Short term load forecasting (STLF) plays an important role in the economic and reliable operation ofpower systems. Electric load demand has a complex profile with many multivariable and nonlineardependencies. In this study, recurrent neural network (RNN) architecture is presented for STLF. Theproposed model is capable of forecasting next 24-hour load profile. The main feature in this networkis ...

Clustering analysis is an important technology in the field of pattern extraction and recognition. In order to find the influence of several factors on clustering results using different algorithms and support the decision for power load pattern extraction using clustering techniques, this paper develops the research on the influence of several factors on clustering results using different algo...

<span>In recent years, support vector regression (SVR) models have been widely applied in short-term electricity load forecasting. A critical challenge when applying the SVR model is to determine for optimal hyperparameters, which can be solved using several optimization methods as grid search algorithm. Another that affects response time and precision of normalization process input data....