2025/12/5
Hassan Bevrani

Hassan Bevrani

Academic rank: Professor
ORCID:
Education: PhD.
H-Index:
Faculty: Faculty of Engineering
ScholarId:
E-mail: bevrani [at] uok.ac.ir
ScopusId: View
Phone: +98-87-33624001
ResearchGate:

Research

Title
Intelligent Automatic Generation Control: Multi-agent Bayesian Networks Approach
Type
Presentation
Keywords
AGC-Bayesian networks-Frequency deviation-Multi-agent system
Year
2010
Researchers Hassan Bevrani ، Fatemeh Daneshfar ، Puria Daneshmand

Abstract

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.