Smart Grid Challenges in Morocco and an Energy Demand Forecasting with Time Series

Facing development requirements and changes in the global energy context, Morocco has begun a process of diversification of the national energy mix in favor of renewable energy, while ensuring a competitive energy, in terms of costs, availability of products and their security and sustainability. Wi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of engineering research in Africa (Print) 2022-07, Vol.61, p.195-215
Hauptverfasser: Mahmoudi, Morad, El Abbassi, Ikram, El Barkany, Abdellah, Meliani, Meryem
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Facing development requirements and changes in the global energy context, Morocco has begun a process of diversification of the national energy mix in favor of renewable energy, while ensuring a competitive energy, in terms of costs, availability of products and their security and sustainability. Within this framework, Morocco launched in 2009 a national energy strategy whose major orientations focus on the security of energy supply and the generalization of its access, the preservation of the environment, through the use of renewable energy, energy efficiency, the strengthening of interconnection and regional cooperation. Through this article, the current state of the Moroccan network will be studied, as well as its potential in terms of renewable energy. Some strategies to overcome the challenges facing smart grid deployment in Morocco will also be presented. Then, the long-term energy demand, generation capacity, and renewable energy evolution in Morocco around 2030 will be estimated based on a time series using the artificial neural network method, which can be injected into the grid without causing any transit restrictions on the utility network or on the whole power system. As a result, the wind power available capacity was estimated to be 4087 MW, and the solar power available capacity was estimated to be 4713 MW by 2030. These results will be then compared to those estimated with the mathematical method. As well as, with the accuracy results of similar studies with different time series forecasting techniques. The accuracy value of this study is between 1.2% and 3.5%. So, the performance and viability of the proposed model can be studied.
ISSN:1663-3571
1663-4144
1663-4144
DOI:10.4028/p-2gufv6