Electrical system load forecasting with polynomial neural networks (based on combinatorial algorithm)

Hüseynov A., Yusifbeyli N., Hashimov A.

International Symposium on Modern Electric Power Systems, MEPS'10, Wroclaw, Poland, 20 - 22 September 2010 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Wroclaw
  • Country: Poland
  • Keywords: combinatorial algorithm, polynomial neural model, short-term load forecasting (STLF), time series
  • Azerbaijan State University of Economics (UNEC) Affiliated: Yes

Abstract

A polynomial neural network model for short term electrical load forecasting (STLF) is developed. Several models use past weekly and monthly system loads to forecast future electrical demands. All models are validated with actual system load data from the Azerbaijani Power Company. Combinatorial algorithm is elaborated to find efficiently the coefficients of regression type model. The paper presents the results, conclusions and points out some directions for future work. © 2011 Institute of Electrical Power.