Midterm load forecasting analysis for Erbil governorate based on predictive models
Author
Source
ZANCO Journal of Pure and Applied Sciences
Issue
Vol. 32, Issue 3 (30 Jun. 2020), pp.20-29, 10 p.
Publisher
Salahaddin University-Erbil Department of Scientific Publications
Publication Date
2020-06-30
Country of Publication
Iraq
No. of Pages
10
Main Subjects
Abstract EN
Electrical power supply is becoming more and more complex as a result of expansion, growing population, and unsuitable planning of administration and peoples.
electrical power load forecasting may be defined as the process of predicting electrical load values for future of the system with respect to current demands.
this analysis is an important procedure for the power system planners and the demand controllers to ensure that the system can generate sufficient of electricity for different kinds of terms such as short, medium and long term load forecasting.
the forecasting analysis allows us to manage the electrical loads with the increasing demand.
for that purpose, we have used some predictive models to analyze of electrical load forecasting for Erbil governorate in Iraq.
this analysis helps us to manage our planning better, arrange system maintenance plan and enhance fuel control.
this study raises an attempt for forecasting the peak (upper limit) monthly demand of electric power for one year ahead.
simple linear regression model and auto regressive integrated moving average model were applied as forecasting models for a power consumer’s dataset for the purpose of predicting forthcoming year electricity load demand.
, also forecasting models are then validated using some indicators, indicator used is root mean square error (RMSE) ,which is conceded a statistic metric that is commonly used for accuracy evaluation of lf methods, and mean absolute error (MAE) both used as a forecasting accuracy criteria.
American Psychological Association (APA)
Ali, Wardah Husayn. 2020. Midterm load forecasting analysis for Erbil governorate based on predictive models. ZANCO Journal of Pure and Applied Sciences،Vol. 32, no. 3, pp.20-29.
https://search.emarefa.net/detail/BIM-1402242
Modern Language Association (MLA)
Ali, Wardah Husayn. Midterm load forecasting analysis for Erbil governorate based on predictive models. ZANCO Journal of Pure and Applied Sciences Vol. 32, no. 3 (2020), pp.20-29.
https://search.emarefa.net/detail/BIM-1402242
American Medical Association (AMA)
Ali, Wardah Husayn. Midterm load forecasting analysis for Erbil governorate based on predictive models. ZANCO Journal of Pure and Applied Sciences. 2020. Vol. 32, no. 3, pp.20-29.
https://search.emarefa.net/detail/BIM-1402242
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 28-29
Record ID
BIM-1402242