基于数据驱动和条件概率的调频容量需求计算方法

Data-driven Based Regulation Reserve Capacity Requirement Calculation Using Conditional Probability

电力系统的二次调频或自动发电控制需要一定的调频备用容量作为支撑。提出了一种基于数据驱动和条件概率的调频容量需求计算方法。首先,对调频容量需求计算中关键指标与参数进行了相关性分析,并采用条件概率的形式建立了调频容量、有功波动和调频表现之间的相关关系;其次,为预测有功波动,建立了基于极限学习机的净负荷标准差区间预测模型;最后,采用数据驱动的方式根据所建立的相关关系和预测所得的有功波动计算各调频容量下调频表现达标概率分布,据此确定系统调频容量需求。基于实际历史数据的仿真结果表明,所提方法不但能够降低平均调频容量,还可提升调频表现。

The secondary frequency regulation or automatic generation control of a power system requires a certain capacity of frequency regulation reserve.This paper proposes a data-driven based method for estimating frequency regulation reserve capacity(FRRC)requirement using conditional probability.First,the correlations between the control performance and its affecting factors are analyzed and established in the form of conditional probability.Secondly,in order to predict the power fluctuation,an interval model for predicting the net load standard deviation is established based on the extreme learning machine.Finally,a data-driven approach is proposed to optimize the FRRC based on the established relationship and the predicted net load fluctuation.The numerical simulation results based on the historical data show that the proposed method can reduce FRRC and improve the control performance.