Document Details

Document Type : Thesis 
Document Title :
SHORT TERM LOAD FORECASTING USING ARTIFICIAL NEURAL NETWORK
التنبؤ بالأحمال الكهربائية على المدى القصير باستخدام تقنية الخلايا الشبكية العصبية
 
Subject : Faculty of Engineering 
Document Language : Arabic 
Abstract : Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models, artificial intelligence, and 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 thesis presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN model is trained with weather-related data, special events indexes and historical electric load-related data. Two ANN models were implemented for one hour ahead, and 24-hours ahead load forecasting. They were tested for one week in different calendar, and religious seasons. The models show very satisfactory results. 
Supervisor : dr.abulaziz m.alshreef 
Thesis Type : Master Thesis 
Publishing Year : 1432 AH
2011 AD 
Added Date : Monday, August 22, 2011 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
إيهاب عبد الرحيم الجديبيALJUDAIBI, EHAB AResearcherMaster 

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