en 3-Control of Electrical Power Systems Control of Electrical Power Systems Research Paper Research Paper Bayesian Networks (BN) provides a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of load-frequency control (LFC). In practice, LFC systems use proportional-integral controllers. However since these controllers are designed using a linear model, the nonlinearities of the system are not accounted for and they are incapable to gain good dynamical performance for a wide range of operating conditions in a multi-area power system. A strategy for solving this problem due to the distributed nature of a multi-area power system, is presented by using a BN multi-agent system. This method admits considerable flexibility in defining the control objective. Also BN provides a flexible means of representing and reasoning with probabilistic information. Efficient probabilistic inference algorithms in BN permit answering various probabilistic queries about the system. Moreover using multi-agent structure in the proposed model, realized parallel computation and leading to a high degree of scalability. To demonstrate the capability of the proposed control structure, we construct a BN on the basis of optimized data using genetic algorithm (GA) for LFC of a three-area power system with two scenarios. Load-Frequency Control,Multi-Agent System (MAS),Bayesian Network, 141 148 http://ijeee.iust.ac.ir/browse.php?a_code=A-10-364-1&slc_lang=en&sid=1 F. Daneshfar daneshfar@ieee.org 180031947532846001639 180031947532846001639 Yes University of Kurdistan H. Bevrani bevrani@ieee.org 180031947532846001640 180031947532846001640 No University of Kurdistan F. Mansoori Fathollah.mansoori@yahoo.com 180031947532846001641 180031947532846001641 No University of Kurdistan