بناء نظام للتنبؤ بطلب الحمل الكهربائي في بغداد == Build a System For Forecasting The Electrical Load Demand in Baghdad
Author name:
هادي طلال جعفر
Supervisor name:
نشات جاسم محمد
General topic:
Administration and Economics
Specific topic:
Administrative Data System
Degree:
Master
University:
Middle Technical University - Administrative Technical College
Language:
Arabic
University location:
Baghdad
First pages:
07T4804 - p.pdf
Abstract:
This research studies how to build a dynamic system for forecasting the electrical demand in Baghdad city by comparing between Statistical Methods in time series analysis such as Seasonal Auto Regressive Integrated Moving Average model (SARIMA),Transfer Function Model with single input - single output(TFMSISO) and Data Mining techniques in prediction using Artificial Neural Networks model such as (Multi - Layer - perception neural networks with sliding windows (MLP - NN - with sliding windows) and dynamic recurrent neural networks RNN's such as the Non - Linear Auto regressive network with exogenous input (NARX Network)), which studies the dynamic relationship between electricity consumption and its relevant variables exogenous variable such as temperature, the Weekly data from January 2007 to December 2014 for all - electric residences in Baghdad are used for this study.Depending on the automated system that built using (Visual C#, Matlab) the results showed the superiority of the non - linear Auto regressive network with exogenous input (NARX Network)) by using some error criterion
