Bayesian networks design of load-frequency control based on GA

Abstract

Frequency regulation in interconnected networks is one of the main challenges in power systems. Significant interconnection frequency deviations can cause under/over frequency relaying and disconnect some loads and generations. Under unfavorable conditions, this may result in a cascading failure and system collapse. A control strategy for solving this problem in a multi-area power system is presented by an intelligent based load frequency control (LFC) using Bayesian networks (BNs). This method admits considerable flexibility in defining the control objectives specifically in a large scale power system. The BNs provide efficient probabilistic inference algorithms that permit answering various probabilistic queries about the system and incorporate expert knowledge and historical data for revising the prior belief in the light of new evidence in many fields. It is also possible to include local conditional dependencies into the model, by directly specifying the causes that influence a given effect. To demonstrate the capability of the proposed control structure, a three-control area power system simulation with two different scenarios is presented.