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Eco-District, an Ideal Framework to Initiate Large-Scale Urban Energy Renovation in Morocco

Echlouchi Khalid, Ouardouz Mustapha, Bernoussi Abdes-Samed

Journal of Ecological Engineering

2022

Vol. 23, nr 9

100--114

In the perspective of the large-scale application of the Moroccan Thermal Construction Regulations (RTCM) to existing buildings, eco-districts represent an ideal framework to initiate, test, and evaluate such an action. This study aims to present a methodological framework to improve the decision-making process for the energy upgrade of a future eco-district transformation. The case study of a neighborhood in northern Morocco shows that thermal insulation of buildings allows a significant reduction of energy needs that can reach an average annual gain of 52.72% compared to the existing situation. While installing PV systems on 50% of the roof surfaces allows a more critical improvement of the obtained gain: the average annual income in the case of monocrystalline PV can reach 108.14% and 94.87% for polycrystalline PV at the scale of the district.

A Proposed Model to Forecast Hourly Global Solar Irradiation Based on Satellite Derived Data, Deep Learning and Machine Learning Approaches

Benamrou Badr, Ouardouz Mustapha, Allaouzi Imane, Ben Ahmed Mohamed

Journal of Ecological Engineering

2020

Vol. 21, nr 4

26--38

An accurate short-term global solar irradiation (GHI) forecast is essential for integrating the photovoltaic systems into the electricity grid by reducing some of the problems caused by the intermittency of solar energy, including rapid fluctuations in energy, management storage, and the high costs of electricity. In this paper, the authors proposed a new hybrid approach to forecast hourly GHI for the Al-Hoceima city, Morocco. For this purpose, a deep long short-term memory network is trained on a combination of the hourly GHI ground measurements from the meteorological station of Al-Hoceima and the satellite-derived GHI from the neighbouring pixels of the point of interest. Xgboost, Random Forest, and Recursive Feature Elimination with cross-validation were used to select the most relevant features, the lagged satellite-derived GHI around the point of interest, as input to the proposed model where the best forecasting model is selected using the Grid Search algorithm. The simulation and results showed that the proposed approach gives high performance and outperformed other benchmark approaches.