Estimation of Short-Term Power Load of a Small House by Generalized Behavioural Learning Method

ERTUĞRUL Ö. F., TAĞLUK M. E.

5th International Istanbul Smart Grid and Cities Congress and Fair (ICSG), İstanbul, Turkey, 19 - 21 April 2017, pp.85-89, (Full Text) identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/sgcf.2017.7947607
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.85-89
  • Inonu University Affiliated: Yes

Abstract

Power load estimation, especially short-term power load estimation, plays an important role in the management of a power system in terms of system security and electricity costs. Therefore, estimation of short-term power load accurately is a popular research issue. In this paper, the generalized behavioral learning method (GBLM), a method developed based on human's behavioral learning theories, was employed to estimate short-term power load. The datasets that belong to houses B and C were employed in the estimation process. Achieved results by GBLM and extreme learning machine (ELM) ELM were compared. It is showed that GBLM estimates short-term power load with a higher success rate than ELM.