摘要
针对大规模新能源接入导致电力系统惯量水平下降,提出了一种基于分区惯量估计的储能容量配置策略。基于传统电力系统的惯量机理分析,建立了含新能源电力系统的等效惯量模型和风光储能虚拟惯量模型。运用谱聚类对电力系统进行分区解决惯量空间分布不均影响估计精度问题,并基于皮尔逊相关系数确定测量节点。运用差值法对分区后系统的各个区域进行惯量估计,进而利用分区惯量估计结果设计电力系统储能容量配置策略。在DIgSLIENT/PowerFactory中搭建含风机的IEEE 10机39节点模型进行仿真验证。仿真结果表明所提方法可以减小惯量估计误差,基于惯量估计结果可以对储能容量进行合理配置,保证储能系统实现快速调频和提供虚拟惯量支撑。
An energy storage capacity configuration strategy based on partitioned inertia estimation is proposed to address the decrease in inertia level of power system caused by large-scale renewable energy integration.Based on the analysis of inertia machanism in traditional power system,an equivalent inertia model and a virtual inertia model for wind power and energy storage are established for power system with renewable energy.The spectral clustering is used to partition the power system to solve the problem that the uneven spatial distribution of inertia affects the estimation accuracy,and the measurement nodes are determined based on Pearson correlation coefficient.The difference method is used to estimate the inertia of each region of the partitioned system,and the energy storage capacity configuration strategy of the power system is designed based on the results of the partition inertia estimation.The simulation of IEEE 10-machine 39-bus model with wind power is built in DIgSLIENT/PowerFactory for verification.The simulative results show that the proposed method can reduce inertia estimation error,and the energy storage capacity can be reasonably configured based on the inertia estimation results to ensure fast frequency regulation and provide virtual inertia support for the energy storage system.
作者
米阳
王沛林
周杰
马思源
李东东
MI Yang;WANG Peiin;ZHOU Jie;MA Siyuan;LI Dongdong(College of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China)
出处
《电力自动化设备》
EI
CSCD
北大核心
2024年第7期13-20,共8页
Electric Power Automation Equipment
基金
国家自然科学基金资助项目(61873159)
上海市自然科学基金资助项目(22ZR1425500)。
关键词
惯量估计
系统分区
谱聚类
差值法
储能容量配置策略
inertia estimation
system partitioning
spectral clustering
difference method
energy storage capacity configuration strategy