The penetration of new energy sources such as wind power is increasing,which consequently increases the occurrence rate of subsynchronous oscillation events.However,existing subsynchronous oscillation source-identific...The penetration of new energy sources such as wind power is increasing,which consequently increases the occurrence rate of subsynchronous oscillation events.However,existing subsynchronous oscillation source-identification methods primarily analyze fixed-mode oscillations and rarely consider time-varying features,such as frequency drift,caused by the random volatility of wind farms when oscillations occur.This paper proposes a subsynchronous oscillation sourcelocalization method that involves an enhanced short-time Fourier transform and a convolutional neural network(CNN).First,an enhanced STFT is performed to secure high-resolution time-frequency distribution(TFD)images from the measured data of the generation unit ports.Next,these TFD images are amalgamated to form a subsynchronous oscillation feature map that serves as input to the CNN to train the localization model.Ultimately,the trained CNN model realizes the online localization of subsynchronous oscillation sources.The effectiveness and accuracy of the proposed method are validated via multimachine system models simulating forced and natural oscillation events using the Power Systems Computer Aided Design platform.Test results show that the proposed method can localize subsynchronous oscillation sources online while considering unpredictable fluctuations in wind farms,thus providing a foundation for oscillation suppression in practical engineering scenarios.展开更多
Wind power(WP)is considered as one of the main renewable energy sources(RESs)for future low-carbon and high-cost-efficient power system.However,its low inertia characteristic may threaten the system frequ-ency stabili...Wind power(WP)is considered as one of the main renewable energy sources(RESs)for future low-carbon and high-cost-efficient power system.However,its low inertia characteristic may threaten the system frequ-ency stability of the power system with a high penetration of WP generation.Thus,the capability of WP participating in the system frequency regulation has become a research hotspot.In this paper,the impact of WP on power system frequency stability is initially presented.In addition,various existing control strategies of WP participating in frequency regulation are reviewed from the wind turbine(WT)level to the wind farm(WF)level,and their perfor-mances are compared in terms of operating principles and practical applications.The pros and cons of each control strategy are also discussed.Moreover,the WP combing with energy storage system(ESS)for system frequency regulation is explored.Furthermore,the prospects,future challenges,and solutions of WP participating in power system frequency regulation are summarized.展开更多
基金supported by the Science and Technology Project of State Grid Corporation of China(5100202199536A-0-5-ZN)。
文摘The penetration of new energy sources such as wind power is increasing,which consequently increases the occurrence rate of subsynchronous oscillation events.However,existing subsynchronous oscillation source-identification methods primarily analyze fixed-mode oscillations and rarely consider time-varying features,such as frequency drift,caused by the random volatility of wind farms when oscillations occur.This paper proposes a subsynchronous oscillation sourcelocalization method that involves an enhanced short-time Fourier transform and a convolutional neural network(CNN).First,an enhanced STFT is performed to secure high-resolution time-frequency distribution(TFD)images from the measured data of the generation unit ports.Next,these TFD images are amalgamated to form a subsynchronous oscillation feature map that serves as input to the CNN to train the localization model.Ultimately,the trained CNN model realizes the online localization of subsynchronous oscillation sources.The effectiveness and accuracy of the proposed method are validated via multimachine system models simulating forced and natural oscillation events using the Power Systems Computer Aided Design platform.Test results show that the proposed method can localize subsynchronous oscillation sources online while considering unpredictable fluctuations in wind farms,thus providing a foundation for oscillation suppression in practical engineering scenarios.
基金supported by the State Grid Corporation Headquarters Science and Technology Project(Grant No.5100-202199273A-0-0-00).
文摘Wind power(WP)is considered as one of the main renewable energy sources(RESs)for future low-carbon and high-cost-efficient power system.However,its low inertia characteristic may threaten the system frequ-ency stability of the power system with a high penetration of WP generation.Thus,the capability of WP participating in the system frequency regulation has become a research hotspot.In this paper,the impact of WP on power system frequency stability is initially presented.In addition,various existing control strategies of WP participating in frequency regulation are reviewed from the wind turbine(WT)level to the wind farm(WF)level,and their perfor-mances are compared in terms of operating principles and practical applications.The pros and cons of each control strategy are also discussed.Moreover,the WP combing with energy storage system(ESS)for system frequency regulation is explored.Furthermore,the prospects,future challenges,and solutions of WP participating in power system frequency regulation are summarized.
