摘要
提出基于变分模态分解和双模经济模型预测控制的虚拟电厂(VPP)优化调度方法。首先,对于风电、光伏、负荷等原始功率曲线,分别通过经鲸鱼算法参数优化的变分模态分解算法进行处理,并利用互信息熵重构形成新的高、低频分量;然后,考虑高、低频分量频率特征以及可控设备不同运行特性分别设计VPP高低频优化调度模型。在此基础上,提出基于双模经济模型预测控制的VPP优化运行控制策略,模态1通过经济模型预测控制改善运行经济性,模态2借助设计的辅助控制器维持跟踪性能。最后,算例分析表明,经参数优化后的变分模态分解信号重构效果更好,提出的双模经济模型预测控制策略可协调各设备出力,在确保VPP跟踪稳态最优点的基础上可提升经济性。
It is crucial to realize both economical operation and good tracking performance of the virtual power plant(VPP)with uncertain source and load.This paper proposes an optimal scheduling method of VPP based on variational mode decomposition and dualmode economic model predictive control.Firstly,the original power curves of wind power,photovoltaic power and load are decomposed by the variational mode decomposition algorithm optimized by the whale algorithm,and new high and low frequency components are reconstructed by mutual information entropy.Then,considering the frequency characteristics and different operating characteristics of controllable equipment,the optimal scheduling model of VPP is designed.An optimization operation control strategy of VPP in terms of dual-mode economic model predictive control is presented on this basis.Operating economy is improved through economic model predictive control through Mode1,and better tracking performance is maintained with the help of auxiliary controller through Mode 2.Finally,the case analysis demonstrates that the signal reconstruction result through the variational mode decomposition after parameter optimization is enhanced.The proposed dual-mode economic model predictive control strategy can coordinate the output of different type of equipment and improve the operation economy of VPP on the basis of ensuring it to track the optimal point of steady state.
作者
余洋
温波
王紫阳
米增强
袁玉宝
常生强
Yu Yang;Wen Bo;Wang Ziyang;Mi Zengqiang;Yuan Yubao;Chang Shengqiang(State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(NCEPU),Baoding 071003,China;Innovation Center for Hebei Intelligent Grid Distribution Technology,Shijiazhuang Kelin Electric Co.,Ltd.,Shijiazhuang 050222,China;Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province(NCEPU),Baoding 071003,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2023年第8期130-138,共9页
Acta Energiae Solaris Sinica
基金
国家重点研发计划(2018YFE0122200)
国家自然科学基金(52077078)
河北省智能电网配用电技术创新中心开放课题(20200803)。
关键词
虚拟电厂
不确定性
变分模态分解
模型预测控制
电负荷调度
virtual power plant
uncertainty
variational mode decomposition
model predictive control
electric load dispatching
