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Erschienen in:
2006 | OriginalPaper | Buchkapitel
The Application of Neural Networks to Electric Power Grid Simulation
verfasst von : Emily T. Swain, Yunlin Xu, Rong Gao, Thomas J. Downar, Lefteri H. Tsoukalas
Erschienen in: Artificial Neural Networks – ICANN 2006
Verlag: Springer Berlin Heidelberg
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A neural network approach is being developed to enable real time simulations for large scale dynamic system simulations of the electric power grid. If the grid is decomposed into several subsystems, neural networks can be utilized to simulate computationally intensive subsystems. An electrical generator sub-system was created in MATLAB using the SIMULINK interface. The SIMULINK model provided corresponding input/output pairs by varying parameters in sample transmission lines. A feed-forward backpropagation neural network was created from this data. Integration of the generator neural network into the SIMULINK interface was also performed. The original SIMULINK model requires about 342,000 iterations to simulate a 30 second simulation and consumes about 27 minutes of execution time. Conversely, the neural network based system is able to determine accurate solutions in less than 75 seconds and 300 iterations, which is more than an order of magnitude reduction in the execution time.