Design of a multi-mode intelligent model predictive control strategy for hydroelectric generating unit

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• 作者：Yang ZhengAuthor Vitae ; Jianzhong Zhou ; ^{jz.zhou@hust.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Wenlong ZhuAuthor Vitae ; Chu ZhangAuthor Vitae ; Chaoshun LiAuthor Vitae ; Wenlong FuAuthor Vitae
• 关键词：Nonlinear model predictive control ; Tree&ndash ; seed algorithm ; Heuristic rolling optimization ; Multi-mode control ; Comprehensive governing and excitation control
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：26 September 2016
• 年：2016
• 卷：207
• 期：Complete
• 页码：287-299
• 全文大小：2198 K

文摘

This paper proposes a nonlinear multi-mode intelligent model predictive control (MPC) strategy for hydroelectric generating unit (HGU). In this multi-mode MPC scheme, excitation MPC mode and integrated MPC mode work for excitation control process and load scheduling condition, respectively. Every control mode is built on the basis of a tree–seed algorithm based model predictive control (TSA–MPC) scheme, which introduces a newly proposed tree–seed algorithm (TSA) and the stability-guaranteed measures into rolling optimization mechanism of nonlinear MPC (NMPC) to replace the existing complex numerical differential geometric solutions. Simulation experiments of the proposed multi-mode MPC and the comparative methods are undertaken under diverse operating conditions in a HGU control system as case studies. Experimental results indicate the superiority in voltage regulation and damping performance as well as the effectiveness of the comprehensive control of turbine governing and generator excitation.