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考虑饱和环节的自动发电控制时滞系统串级控制

陈晨 李平康 贾智州

电力系统自动化2017,Vol.41Issue(10):66-71,6.
电力系统自动化2017,Vol.41Issue(10):66-71,6.DOI:10.7500/AEPS20160930010

考虑饱和环节的自动发电控制时滞系统串级控制

Cascade Control of Automatic Generation Control Time-delay System Considering Saturation

陈晨 1李平康 1贾智州1

作者信息

  • 1. 北京交通大学机械与电子控制工程学院, 北京市 100044
  • 折叠

摘要

Abstract

As there are constraints such as the time delay and generation rate constraint (GRC) in the automatic generation control (AGC) regulation process, the frequency regulation characteristics of power systems cannot be reflected by the AGC control strategy based on linear models.For the saturation and the time delay in the AGC time-delay system, a genetic optimization strategy of AGC cascade control system based on the proportional-integral (PI) stability domain is proposed.AGC system is equivalent to cascade control system made up of load frequency control loop and unit control loop.The Hopf bifurcation algebraic criterion and the time-delay system stability criteria are used to compute the stability domain of the inner and outer loops, respectively.It is proved that the parameters of the saturation and the time delay will affect the PI stability domains.Then the PI stability domains are converted into constraints of controller parameter optimization.Optimization comparative researches for the inner loop have shown that the integral of the absolute error (IAE) index has better performance in suppressing disturbances while the integral of the time squared error (ITSE) index has smaller fluctuations for the outer loop.Genetic optimization results show that the proposed control strategy is able to effectively resist the impact of the saturation and the time delay on the AGC system.

关键词

发电机变化率约束/时延/串级控制/Hopf分岔代数判据/遗传优化

Key words

generation rate constraint (GRC)/time delay/cascade control/Hopf bifurcation algebraic criterion/genetic optimization

引用本文复制引用

陈晨,李平康,贾智州..考虑饱和环节的自动发电控制时滞系统串级控制[J].电力系统自动化,2017,41(10):66-71,6.

基金项目

国家自然科学基金资助项目(61074104).This work is supported by National Natural Science Foundation of China (No.61074104). (61074104)

电力系统自动化

OA北大核心CSCDCSTPCD

1000-1026

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