Volume 7, Issue 2 (June 2011)                   IJEEE 2011, 7(2): 141-148 | Back to browse issues page

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Daneshfar F, Bevrani H, Mansoori F. Load-Frequency Control: a GA based Bayesian Networks Multi-agent System . IJEEE. 2011; 7 (2) :141-148
URL: http://ijeee.iust.ac.ir/article-1-345-en.html
Abstract:   (8370 Views)
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.
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Type of Study: Research Paper | Subject: Control of Electrical Power Systems
Received: 2010/11/14 | Revised: 2011/12/24 | Accepted: 2011/06/18

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