基于时间序列相似性度量的新能源-负荷特性指标
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摘要
为满足新能源高渗透率电力系统在曲线性状、特征、度量上对负荷特性指标的新需求,提出一种将新能源出力和用电负荷曲线的负荷特性指标拓展为可表达其相互关系的新能源-负荷特性指标。计及数据分布特性与形态波动特征,改进时间序列相似性度量方法,将欧氏距离与改进后的动态时间弯曲距离相结合求取负荷曲线和新能源出力曲线的相似性距离,将其定义为源荷相似性距离作为新能源-负荷特性指标。算例表明,所提指标比传统负荷特性指标能更有效描述新能源高渗透率电力系统负荷特性。
In order to meet the new demand of new energy high-permeability power system on load characteristic index in terms of curve traits,characteristics and measures,a new energy-load characteristic index is proposed,which is expanded from the load characteristic index of new energy output and power load curve to express their relation. Considering the characteristics of data distribution and morphological fluctuation,the time series similarity measure method is improved,and the similarity distance between load curve and new energy output is obtained with the combination of Euclidean distance and the improved dynamic time warping distance,which is defined as source-load similarity distance and taken as the new energy-load characteristic index. Case shows that the proposed index can describe the load characteristic of new energy high-permeability power system more effectively than the traditional load characteristic index.
In order to meet the new demand of new energy high-permeability power system on load characteristic index in terms of curve traits,characteristics and measures,a new energy-load characteristic index is proposed,which is expanded from the load characteristic index of new energy output and power load curve to express their relation. Considering the characteristics of data distribution and morphological fluctuation,the time series similarity measure method is improved,and the similarity distance between load curve and new energy output is obtained with the combination of Euclidean distance and the improved dynamic time warping distance,which is defined as source-load similarity distance and taken as the new energy-load characteristic index. Case shows that the proposed index can describe the load characteristic of new energy high-permeability power system more effectively than the traditional load characteristic index.
引文
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[17] 龚薇,刘俊勇.计及负荷波动率和互补系数的负荷恢复[J].电网技术,2014,38(9):2490-2496.GONG Wei,LIU Junyong.Load recovery considering load fluctuation and complementary coefficients[J].Power System Technology,2014,38(9):2490-2496.
[18] 卫志农,张思德.计及电转气的电 - 气互联综合能源系统削峰填谷研究[J].中国电机工程学报,2017,37(16):4601-4609,4885.WEI Zhinong,ZHANG Side.Research on peak load filling in electricity and gas interconnected integrated energy system considering electric rotation gas[J].Proceedings of the CSEE,2017,37(16):4601-4609,4885.
[19] 杨玉青,牛利勇.考虑负荷优化控制的区域配电网储能配置[J].电网技术,2015,39(4):1019-1025.YANG Yuqing,NIU Liyong.Analysis of energy storage configuration in regional distribution network considering load optimization control[J].Power System Technology,2015,39(4):1019-1025.
[2] 牛林华,龚庆武.大规模风电入网下的风气火电力系统联合优化调度[J].电力自动化设备,2015,35(11):52-58.NIU Linhua,GONG Qingwu.Joint optimization of wind power and fire power system under large-scale wind power network[J].Electric Power Automation Equipment,2015,35(11):52-58.
[3] 刘文颖,文晶.考虑风电消纳的电力系统源荷协调多目标优化方法[J].中国电机工程学报,2015,35(5):1079-1088.LIU Wenying,WEN Jing.Multi-objective optimization of power system source-load coordination considering wind power consumption[J].Proceedings of the CSEE,2015,35(5):1079-1088.
[4] 刘思,李林芝.基于特性指标降维的日负荷曲线聚类分析[J].电网技术,2016,40(3):797-803.LIU Si,LI Linzhi.Calculation of daily load curve based on dimensionality reduction of characteristic indexes[J].Power System Technology,2016,40(3):797-803.
