z-logo
open-access-imgOpen Access
Fuzzy expert systems: an application to short-term load forecasting
Author(s) -
YuanYih Hsu,
Ku-Long Ho
Publication year - 1992
Publication title -
iee proceedings c generation transmission and distribution
Language(s) - English
Resource type - Journals
eISSN - 2053-7921
pISSN - 0143-7046
DOI - 10.1049/ip-c.1992.0066
Subject(s) - expert system , term (time) , fuzzy logic , heuristic , computer science , fuzzy set , set (abstract data type) , data mining , electric power system , probabilistic forecasting , machine learning , artificial intelligence , power (physics) , physics , quantum mechanics , probabilistic logic , programming language
An expert system using fuzzy set theory is presented for short-term load forecasting. Since most statistical methods for short-term load forecasting rely heavily on weather variables and statistical models, errors may appear in the forecasted hourly loads due to uncertainties in weather variables and statistical models. thus, to have better accuracy, the operators in many utilities try to update the forecasted loads in real time using the records of the past few hours and their heuristic rules. An expert system to perform this updating function is developed. Experienced operators' heuristic rules are imbedded in the knowledge base. The uncertainties in weather variables and statistical models are dealt with using the fuzzy-set theory. To demonstrate the effectiveness of the proposed fuzzy expert system, short-term load forecasting is performed on the Taiwan power system. Test results indicate that the fuzzy expert system is very effective in improving the accuracy of the forecast hourly loads

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom