DocumentCode
3228736
Title
Long term electricity demand forecasting using autoregressive integrated moving average model: Case study of Morocco
Author
Citroen, Noreddine ; Ouassaid, Mohammed ; Maaroufi, Mohamed
Author_Institution
Dept. of Electr. Eng., Mohammed V Univ., Rabat, Morocco
fYear
2015
fDate
25-27 March 2015
Firstpage
59
Lastpage
64
Abstract
Electricity demand forecasting is vitally important for power production companies. It has many applications, including energy production scheduling, maintenance and operation of electric network, elaboration of accurate investment and development plans for transmission and distribution networks, negotiation of PPAs (Power Purchase Agreements) and purchasing fuels at optimal costs. Over the last decades, a large variety of mathematical models have been developed for load forecasting, including short-term, medium-term and long term models. This article aims at developing a long term load forecasting model for Moroccan electric grid, using Auto-Regressive Moving Average model. The results are compared to official forecasts of ONEE (Office National de l´Eau et d´Electrcité). This model will be a useful tool for decision makers, to better design investment plans and strategies, aiming at reducing the impact of energy bill on Moroccan economy.
Keywords
autoregressive moving average processes; load forecasting; Morocco; ONEE official forecast; autoregressive integrated moving average model; energy production scheduling; investment plans; load forecasting; long term electricity demand forecasting; Predictive models; Auto-Regressive; demand; electricity; forecast;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Information Technologies (ICEIT), 2015 International Conference on
Conference_Location
Marrakech
Print_ISBN
978-1-4799-7478-8
Type
conf
DOI
10.1109/EITech.2015.7162950
Filename
7162950
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