储能系统平滑光伏电站功率波动的变参数斜率控制方法

为提高储能系统平滑光伏电站功率波动的能力,提出了基于超短期预测的变参数斜率控制策略。在斜率控制的基础上,通过提出控制荷电状态划分的2个参数变量以及4个充放电功率调节参数,建立了可调整荷电状态的储能系统平滑控制策略。根据超短期预测功率建立目标函数,采用自适应混沌粒子群算法对控制变量进行实时优化,实现平滑效果和荷电状态的协同优化。以光伏电站实测数据进行仿真分析,对比定参数控制策略,该方法在保证平抑效果的基础上能够限制储能系统的充放电深度。

Slope Control Method with Variable Coefficients of Battery Energy Storage System for Smoothing Photovoltaic Power Fluctuation

In order to improve the ability of battery energy storage system(BESS)to smooth photovoltaic(PV)power fluctuation, a slope control method with variable coefficients based on ultra-short term power prediction is proposed. On the basis of the slope control method, two parameters for controlling the partition of state of charge(SOC)and four charge and discharge power regulation parameters are proposed. Then a smoothing strategy containing the above six variable coefficients and able to regulate SOC automatically is developed. The objective function is developed based on the ultra-short term PV power prediction. And a self-adaptive chaos particle swarm optimization algorithm is used to optimize the coefficients in real time, realizing the coordinated optimization between the smoothing performance and SOC. Compared with the method with fixed coefficients, the simulation results show that the control strategy is able to reduce the charge and discharge depth of BESS on the premise of ensured smoothing of power fluctuation. This work is supported by National Natural Science Foundation of China(No. 51677067), Beijing New-star Plan of Science and Technology(No. Z141101001814094)and State Grid Corporation of China(No. DG71-15-039).