Automatic generation control (AGC) is one of the
important control problems in electric power system design and
operation, and is becoming more significant today because of increasing
renewable energy sources such as wind farms. The power
fluctuation caused by a high penetration of wind farms negatively
contributes to the power imbalance and frequency deviation. In
this paper, a new intelligent agent-based control scheme, using
Bayesian networks (BNs), is addressed to design AGC system in
a multiarea power system. Model independence and flexibility in
specifying the control objectives identify the proposed approach as
an attractive solution forAGCdesign in a real-world power system.
The BN also provides a robust probabilistic method of reasoning
under uncertainty, and moreover, using multiagent structure in
the proposed control framework realizes parallel computation and
a high degree of scalability. The proposed control scheme is examined
on the 10-machine New England test power system. An
experimental real-time implementation is also performed on the
aggregated model of West Japan power system.
