Intelligent Automatic Generation Control: Multi-agent Bayesian Networks Approach

被引：10

作者：

Bevrani, H. ^{[1
,2
]}

Daneshfar, F. ^{[2
]}

Daneshmand, P. R. ^{[2
]}

机构：

[1] Kumamoto Univ, Kumamoto 860, Japan

[2] Univ Kurdistan, Dept Elect & Comp Engn, Sanandaj, Iran

来源：

2010 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL | 2010年

关键词：

AGC; Bayesian networks; Frequency deviation; Multi-agent system;

D O I：

10.1109/ISIC.2010.5612931

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new intelligent agent based control scheme, using Bayesian networks (BNs), to design automatic generation control (AGC) system in a multi-area power system is addressed. Model independency and flexibility in specifying the control objectives, make the proposed approach as an attractive solution for AGC design in a real-world power system. The proposed control scheme is tested in simulation on a three areas power system and shows desirable performance. The results are also compared with the multi-agent reinforcement learning based AGC design technique.

引用

页码：773 / 778

页数：6

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