面向风电功率波动平抑的储能系统鲁棒模型预测控制

Robust model predictive control of energy storage system for wind power fluctuation smoothing

作为支撑新能源高比例消纳的重要灵活性资源,储能可有效应对强不确定性的风力发电对电力系统安全稳定运行的影响。提出了一种面向功率平抑的风-储系统鲁棒模型预测控制技术。首先,为考虑风力发电的不确定性,避免预测误差的参数化先验假设,采用盒式不确定性集来对风电出力进行建模。其次,建立了包含并网功率波动均值、储能电站运行充放电总能量、储能电站出力系数的风电功率波动平抑效果评价指标。然后,建立了面向功率平抑的风-储系统运行双层优化模型。为提高双层不确定性优化模型的可求解性,采用强对偶理论将原双层模型变换为单层确定性优化模型,并通过大M法用一组线性不等式约束来代替双线性约束。最后,算例分析验证了所提方法的有效性。

As an important flexible resource to support the high proportion of renewable energy consumption,energy storage is able to cope with the influence of wind power uncertainty on the operation of the electricity system.This paper proposes a wind power fluctuation smoothing method based on robust model predictive control technique.Firstly,to consider the uncertainty of wind power generation and avoid the parametric a priori assumptions of prediction errors,a box-type uncertainty set is utilized to model the wind power output.Secondly,the evaluation index of wind power fluctuation smoothing including the mean value of grid-connected power fluctuation,the total output energy of storage power station,and the output coefficient of energy storage power station is established.Then,an optimization model of the operation of wind-storage systems for wind power smoothing is constructed.To improve the solvability of the two-layer uncertainty optimization model,the original double-layer optimization model is converted into a singlelayer deterministic optimization model by the strong dual theory.The bilinear term is replaced by a set of linear inequality constraint based on big-M method.Finally,the effectiveness of the proposed method is verified by numerical experiments.