Frequency Response Method for Power Renewable Energy Based on Logistic Regression Model
Traditional frequency response methods for power renewable energy focus on frequency fluctuation extraction,which is often affected by secondary frequency drops,leading to suboptimal response effects.This study proposes a frequency response method based on the Logistic Regression model.By extracting reduced-order characteristics of common-mode frequency response of power renewable energy and extracte the features related to frequency response from renewable energy frequency data and simplifying the regression model's complexity.The we establish a frequency response model matrix using Logistic Regression to map the complex relationship between renewable energy generation power and frequency response.It quantifies the frequency response limits of renewable energy power and determines the imbalance power generated,helping to maintain system frequency stability.Experimental results show that this method offers improved frequency response performance and is applicable in practical scenarios.
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