引用本文:张怡,刘向杰.互联电力系统鲁棒分布式模型预测负荷频率控制[J].控制理论与应用,2016,33(5):621~630.[点击复制]
ZHANG Yi,LIU Xiang-jie.Robust distributed model predictive control for load frequency control of uncertain power systems[J].Control Theory and Technology,2016,33(5):621~630.[点击复制]
互联电力系统鲁棒分布式模型预测负荷频率控制
Robust distributed model predictive control for load frequency control of uncertain power systems
摘要点击 2869  全文点击 2830  投稿时间：2015-09-28  修订日期：2016-06-15
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DOI编号  10.7641/CTA.2016.50778
  2016,33(5):621-630
中文关键词  负荷频率控制  鲁棒控制  分布式模型预测控制  线性矩阵不等式
英文关键词  load frequency control  robust control  distributed model predictive control  linear matrix inequalities
基金项目  国家自然科学基金项目(61273144, 61533013), 北京市自然科学基金项目(4122071)资助
作者单位E-mail
张怡* 华北电力大学 新能源电力系统国家重点实验室；华北理工大学电气学院 zy110806@163.com 
刘向杰 华北电力大学 新能源电力系统国家重点实验室
 		 
中文摘要
      负荷频率控制是现代互联电力系统运行的重要保障. 本文针对含有不确定因素和负荷扰动的多区域互联 电力系统提出了一种基于线性矩阵不等式参数可调节的鲁棒分布式预测控制算法. 设计各个区域控制器目标函数 引入相邻区域的状态变量和输入变量, 同时考虑发电机变化速率约束和阀门位置约束, 将求解一组凸优化问题转化 成线性矩阵不等式求解, 得到各个区域的控制律, 在线性矩阵不等式中引入一组可调参数, 将优化一个上限值转化 成优化吸引区, 降低算法的保守性. 仿真结果验证了该算法在负荷扰动、系统参数不确定和结构不确定性情况下具 有鲁棒性.
英文摘要
      Reliable load frequency control is crucial to the operation and design of modern electric power systems. However, the power systems are always subject to uncertainties and external disturbances. Considering the LFC problem of a multi-area interconnected power system, this paper presents a robust distributed model predictive control (RDMPC) based on linear matrix inequalities. The proposed algorithm solves a series of local convex optimization problems to minimize an attractive range for a robust performance objective by using a time-varying state-feedback controller for each control area. The scheme incorporates the two critical nonlinear constraints, e.g., the generation rate constraint and the valve limit, into convex optimization problems based on linear matrix inequalities. Furthermore, the algorithm explores the use of an expanded group of adjustable parameters in LMI to transform an upper bound into an attractive range for reducing conservativeness. Good performance and robustness are obtained in the presence of power system dynamic uncertainties and load change.