计及节点时变关联特征的配电网谐波传递特性分析OA
Harmonic Transfer Characteristics Analysis of Distribution Networks Considering the Time-varying Correlation Features
新型配电网中分布式光伏等新能源设备接入量不断提升,系统结构日益复杂且谐波呈现时变随机特征,这给配电网谐波传递规律分析造成极大困难.为明确新型配电网中谐波在节点间的传播范围和传递规律,并指导分布式光伏接入下的配电网承载力评估,提出计及节点时变关联特征的谐波传递特性分析方法.首先,基于节点间的谐波传递关系定义配电网节点间的谐波传递系数,并基于传递系数获取分布式光伏接入下的配电网承载力;然后,利用修正的余弦相似度对配电网节点进行聚类并选取区域划分的关键节点,实现配电网谐波复杂传递关系的降维;最后,通过构造考虑节点时变关联性的输入输出特征,建立基于 RBF-ARX 的谐波传递分析模型,对系统中谐波的时变传递特性进行评估.实验结果表明,所提谐波传递分析方法能够深度挖掘节点间谐波的时变关联特征,对配电网中复杂的谐波传递特性开展准确高效分析.
With the increasing access volume of source-load-storage and control equipment in new distribution networks,the system structure is becoming more and more complicated and the harmonics show time-varying random characteristics,which makes it extremely difficult to analyze the harmonic transfer law in distribution networks.To clarify the transmission range and transfer law of harmonics between nodes in a new distribution network and guide the assessment of distribution network carrying capacity under distributed photovoltaic(PV)integration,this paper proposes a harmonic transfer characteristic analysis method considering the time-varying correlation characteristics of nodes.Firstly,the harmonic transfer coefficients between distribution network nodes are defined based on the harmonic transfer relationship between nodes,and the distribution network carrying capacity under distributed PV integration is obtained based on the transfer coefficients.Then,the modified cosine similarity is used to cluster the distribution network nodes and select the key nodes for regional division to realize the dimensionality reduction of the harmonic complex transmission relationship of the distribution network.Finally,this paper establishes a RBF-ARX-based harmonic transfer analysis model to evaluate the time-varying transfer characteristics of harmonics in the system by constructing input-output features considering time-varying correlations of nodes.The experimental results show that the proposed harmonic transfer characteristic analysis method can deeply explore the time-varying correlation characteristics of the harmonics between nodes,and efficiently analyze the complex harmonic transfer characteristics in distribution networks.
丁玉昊;孙媛媛;李亚辉;李博文;易皓;李亚琼
山东大学电气工程学院,山东省 济南市 250061山东大学电气工程学院,山东省 济南市 250061山东大学电气工程学院,山东省 济南市 250061山东大学电气工程学院,山东省 济南市 250061西安交通大学电气工程学院,陕西省 西安市 710049中国电力科学研究院有限公司,北京市 海淀区 102200
信息技术与安全科学
谐波传递系数数据驱动时变关联特征机器学习
harmonic transfer coefficientsdata-driventime-varying correlation featuresmachine learning
《中国电机工程学报》 2026 (11)
4491-4501,中插9,12
国家重点研发计划项目(2023YFB2407500).National Key R&D Program of China(2023YFB2407500).
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