AUTHORS: S. H. Oudjana, A. Hellal
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ABSTRACT: Long-term load forecasting accuracy is very important for electrical power systems. This paper explores the application of new model using neural networks (NN) and Particle Swarm Optimization (PSO) to study the design of load forecasting systems for many years ahead using historical loads databases of Slovakia power systems. In this study, instead of the method of back-propagation of the gradient, the optimization technique by swarms of particles is well tested for training neural network that optimizes the forecast error. Simulations were run and the results are discussed showing that New Hybrid Technique (PSO-NN) is capable to decrease the load forecasting error.
KEYWORDS: Load Forecasting, Neural Networks, Particle Swarm Optimization
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WSEAS Transactions on Business and Economics, ISSN / E-ISSN: 1109-9526 / 2224-2899, Volume 15, 2018, Art. #3, pp. 13-17
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