Intelligent Modelling Techniques of Power Load Forecasting for the Western Area of Saudi Arabia

Al-Shareef , A. J.; Abbod , M. F.

doi:10.4197/Eng.21-1.1

Article Details

Intelligent Modelling Techniques of Power Load Forecasting for the Western Area of Saudi Arabia

Authors:

Al-Shareef , A. J. | Abbod , M. F.

Publisher:

King Abdulaziz University : Scientific Publishing Centre

Main Topics:

Engineering and applied operations

Journal:

Journal of King Abdulaziz University: Engineering Sciences 2010 vol.21 Issue 1, pp.3-18

Document Type:

Article

Publication Date:

1/2010

Document Language:

English

Document ID (Org No.):

30495

Frequency:

Bi-Annual

eISSN:

16584260

pISSN:

13191047

DOI:

10.4197/Eng.21-1.1

Descriptors:

Keywords:

Abstract:

 Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This paper presents the development of an ANN-based short-term load forecasting model with improved accuracy for the Regional Power Control Centre of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data, special events indexes and historical electric load-related data using the data from the calendar years 2003, to 2007 for training. Different neural networks topologies have been trained and tested for achieve the optimal topology and ranking the input variables in terms of their importance. Based on the optimal NN topology, the network has been trained to predict the ahead load at different time intervals.

Article Details

Intelligent Modelling Techniques of Power Load Forecasting for the Western Area of Saudi Arabia

Authors:

Al-Shareef , A. J. | Abbod , M. F.

Publisher:

King Abdulaziz University : Scientific Publishing Centre

Main Topics:

Engineering and applied operations

Journal:

Journal of King Abdulaziz University: Engineering Sciences 2010 vol.21 Issue 1, pp.3-18

Document Type:

Article

Publication Date:

1/2010

Document Language:

English

Document ID (Org No.):

30495

Frequency:

Bi-Annual

eISSN:

16584260

pISSN:

13191047

DOI:

10.4197/Eng.21-1.1

Descriptors:

ELECTRICAL ENGINEERING

LOAD MEASUREMENT

FORECASTING

ARTIFICIAL INTELLIGENCE

SAUDI ARABIA

Artificial neural networks

short-term load forecasting

back propagation

Issues

Article Details

Authors: Al-Shareef , A. J. | Abbod , M. F.

Publisher: King Abdulaziz University : Scientific Publishing Centre

Main Topics: Engineering and applied operations

Journal: Journal of King Abdulaziz University: Engineering Sciences 2010 vol.21 Issue 1, pp.3-18

Document Type: Article

Publication Date: 1/2010

Document Language: English

Document ID (Org No.): 30495

Frequency: Bi-Annual

eISSN: 16584260

pISSN: 13191047

DOI: 10.4197/Eng.21-1.1

Descriptors:

Issues

Authors:

Al-Shareef , A. J. | Abbod , M. F.

Publisher:

King Abdulaziz University : Scientific Publishing Centre

Main Topics:

Engineering and applied operations

Journal:

Journal of King Abdulaziz University: Engineering Sciences 2010 vol.21 Issue 1, pp.3-18

Document Type:

Article

Publication Date:

1/2010

Document Language:

English

Document ID (Org No.):

30495

Frequency:

Bi-Annual

eISSN:

16584260

pISSN:

13191047

DOI:

10.4197/Eng.21-1.1