引用本文: | 苏杰,孙金龙,刘友宽,等.基于仿人智能控制的火电厂AVC系优化研究[J].电力系统保护与控制,2018,46(2):157-162.[点击复制] |
SU Jie,SUN Jinlong,LIU Youkuan,et al.Research on AVC system optimization of power plant based on human-simulated intelligent control[J].Power System Protection and Control,2018,46(2):157-162[点击复制] |
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摘要: |
目前,国内部分火电厂存在着母线电压和无功转换偏差大、脉宽调节时间不合理、无功控制和励磁控制相互不协调等问题,影响到火电厂自动电压控制系统的投运率和合格率。为解决上述问题,结合云南某火电厂自动电压控制系统的设计特点,建立了该厂单机自动电压控制系统模型。为了提高动态调节性能指标,改善控制效果,提出了仿人智能电压控制器和仿人智能无功控制器相结合的控制策略,来替代现场采用的电压PID控制和机组无功非线性控制。通过仿真验证了该控制策略的优越性,实现了对火电厂自动电压控制系统的优化研究。 |
关键词: 自动电压控制系统 建模 仿人智能控制 优化 |
DOI:10.7667/PSPC170072 |
投稿时间:2017-01-13修订日期:2017-04-11 |
基金项目: |
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Research on AVC system optimization of power plant based on human-simulated intelligent control |
SU Jie,SUN Jinlong,LIU Youkuan,LIU Shi |
(North China Electric Power University, Baoding 071000, China;Yunnan Electric Power Research Institute Group Co., Ltd., Kunming 650000, China) |
Abstract: |
At present, in some of the domestic thermal power plants, there are some problems such as large deviation between bus voltage and reactive power conversion, unreasonable pulse width adjustment time, reactive power control and excitation control being uncoordinated, etc., affecting the commissioning and qualified rate of thermal power plant automatic voltage control system. In order to solve the above problems, combined with the design features of automatic voltage control system of a thermal power plant in Yunnan province, this paper establishes a stand-alone automatic voltage control system model for the plant. In order to improve the dynamic adjustment performance index and the control effect, a control strategy combining human-simulated intelligent voltage controller and humanoid intelligent reactive power controller is proposed to replace the voltage PID control and unit reactive power nonlinear control on spot. The simulation proves the superiority of the control strategy, realizing the optimization of the automatic voltage control system of the thermal power plant. |
Key words: automatic voltage control system modeling human-simulated intelligent control optimization |