基于改进型Smith预估计器与大数据的光伏电网调频逐步惯性控制方法

A Stepwise Inertial Control Method for Photovoltaic Grid Frequency Adjustment Based on Improved Smith Predictor and Big Data

光伏电网频率调整过程中,依靠常规Smith预估控制器实现电网调频控制,对模型精度具有较强的依赖性,控制策略实施后最大频率变化率(rate of change of frequency,RoCoF)较大。因此,提出基于改进型Smith预估计器与大数据的光伏电网调频逐步惯性控制方法。首先,采集历史气象数据和光伏电网运行数据,应用大数据分析领域的密度峰值聚类算法进行划分处理,再筛选相似日数据输入长短期记忆网络中,预测出未来光伏发电的功率变化;然后,依托逐步惯性控制思想,设计包含短时超发、转速恢复等多个阶段的电网调频控制策略,将模糊自适应比例-积分-微分(proportion-integration-differentiation,PID)控制器融入常规Smith预估计器,从而升级得到优化版的Smith预估计器;最后,在不受被控模型变化影响的情况下,依据预估补偿原理完成逐步惯性调频控制,并应用麻雀搜索算法求解出最优控制参数。实验结果表明:该控制方法实施后,光伏电网运行过程中最大RoCoF仅为0.086 Hz/s,有效降低了对模型精度的依赖性,保证了电力系统的稳定运行。

In the process of frequency adjustment in photovoltaic power grids,relying on conventional Smith predictive controllers to achieve grid frequency adjustment control has a strong dependence on the accuracy of the model,and the maximum rate of change of frequency(RoCoF)after the implementation of the control strategy is large.Therefore,a stepwise inertial control method for photovoltaic grid frequency adjustment based on an improved Smith predictor and big data is proposed.First,the historical meteorological data and photovoltaic power grid operation data are collected,and the density peak clustering algorithm in the field of big data analysis is applied for partition processing,and then the data of similar days are screened into the long and short term memory network to predict the power change of photovoltaic power generation in the future.Then,based on the idea of stepwise inertia control,the frequency adjustment control strategy of power grid is designed,including short-time overdrive,speed recovery and other stages.The fuzzy adaptive proportion-integration-differentiation(PID)controller is integrated into the conventional Smith predictor.Thus,the optimized Smith predictor is upgraded.Finally,under the condition of not being affected by the change of the controlled model,the stepwise inertial frequency adjustment control is completed according to the predictive compensation principle,and the sparrow search algorithm is used to solve the optimal control parameters.The experimental results show that after the implementation of the control method,the maximum RoCoF during the operation of the photovoltaic power grid is only 0.086Hz/s,which effectively reduces the dependence on the accuracy of the model and ensures the stable operation of the power system.