基于数据驱动的多污染模式电能质量耦合性评估

doi:10.11930/j.issn.1004-9649.202102087

中国电力 ›› 2022, Vol. 55 ›› Issue (11): 84-90.DOI: 10.11930/j.issn.1004-9649.202102087

基于数据驱动的多污染模式电能质量耦合性评估

张健, 于浩, 梁建权, 王悦, 刘贺千

国网黑龙江省电力有限公司电力科学研究院，黑龙江哈尔滨 150030

收稿日期:2021-02-25 修回日期:2022-04-24 发布日期:2022-11-29
作者简介:张健（1981—），男，硕士，高级工程师，从事电力设备状态检测及评价研究，E-mail：13946077726@139.com;于浩（1988—），男，通信作者，博士，工程师，从事电能质量分析与控制研究，E-mail：yuhao_sagittarius@163.com;梁建权（1983—），男，博士，高级工程师，从事电磁场分析与计算研究，E-mail：ljq_hit@163.com
基金资助:
国家电网有限公司科技项目（极端气候条件下输电通道运行可靠性提升关键技术研究，5200-201930071A-0-0-00）。

Power Quality Coupling Assessment Based on Data-Driven under Multiple Pollution Patterns

ZHANG Jian, YU Hao, LIANG Jianquan, WANG Yue, LIU Heqian

Electric Power Research Institute of State Grid Heilongjiang Electric Power Co., Ltd., Harbin 150030, China

Received:2021-02-25 Revised:2022-04-24 Published:2022-11-29
Supported by:
This work is supported by Science and Technology Project of SGCC (Research on Key Technology of Transmission Channel Operation Reliability Improvement under Extreme Climate Condition, No.5200-201930071A-0-0-00).

摘要/Abstract

摘要： 为量化电网中不同电能质量变化规律下节点间扰动的相互影响，提出一种基于数据驱动的多污染模式电能质量耦合性评估方法。首先，利用频域分解构建周期性和随机性变化扰动模式，根据扰动的变化趋势和严重性，通过考虑局部极值点的分段线性拟合提取扰动模式特征。其次，提出模式距离度量法对各扰动模式特征实施模式匹配，分析不同模式下节点间扰动时间序列的耦合性，确定系统节点间扰动的相互影响。最后，采用IEEE 14节点系统进行仿真算例分析，通过对比常用的时间序列模式匹配方法，验证了所提方法的准确性和适用性。

关键词: 数据驱动, 电能质量, 耦合性, 污染模式, 频域分解

Abstract: In order to quantify the influence of disturbance among nodes under different power quality variation laws, a power quality coupling assessment method is proposed based on data-driven under multiple pollution patterns. Firstly, the periodic and random variation patterns are constructed for all disturbances by using frequency-domain decomposition. According to the disturbance variation trend and severity, the disturbance pattern features are extracted through piecewise linear fitting based on local extreme points. And then, a pattern distance measurement method is developed to implement pattern matching on the pattern features and to analyze the coupling of disturbance time series among nodes under different pollution patterns, thereby determining the interplay of disturbance among nodes. Finally case simulation analyses are conducted on the IEEE 14-bus system, and the accuracy and efficiency of the proposed method are verified by comparing the conventional time series pattern matching methods.

Key words: data-driven, power quality, coupling, pollution pattern, frequency-domain decomposition

张健, 于浩, 梁建权, 王悦, 刘贺千. 基于数据驱动的多污染模式电能质量耦合性评估[J]. 中国电力, 2022, 55(11): 84-90.

ZHANG Jian, YU Hao, LIANG Jianquan, WANG Yue, LIU Heqian. Power Quality Coupling Assessment Based on Data-Driven under Multiple Pollution Patterns[J]. Electric Power, 2022, 55(11): 84-90.

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基于数据驱动的多污染模式电能质量耦合性评估

Power Quality Coupling Assessment Based on Data-Driven under Multiple Pollution Patterns

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基于数据驱动的多污染模式电能质量耦合性评估

Power Quality Coupling Assessment Based on Data-Driven under Multiple Pollution Patterns

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