电力系统自动化2024，Vol.48Issue(8)：53-66,14.DOI:10.7500/AEPS20230716004
计及频率响应时空相关性的新能源电力系统惯量估计方法
Inertia Estimation Method for Power System with Renewable Energy Considering Spatio-temporal Correlation of Frequency Response
摘要
Abstract
The power system with high-proportion renewable energy has low inertia level and high uncertainty.The system inertia level is closely related to the dynamic frequency response process.Considering the spatio-temporal correlation of frequency response process between nodes within the system,dynamically quantifying the spatio-temporal correlation of frequency between nodes provides an effective technique for real-time inertia estimation in the new power system.Firstly,a calculation method for inertia of synchronous units and renewable energy generator units is proposed.Secondly,the Granger causality test algorithm is used to dynamically analyze the frequency correlation of different nodes in the system,thereby establishing a time-varying spatio-temporal causal correlation set of system frequency.Furthermore,based on the swing equation of frequency response processes of various nodes in the system,a system inertia-frequency state space model is constructed.Subsequently,a novel method for estimating the inertia of power system with high-proportion renewable energy is proposed using the unscented Kalman filter and fixed-lag smoother.Finally,the proposed method is validated using an improved IEEE 39-node system,demonstrating its effectiveness and applicability.Results show that the proposed method ensures consistent inertia estimation performance in different renewable energy penetration rates and frequency disturbance scenarios,which has engineering application potential.关键词
惯量估计/电力系统/新能源/因果相关/状态空间/频率响应/滤波-平滑两阶段估计Key words
inertia estimation/power system/renewable energy/causal correlation/state space/frequency response/filtering-smoothing two-stage estimation引用本文复制引用
裴铭,叶林,罗雅迪,沙立成,张再驰,宋旭日..计及频率响应时空相关性的新能源电力系统惯量估计方法[J].电力系统自动化,2024,48(8):53-66,14.基金项目
国家电网有限公司总部科技项目(5108-202218280A-2-294-XG) （5108-202218280A-2-294-XG）
国家自然科学基金新型电力系统联合基金重点资助项目(U22B20117). This work is supported by State Grid Corporation of China(No.5108-202218280A-2-294-XG)and Smart Grid Joint Foundation Program of National Natural Science Foundation of China(No.U22B20117). （U22B20117）
