enterprise recovery degree. Focused on the large deviation problem in the main production time extracting process, this paper proposes to adopt Dynamic Time Warping (DTW) to the measurement of main production period of power loads. After constructing a reference load curve, the DTW method is adopted to realize the optimal mapping of the test curve and the reference curve by the stretch out or draw back the two curves in time dimension. Then, the main production period of test load could be calculated by searching in the optimal warping path table. Finally, the effectiveness of the method is verified with experimental results of typical load curves from a southwest district. This paper also analyzes the influence of abnormal measurement data on the recognition of main production period. Meanwhile, the comparison results show that the main production period calculated with algorithm proposed in this paper is more accurate than the method of identifying the rising and falling points.
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