[5] 丁明,黄冯,邹佳芯,等.改进谱聚类与遗传算法相结合的电力时序曲线聚类方法[J].电力自动化设备,2019,39(2):93-99,114.DING Ming,HUANG Feng,ZOU Jiaxin,et al.A power time series curve clustering method based on improved spectral clustering and genetic algorithm[J].Electric Power Automation Equipment,2019,39(2):93-99,114.
[6] BENITEZ I,DIEZ J.Dynamic clustering of residential electricity consumption time series data based on Hausdorff distance[J].Electric Power Systems Research,2016,140:517-526.
[7] 于之虹,黄彦浩.基于时间序列关联分析的稳定运行规则提取方法[J].中国电机工程学报,2015,35(3):519-526.YU Zhihong,HUANG Yanhao.A method for extracting stable opera-tion rules based on time series correlation analysis[J].Proceedings of the CSEE,2015,35(3):519-526.
[8] 吴虎胜,张凤鸣.多元时间序列相似性研究综述[J].统计与决策,2014(7):77-81.WU Husheng,ZHANG Fengming.Review of multivariate time series similarity research[J].Statistics and Decision,2014(7):77-81.
[9] CAI Q,CHEN L.Piecewise statistic approximation based similarity measure for time series[J].Knowledge-Based Systems,2015,85:181-195.
[10] SUN Youqiang,LI Jiuyong,LIU Jixue,et al.An improvement of symbolic aggregate approximation distance measure for time series[J].Neurocomputing,2014,138:189-198.
[11] ?UCZAK M.Hierarchical clustering of time series data with parametric derivative dynamic time warping[J].Expert Systems with Applications,2016,62:123-135.
[12] CAO D,LIU J.Research on dynamic time warping multivariate time series similarity matching based on shape feature and inclination angle[J].Journal of Cloud Computing,2016,5(1):11-23.
[13] 王业,陆于平.基于动态时间弯曲的差动保护算法[J].中国电机工程学报,2012,32(28):133-141.WANG Ye,LU Yuping.Differential protection algorithm based on dynamic time bending[J].Proceedings of the CSEE,2012,32(28):133-141.
[14] 别朝红,胡国伟.考虑需求响应的含风电电力系统的优化调度[J].电力系统自动化,2014,38(13):115-120,159.BIE Zhaohong,HU Guowei.Optimization scheduling of wind power generation systems considering demand response[J].Automation of Electric Power Systems,2014,38(13):115-120,159.
[15] 张程飞,刘纯.基于模糊多目标优化的电网日前风电接纳能力评估模型[J].电网技术,2015,39(2):426-431.ZHANG Chengfei,LIU Chun.Evaluation model of wind power receptivity based on fuzzy multi-objective optimization[J].Power System Technology,2015,39(2):426-431.
[16] 李剑楠,乔颖.多时空尺度风电统计特性评价指标体系及其应用[J].中国电机工程学报,2013,33(13):53-61.LI Jiannan,QIAO Ying.An index system for evaluating wind power statistical properties based on multiple spatial and temporal dimensions and its application[J].Proceedings of the CSEE,2013,33(13):53-61.
[17] 龚薇,刘俊勇.计及负荷波动率和互补系数的负荷恢复[J].电网技术,2014,38(9):2490-2496.GONG Wei,LIU Junyong.Load recovery considering load fluctuation and complementary coefficients[J].Power System Technology,2014,38(9):2490-2496.
[18] 卫志农,张思德.计及电转气的电 - 气互联综合能源系统削峰填谷研究[J].中国电机工程学报,2017,37(16):4601-4609,4885.WEI Zhinong,ZHANG Side.Research on peak load filling in electricity and gas interconnected integrated energy system considering electric rotation gas[J].Proceedings of the CSEE,2017,37(16):4601-4609,4885.
[19] 杨玉青,牛利勇.考虑负荷优化控制的区域配电网储能配置[J].电网技术,2015,39(4):1019-1025.YANG Yuqing,NIU Liyong.Analysis of energy storage configuration in regional distribution network considering load optimization control[J].Power System Technology,2015,39(4):1019-1025.
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