Short Term Load Forecasting of Taiwan Power System Using a Knowledge-based Expert System
Journal
IEEE Transactions on Power Systems
Journal Volume
5
Journal Issue
4
Pages
1214-1221
Date Issued
1990-11
Date
1990-11
Author(s)
Ho, K. L.
Abstract
A knowledge-based expert system is proposed for the short term load forecasting of Taiwan power system. The developed expert system, which was implemented on a personal computer, was written in PROLOG using a 5-year data base. To benefit from the expert knowledge and experience of the system operator, eleven different load shapes, each with different means of load calculations, are established. With these load shapes at hand, some peculiar load characteristics pertaining to Taiwan Power Company can be taken into account. The special load types considered by the expert system include the extremely low load levels during the week of the Chinese New Year, the special load characteristics of the days following a tropical storm or a typhoon, the partial shutdown of certain factories on Saturdays, and the special event caused by a holiday on Friday or on Tuesday, etc. A characteristic feature of the proposed knowledge-based expert system is that it is easy to add new information and new rules to the knowledge base. To illustrate the effectiveness of the presented expert system, short-term load forecasting is performed on Taiwan power system by using both the developed algorithm and the conventional Box-Jenkins statistical method. It is found that a mean absolute error of 2.52% for a year is achieved by the expert system approach as compared to an error of 3.86% by the statistical method. © 1990 IEEE
Subjects
artificial intelligence; expert systems; loadforecasting
Other Subjects
Computer Programming Languages--PROLOG; Computers, Personal; Expert Systems--Knowledge Bases; Taiwan Power System; Electric Power Systems
Type
journal article