摘要
大规模储能电站一般由数十甚至上百台机组组成。针对仿真模型的复杂度、计算量和可靠性,提出对数值进行加权平均等值建模的方法。将等值后的机组数据进行参数辨识得到系统输出功率的传递函数模型,该传递函数模型阶数远低于详细模型,仿真运算量大幅度减少。对比两种模型的仿真结果,模型适配率不低于99%,验证了加权平均和系统辨识方法的有效性。
Large scale energy storage power station generally consists of dozens or even hundreds of units.A method of weighted average equivalent modeling for numerical values was proposed to address the complexity,computational volume and reliability of simulation models.The parameters of the equivalent unit data were identified to obtain the transfer function model of the system output power;the order of the transfer function model was much lower than that of the detailed model,resulting in a significant reduction in simulation computation.Comparing the simulation results of the two models,the model adaptation rate is not less than 99%,which verifies the effectiveness of the weighted average and system identification methods.
作者
杨农
凌志斌
潘三博
Yang Nong;Ling Zhibin;Pan Sanbo(School of Electrical Engineering,Shanghai Dianji University,Shanghai 201306,China;Key Laboratory of Control of Power Transmission and Conversion,Shanghai Jiao Tong University,Shanghai 200240,China)
出处
《电气自动化》
2025年第3期40-42,共3页
Electrical Automation
基金
国家自然科学基金项目(52277221)。
关键词
加权平均
系统辨识
动态模型
储能电站
传递函数
weighted average
system identification
dynamic model
energy storage power station
transfer function
