Integration of distributed energy storage(DES)is beneficial for mitigating voltage fluctuations in highly distributed generator(DG)-penetrated active distribution networks(ADNs).Based on an accurate physical model of ...Integration of distributed energy storage(DES)is beneficial for mitigating voltage fluctuations in highly distributed generator(DG)-penetrated active distribution networks(ADNs).Based on an accurate physical model of ADN,conventional model-based methods can realize optimal control of DES.However,absence of network parameters and complex operational states of ADN poses challenges to model-based methods.This paper proposes a data-driven predictive voltage control method for DES.First,considering time-series constraints,a data-driven predictive control model is formulated for DES by using measurement data.Then,a data-driven coordination method is proposed for DES and DGs in each area.Through boundary information interaction,voltage mitigation effects can be improved by interarea coordination control.Finally,control performance is tested on a modified IEEE 33-node test case.Case studies demonstrate that by fully utilizing multi-source data,the proposed predictive control method can effectively regulate DES and DGs to mitigate voltage violations.展开更多
In this paper, a vector regulating principle of the phase and amplitude control PAC method for three-phase grid-connected inverters is presented.To solve the problem of heavy inrush current and slow dynamic response w...In this paper, a vector regulating principle of the phase and amplitude control PAC method for three-phase grid-connected inverters is presented.To solve the problem of heavy inrush current and slow dynamic response when system starts up, the starting voltage prediction control and the current feed-forward control are proposed and used, which improve the dynamic performance of the system in the PAC.The experimental results carried out on a three-phase grid-connected inverter proved the validity of the proposed method.展开更多
基金supported by the National Key R&D Program of China(2020YFB0906000,2020YFB0906001).
文摘Integration of distributed energy storage(DES)is beneficial for mitigating voltage fluctuations in highly distributed generator(DG)-penetrated active distribution networks(ADNs).Based on an accurate physical model of ADN,conventional model-based methods can realize optimal control of DES.However,absence of network parameters and complex operational states of ADN poses challenges to model-based methods.This paper proposes a data-driven predictive voltage control method for DES.First,considering time-series constraints,a data-driven predictive control model is formulated for DES by using measurement data.Then,a data-driven coordination method is proposed for DES and DGs in each area.Through boundary information interaction,voltage mitigation effects can be improved by interarea coordination control.Finally,control performance is tested on a modified IEEE 33-node test case.Case studies demonstrate that by fully utilizing multi-source data,the proposed predictive control method can effectively regulate DES and DGs to mitigate voltage violations.
基金supported by the Shanghai Education Committee Scientific Research Subsidization (Grant No.05AZ30)the Specialized Research Fund for the Doctoral Program of Higher Education (Grant No. 20060280018)
文摘In this paper, a vector regulating principle of the phase and amplitude control PAC method for three-phase grid-connected inverters is presented.To solve the problem of heavy inrush current and slow dynamic response when system starts up, the starting voltage prediction control and the current feed-forward control are proposed and used, which improve the dynamic performance of the system in the PAC.The experimental results carried out on a three-phase grid-connected inverter proved the validity of the proposed method.
