Short-term daily peak load forecasting using fast learning neural network
作者： Gul Muhammad Khan , Shahid Khan , Fahad Ullah
DOI: 10.1109/ISDA.2011.6121762
关键词:
摘要: Load forecasting has been an inevitable issue in electric power supply past. It is always desired to predict the load requirements order generate and efficiently. In this research, a neuro-evolutionary technique known as Cartesian Genetic Algorithm evolved Artificial Neural Network (CGPANN) deployed develop peak model for prediction of loads 24 hours ahead. The proposed presents training all parameters (ANN) including: weights, topology functionality individual nodes. network trained both on annual well quarterly bases, thus obtaining unique each season.
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