24 hours fuzzy logic technique for load forecasting/ Mohd Daud Alang Hassan
Load forecasting is an important in energy management system. It can be used as an aid in operation and planning of distribution power system. In this thesis a knowledge-based expert system is proposed for the short term load forecasting in which fuzzyTECH software is employed to manipulate actual v...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
1998
|
| Online Access: | https://ir.uitm.edu.my/id/eprint/100690/1/100690.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
my-uitm-ir.100690 |
|---|---|
| record_format |
uketd_dc |
| spelling |
my-uitm-ir.1006902024-08-17T17:05:16Z 24 hours fuzzy logic technique for load forecasting/ Mohd Daud Alang Hassan 1998 Alang Hassan, Mohd Daud Load forecasting is an important in energy management system. It can be used as an aid in operation and planning of distribution power system. In this thesis a knowledge-based expert system is proposed for the short term load forecasting in which fuzzyTECH software is employed to manipulate actual value of previous load forecast. To develop fuzzy logic system, three different load profiles from data collection are establish. The fuzzy logic based expert system utilizes the historical relationship between load and drybulb temperature and forecast load for 1-24 hour ahead. Experiments were carried out to develop the short term load forecasting (STLF) system. Based on these experiments a triangular membership function with five linguistic term and twenty five appropriate fuzzy rule base give accurate forecast and it used as a forecaster . Overall forecast give a percentage error less then 5 %. 1998 Thesis https://ir.uitm.edu.my/id/eprint/100690/ https://ir.uitm.edu.my/id/eprint/100690/1/100690.pdf text en public degree Universiti Teknologi, MARA (UiTM) Faculty of Electrical Engineering Mohd Shah Baki, Shah Rizam |
| institution |
Universiti Teknologi MARA |
| collection |
UiTM Institutional Repository |
| language |
English |
| advisor |
Mohd Shah Baki, Shah Rizam |
| description |
Load forecasting is an important in energy management system. It can be used as an aid in operation and planning of distribution power system. In this thesis a knowledge-based expert system is proposed for the short term load forecasting in which fuzzyTECH software is employed to manipulate actual value of previous load forecast. To develop fuzzy logic system, three different load profiles from data collection are establish. The fuzzy logic based expert system utilizes the historical relationship between load and drybulb temperature and forecast load for 1-24 hour ahead. Experiments were carried out to develop the short term load forecasting (STLF) system. Based on these experiments a triangular membership function with five linguistic term and twenty five appropriate fuzzy rule base give accurate forecast and it used as a forecaster . Overall forecast give a percentage error less then
5 %. |
| format |
Thesis |
| qualification_level |
Bachelor degree |
| author |
Alang Hassan, Mohd Daud |
| spellingShingle |
Alang Hassan, Mohd Daud 24 hours fuzzy logic technique for load forecasting/ Mohd Daud Alang Hassan |
| author_facet |
Alang Hassan, Mohd Daud |
| author_sort |
Alang Hassan, Mohd Daud |
| title |
24 hours fuzzy logic technique for load forecasting/ Mohd Daud Alang Hassan |
| title_short |
24 hours fuzzy logic technique for load forecasting/ Mohd Daud Alang Hassan |
| title_full |
24 hours fuzzy logic technique for load forecasting/ Mohd Daud Alang Hassan |
| title_fullStr |
24 hours fuzzy logic technique for load forecasting/ Mohd Daud Alang Hassan |
| title_full_unstemmed |
24 hours fuzzy logic technique for load forecasting/ Mohd Daud Alang Hassan |
| title_sort |
24 hours fuzzy logic technique for load forecasting/ mohd daud alang hassan |
| granting_institution |
Universiti Teknologi, MARA (UiTM) |
| granting_department |
Faculty of Electrical Engineering |
| publishDate |
1998 |
| url |
https://ir.uitm.edu.my/id/eprint/100690/1/100690.pdf |
| _version_ |
1811769082734706688 |