Improved Model Predictive Control with Prescribed Performance for Aggregated Thermostatically Controlled Loads

作     者：Yang Yu Li Quan Zengqiang Mi Jianbin Lu Shengqiang Chang Yubao Yuan Yang Yu;Li Quan;Zengqiang Mi;Jianbin Lu;Shengqiang Chang;Yubao Yuan

作者机构：the State Key Laboratory of Alternate Electrical Power System with Renewable Energy SourcesNorth China Electric Power UniversityBaodingChina the Innovation Center for Hebei Intelligent Grid Distribution TechnologyShijiazhuang Kelin Electric Co.Ltd.ShijiazhuangChina 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报（英文）)

年 卷 期：2022年第10卷第2期

页      面：430-439页

核心收录：

学科分类：080802[工学-电力系统及其自动化] 0808[工学-电气工程] 08[工学] 

基　　金：the key projects in 2018 National Key R&D Programs(No.2018YFE0122200) the Fundamental Research Funds for the Central Universities(No.2020MS090) opening project of Hebei Smart Grid Distribution and Utilization Technology Innovation Center(No.20200803) 

主　　题：Lyapunov function model predictive control power tracking prescribed performance thermostatically controlled load 

摘      要：Aggregate thermostatically controlled loads(AT-CLs)are a suitable candidate for power imbalance on demand side to smooth the power fluctuation of renewable energy.A new control scheme based on an improved bilinear aggregate model of ATCLs is investigated to suppress power ***,the original bilinear aggregate model of ATCLs is extended by the second-order equivalent thermal parameter model to optimize accumulative error over a long time ***,to ensure the control performance of tracking error,an improved model predictive control algorithm is proposed by integrating the Lyapunov function with the error transformation,and theoretical stability of the proposed control algorithm is ***,the simulation results demonstrate that the accuracy of the improved bilinear aggregate model is enhanced;the proposed control algorithm has faster convergence speed and better tracking accuracy in contrast with the Lyapunov function-based model predictive control without the prescribed performance.