ABSTRACT
This chapter addresses new intelligent agent-based control scheme, using Bayesian networks (BN), to design an automatic generation control (AGC) system in a multiarea power system. It introduces an intelligent BN-based multiagent control scheme to satisfy AGC objectives concerning the integration of wind power units. A BN is a graphical model that efficiently encodes the joint probability distribution for a large set of variables. There are several attractive properties of BNs for the inference of power system fault diagnosis, reliability assessment, operation, and control. The BN approaches are not model based and can be easily scalable for large-scale systems, such as real-world power systems. The dynamic behavior of a power system in the presence of wind power units might be different from that in conventional power plants. In a BN, probabilistic relationships are represented by a simple directed acyclic graph. Inference and reasoning from evidence and factual knowledge is the most common task in the BN applications, even for incomplete information.
