摘要
针对随机性强和波动性大的新能源发电系统,为了平滑其出力,提出了一种混合储能系统的功率变换器电流预测控制方法。该方法首先分析了锂电池和超级电容充放电速度的互补特性,以及它们的功率变换器各种开关状态。然后基于模型预测控制建立了锂电池、超级电容器和双功率变换器预测模型。在此基础上,应用模型预测控制设计了混合储能控制系统。在考虑锂电池电流跟踪误差、超级电容器电流跟踪误差、超级电容器损耗和双功率变换器开关管导通数量的情况下,构建了多目标评价函数,并进行了最优开关模式求解。通过实时优化控制系统,输出最优开关模式,既实现了锂电池大电流充放电和跟踪低频变化功率,也实现了超级电容器小电流充放电和跟踪高频变化功率。因此,该方法实现了混合储能系统能量合理分配,延长了锂电池使用寿命,减少了开关动作,提高了系统整体效率。最后,通过仿真验证了所提方法的正确性。
In order to smooth the power output of the new energy generation system with strong randomness and fluctuation,a current predictive control method of power converter for hybrid energy storage is proposed. Firstly,the complementary characteristics of charging and discharging speeds of lithium batteries and super-capacitors are analyzed,as well as the switching states of their power converters. Then,on the basis of model predictive control,the predictive models of lithium battery,super-capacitor and dual power converter are established. On this basis,a hybrid energy storage control system is designed by using model predictive control. Considering the current tracking errors of lithium batteries,supercapacitor current tracking errors,super-capacitor losses and the number of switches of dual power converter,a multiobjective evaluation function is constructed and the optimal switching mode is solved. After real-time optimization of the control system,the optimal switching mode is output. In this way,not only the high-current and low-frequency variable power tracking of lithium battery,but also the low-current and high-frequency variable power tracking of super-capacitor are realized. Therefore,the balanced energy distribution of hybrid energy storage system is realized. The service life of lithium battery is prolonged. The switching action is reduced,and the overall efficiency of the system is improved. Finally,the correctness of the proposed method is verified by simulation.
作者
王上行
贾学翠
王立华
闫士杰
李相俊
WANG Shangxing;JIA Xuecui;WANG Lihua;YAN Shijie;LI Xiangjun(State Key Laboratory of Control and Operation of Renewable Energy and Storage Systems(China Electric Power Research Institute),Beijing 100192,China;College of Information Science and Engineering,Northeastern University,Shenyang 110819,China)
出处
《电力建设》
北大核心
2020年第1期71-79,共9页
Electric Power Construction
基金
国家电网公司科技项目(基于信息物理融合的超大规模电池储能电站智能协调控制与能量优化管理——超大规模电池储能电站仿真模型及其暂态变化特性研究)(DG71-18-009)~~
关键词
混合储能系统
模型预测控制
双功率变流器
多目标优化
最优开关模式
hybrid energy storage system
model predictive control
dual power converter
multi-objective optimization
optimal switching mode
