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identifiability Analysis of Load Model Parameters by Estimating Confidential Intervals

CSEE Journal of Power and Energy Systems 2023年第5期9卷 1666-1675页

作者： Xinran Zhang Chao Lu Ying Wang Qiantu Ruan Hongbo Ye Weihong Wang the School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China. the State Key Laboratory of Control and Simulation of Power System and Generation Equipment Tsinghua UniversityBeijing 100084China School of Technology Beijing Forestry UniversityBeijing 100083China the State Grid Shanghai Electric Power Company Shanghai 200122China

The identification of load model parameters from practical measurement data has become an essential method to build load models for power system simulation,analysis and *** practical situations,the accuracy of the load model parameters identification results is impacted by data quality and measurement accuracy,which leads to the problem of *** this paper,an identifiability analysis methodology of load model parameters,by estimating the confidential intervals(CIs)of the parameters,is *** load model structure and the combined optimization and regression method to identify the parameters are first ***,the definition and analysis method of identifiability are *** CIs of the parameters are estimated through the profile likelihood method,based on which a practical identifiability index(PII)is defined to quantitatively evaluate ***,the effectiveness of the proposed analysis approach is validated by the case study results in a practical provincial power *** results show that the impact of various disturbance magnitudes,measurement errors and data length can all be reflected by the proposed ***,the proposed PII can provide guidance in data length selection in practical load model identification situations.

关键词： Confidential interval Load modeling parameter estimation practical identifiability

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Parameter identifiability of a within-host SARS-CoV-2 epidemic model

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Infectious Disease Modelling 2024年第3期9卷 975-994页

作者： Junyuan Yang Sijin Wu Xuezhi Li Xiaoyan Wang Xue-Song Zhang Lu Hou Complex Systems Research Center Shanxi UniversityTaiyuan030006China Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention Shanxi UniversityTaiyuan030006China School of Mathematics and Science Henan Normal UniversityXinxiang453000China School of Information Shanxi University of Finance and EconomicsTaiyuan030006China Agriculture and Animal Husbandry Technology Promotion Center of Xingan League Xingan League137400China

Parameter identification involves the estimation of undisclosed parameters within a system based on observed data and mathematical *** this investigation,we employ DAISY to meticulously examine the structural identifiability of parameters of a within-host SARS-CoV-2 epidemic model,taking into account an array of observable ***,Monte Carlo simulations are performed to offer a comprehensive practical analysis of model ***,sensitivity analysis is employed to ascertain that decreasing the replication rate of the SARS-CoV-2 virus and curbing the infectious period are the most efficacious measures in alleviating the dissemination of COVID-19 amongst hosts.

关键词： Structural identifiability practical identifiability Sensitivity analysis The basic reproduction number

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