This paper presents a comprehensive evaluation of Electric Spring(ES)performance through simulation experiments and polynomial regression modelling.The study pri-marily aims to assess how varying load impedance ratios...This paper presents a comprehensive evaluation of Electric Spring(ES)performance through simulation experiments and polynomial regression modelling.The study pri-marily aims to assess how varying load impedance ratios impact ES performance,develop a polynomial regression model to predict the relationship between ES parameters and the ratio of non-critical to critical load impedance,and validate the model against simulation results.Detailed simulations were performed to analyse the effects of different impedance ratios on ES behaviour.Subsequently,a polynomial regression model was formulated to accurately capture the relationship between the ES parameters and impedance ratios.The findings indicate that the polynomial regression model effectively predicts ES perfor-mance,with the predicted values closely matching the simulation results.The validation process confirms the model's accuracy and reliability,demonstrating its potential for practical applications in optimising ES performance under various impedance conditions.This study offers valuable insights into the enhancement of ES systems through precise modelling and analysis,contributing to improved stability and efficiency in power systems.展开更多
文摘This paper presents a comprehensive evaluation of Electric Spring(ES)performance through simulation experiments and polynomial regression modelling.The study pri-marily aims to assess how varying load impedance ratios impact ES performance,develop a polynomial regression model to predict the relationship between ES parameters and the ratio of non-critical to critical load impedance,and validate the model against simulation results.Detailed simulations were performed to analyse the effects of different impedance ratios on ES behaviour.Subsequently,a polynomial regression model was formulated to accurately capture the relationship between the ES parameters and impedance ratios.The findings indicate that the polynomial regression model effectively predicts ES perfor-mance,with the predicted values closely matching the simulation results.The validation process confirms the model's accuracy and reliability,demonstrating its potential for practical applications in optimising ES performance under various impedance conditions.This study offers valuable insights into the enhancement of ES systems through precise modelling and analysis,contributing to improved stability and efficiency in power systems.
