Self-Healing Control of Expansion Power Systems in Structural Stability Based on Parameter Optimization

LI Xiaohua; LIU Yang; JIANG Benyuan; XU Yianying

您当前的位置：

首页 >

文章列表页 >

Self-Healing Control of Expansion Power Systems in Structural Stability Based on Parameter Optimization

更新时间：2023-12-11

- Self-Healing Control of Expansion Power Systems in Structural Stability Based on Parameter Optimization
- Acta Scientiarum Naturalium Universitatis SunYatseni Vol. 53, Issue 6, Pages: 140-145(2014)
- 作者机构：
  
  1. 辽宁科技大学电子与信息工程学院,辽宁,鞍山,114051
  2. 
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2014，
  
  Published Online：25 November 2014，
扫描看全文
LI Xiaohua, LIU Yang, JIANG Benyuan, et al. Self-Healing Control of Expansion Power Systems in Structural Stability Based on Parameter Optimization. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 53(6):140-145(2014)
DOI：

LI Xiaohua, LIU Yang, JIANG Benyuan, et al. Self-Healing Control of Expansion Power Systems in Structural Stability Based on Parameter Optimization. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 53(6):140-145(2014) DOI：

摘要

针对一类互联电力系统在线扩容时的自动发电控制（AGC）设计，采用动态输出反馈和遗传算法提出了一种能保证扩容后系统在拓扑结构突然改变时稳定运行的结构自愈优化控制方法。这种方法通过对扩容系统的建模，采用线性矩阵不等式方法设计了使其结构稳定的鲁棒分散控制器，并用遗传算法优化了问题求解中的相关参数，避免了设计中参数选择的盲目性。在优化过程中选取了综合评价系统时域响应性能的适应度函数来优化控制器设计中的互联约束矩阵，达到了改善系统性能指标的目的。文中针对一类互联电力系统模型进行了仿真研究，考虑在原区域电力系统的基础上在线增加一个新的区域，对新区域的自动发电控制律采用所提出方法进行了设计，仿真结果表明该方法达到了扩容后系统稳定的结构自愈控制要求，且采用遗传算法优化后的系统性能明显优于优化前的，证明了该方法的有效性。

Abstract

Aiming at automatic generation control (AGC) design of a class of interconnected power systems when the expansion is done on line

an optimized selfhealing control method

which can guarantee the expanded system to steady run when the topological structure is changed suddenly

is proposed by adopting dynamic output feedback and genetic algorithm. By means of modeling to the expansion system

the robust decentralized controller keeping the system structure to be stable is designed by using LMI method. Genetic algorithm is used to optimize the related parameters emerged in the process to solve

and the blindness to choose the parameters is avoided. In the optimal process

the fitness function evaluating synthetically the time domain response performance is chosen to optimize the interconnected constraint matrix in the design. The performance indexes of the system are improved. The simulation research is done against a kind of interconnected power system model. Consider a new area subsystem is add to original system on line

the automatic generation control law of the new area is designed by using the proposed method. The simulation results show that the proposed method reaches the selfhealing control request

which the structure of the expansion system is stable. The control performances optimized by genetic algorithm are better than the before

and the effectiveness of this method is proved.

关键词

互联电力系统扩容动态输出反馈遗传算法线性矩阵不等式

Keywords

interconnected power systemexpansiondynamic output feedbackgenetic algorithmLMI

references

Views

299

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Location routing problem with outsourcing strategy

Delaydependent Stability for Systems with Two Additive Timevarying Delay Components

Optimization of Bridges- Parameters Based on BP Neural Network and Genetic Algorithm

Solving Nonlinear Equations Based on Improved Genetic Algorithm

Prediction Model based on Particle Swarm-projection Pursuit and Genetic-neural Networks

Related Author

ZHU Zixuan

WU Weitiao

LI Ting

JIN Wenzhou

LIU Heping

LIU Kun

ZHAO Liying

HUANG Xiaoqing

Related Institution

School of Civil and Transportation Engineering, South China University of Technology

Applied Science School, University of Science and Technology Beijing

Information and Engineering School, University of Science and Technology Beijing

School of Construction Engineering Maoming University

School of Building and Communication South China University of Techenology

Postal code：510275
Tel：020-84112585，84113223 Email：xuebaozr@mail.sysu.edu.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09064830号-19 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