a novel random fuzzy neural networks for tackling uncertainties of electric load forecasting论文.pdf

Electrical Power and Energy Systems 73 (2015) 34–44 Contents lists available at ScienceDirect Electrical Power and Energy Systems journal homepage: www.else /locate/ijepes A novel random fuzzy neural networks for tackling uncertainties of electric load forecasting Chin Wang Lou ⇑, Ming Chui Dong Faculty of Science and Technology, University of Macau, Avenida da Universidade, Taipa, Macau a r t i c l e i n f o a b s t r a c t Article history: In this paper, fuzzy (inaccuracy, vague, dispersion of individual interpretation) and random (incom- Received 5 February 2014 pleteness, noise and variability) uncertainties of electric load forecasting are modeled by random Received in revised form 7 March 2015 fuzzy variables (RFVs). Further integrating it into neural networks (NN) to formulate a novel inte- Accepted 15 March 2015 grated technique–Random Fuzzy NN (RFNN) for load forecasting is presented. The features of this methodology are as follows. (1) It is able to effectively and simultaneously model referred uncertain- ties occurred in load forecasting by one integrated technique, which existing techniques (e.g. fuzzified Keywords: NN or Bayesian NN) tackle them separately. (2) Specially, historical data/information containing Load forecasting incomp