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作 者:李笑宇 韩伟 马伟东 LI Xiaoyu;HAN Wei;MA Weidong(Electric Power Science Research Institute,State Grid Henan Electric Power Company,Zhengzhou,Henan 102206,China)
机构地区:[1]国网河南省电力公司电力科学研究院,河南郑州102206
出 处:《自动化应用》2025年第4期83-88,共6页Automation Application
基 金:国网河南省电力公司科技项目(521702230012)。
摘 要:风电爬坡事件会造成风电出力在短时间内大幅波动,引发联络线越限风险。由于自动发电控制(AGC)调节容量分布不均,传统控制策略应对风电爬坡事件的调节效率有所下降。首先,基于数据驱动思想,建立单层LSTM模型,以预测爬坡率与联络线功率偏差之间的关联系数;然后,在此基础上综合爬坡率和爬坡事件预测准确率提出联络线越限风险的评价指标;最后,根据所提指标制定变增益系数的AGC控制策略,并依据实际电网模型进行仿真验证,以验证该策略改善AGC的调节能力。Wind power climbing events can cause significant fluctuations in wind power output over short periods,posing risks of off-limit of tie lines.The uneven distribution of regulation capacity in Automatic Generation Control(AGC)strategies leads to reduced efficiency in addressing wind power climbing events using traditional control methods.Firstly,based on the data-driven approach,a single-layer LSTM model is established to predict the correlation coefficient between the climbing rate and tieline power deviation.Subsequently,based on this,a risk assessment indicator for tie-line off-limit is proposed,incorporating both the climbing rate and prediction accuracy of wind power climbing events.Finally,an AGC control strategy with variable gain coefficients is developed according to the proposed index,and simulations are conducted based on an actual power grid model to verify that this strategy can effectively enhance the regulation capability of AGC.
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