Abstract
Modern systems of voltage control in distribution grids need load forecast. The paper describes forecasting methods and concludes that using of artificial neural networks for this problem is preferable. It shows that for the complex real networks particle swarm method is faster and more accurate than traditional back propagation method.
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CITATION STYLE
Lis, R., Vanin, A., & Kotelnikova, A. (2017). Methods of Training of Neural Networks for Short Term Load Forecasting in Smart Grids. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10448 LNAI, pp. 433–441). Springer Verlag. https://doi.org/10.1007/978-3-319-67074-4_42
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