Power demand prediction using fuzzy logic

A. Al-Anbuky, S. Bataineh, S. Al-Aqtash

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


The paper discusses the implementation of a fuzzy-logic approach to provide a structural framework for the representation, manipulation and utilization of data and information concerning the prediction of power commitments. A neural network would then be implemented to accommodate and manipulate the large amount of sensor data involved. A training facility could allow the system to replace the requirement for skilled dispatchers in scheduling the generators. An algorithm has been implemented and trained to predict the total power demand on an hourly basis. The parameters taken into consideration cover environmental and weather-related conditions. Prediction of the power demand at each geographical load point, and hence the country-wide demand, has been tested in Jordan. Results concerning the daily prediction have been obtained. It is found to be very promising, especially in that the prediction is evaluated in a fuzzy environment.

Original languageEnglish
Pages (from-to)1291-1298
Number of pages8
JournalControl Engineering Practice
Issue number9
Publication statusPublished - Sept 1995
Externally publishedYes


  • Fuzzy Systems
  • Load forecasting
  • Power management
  • Unit Commitment

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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