电池储能平抑风电功率波动的预测控制方法  

A Model Predictive Control Method of Battery Energy Storage for Smoothing Wind Power Fluctuation

作　　者：罗毅[1] 李达[1] 

机构地区：[1]华北电力大学控制与计算机工程学院,北京102206

出　　处：《电力科学与工程》2015年第11期1-5,11,共6页Electric Power Science and Engineering

基　　金：北京市自然科学基金(4122071)

摘　　要：风电波动性和随机性严重影响电力系统安全稳定性。为了平抑风功率波动,提出了一种基于模型预测控制(MPC)原理的平抑风电功率波动的电池储能控制方法。该方法利用风电场超短期功率预测信息,以并网风电功率的波动范围、电池储能荷电状态(SOC)、储能出力大小等为约束,通过滚动优化实现对储能的优化控制。算例表明,该方法既能有效平抑风电功率波动,又能超前控制储能SOC值,维持储能的平滑能力,避免储能过充过放。The fluctuation and randomness of wind power harmfully impacts on the security and stability of power system. In order to smooth the fluctuation of wind power,a new control strategy for battery energy storage system（ BESS） based on the model predictive control（ MPC） is proposed. Based on the super short-term power forecasting results,an optimal control of the energy storage system is realized through receding optimization with a number of constrains considered such as the fluctuation range of grid-connected wind power,the state-of-charge（ SOC） of the energy storage system and energy storage output size. Simulation studies demonstrate that the new method can not only smooth the short-term fluctuation,but also control the SOC range ahead,thus maintaining the smoothing performance of BESS and avoiding overcharging and discharging.

关 键 词：风功率波动 电池储能系统 荷电状态 模型预测控制 

分 类 号：TM614[电气工程—电力系统及自动化]