山东电力技术2026，Vol.53Issue(8)：1-13,13.DOI:10.20097/j.cnki.issn1007-9904.250726
考虑多扰动和频率响应分布性的新能源电力系统分区研究
Research on the Partitioning of Renewable Energy Power Systems Considering Multiple Disturbance and Distribution Characteristics of Frequency Response
摘要
Abstract
The frequency dynamic response of renewable energy power systems exhibits significant spatio-temporal distribution characteristics,making existing partitioning methods inadequate for accurately capturing the spatio-temporal similarity of nodal frequency responses.To address this issue,this paper proposes a partitioning method based on data-driven approaches and the morphological similarity of inter-node frequency dynamic responses under multiple disturbance scenarios.First,the dynamic time warping(DTW)distance is introduced to measure the similarity between node frequency curves under multiple disturbances,and a frequency dynamic response similarity index(DFDI)is constructed.On this basis,the K-means++clustering algorithm is employed to achieve system partitioning.Then,an evaluation framework for partitioning effectiveness is established to quantify partition accuracy by measuring both intra-region frequency response similarity and the inter-region separation.Finally,simulations conducted on a modified IEEE 39-bus system demonstrate that the proposed method can effectively identify regions with similar frequency responses under different distributions of frequency regulation resources and scenarios involving renewable energy participation in frequency regulation.The partitioning performance is significantly superior to that of traditional methods.This work lays a foundation for regional inertia assessment,frequency response modeling,and inertia configuration in renewable energy power systems.关键词
频率响应时空分布/多扰动场景/DTW距离/系统分区/分区评价Key words
spatio-temporal distribution of frequency response/multiple disturbance scenarios/DTW distance/system partitioning/evaluation of partitioning results分类
信息技术与安全科学引用本文复制引用
魏永凯,潘学萍,郭金鹏,孙晓荣,徐涛,周鹏..考虑多扰动和频率响应分布性的新能源电力系统分区研究[J].山东电力技术,2026,53(8):1-13,13.基金项目
国家自然科学基金项目(52407094,52477089). National Natural Science Foundation of China(52407094,52477089). （52407094,52477089）
