Renewable energy management system for Saudi Arabia: Methodology and preliminary results

Imen Gherboudj, Mohamed Zorgati, Phani Kumar Chamarthi, Arttu Tuomiranta, Baraa Mohandes, Naseema S. Beegum, Jood Al-Sudairi, Omar Al-Owain, Hussain Shibli, Mohamed El-Moursi, Mohamed Hosni Ghedira

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


A Renewable Energy Management System (REMS) has been developed for Saudi Arabia to provide the system operator with the daily day-ahead electrical power generation forecasts. The core models included in REMS are: (i) adapted weather research and forecasting (WRF-solar) model that predicts weather conditions and solar irradiance components based on the aerosol (natural and anthropogenic) properties from CHIMERE chemistry transport model, (ii) renewable power prediction schemes that predict electrical power for specific solar technologies (photovoltaic and concentrating solar power plants) at different scales (plant, substation, area, and country land), and (iii) cutting-edge web-interface and geospatial technologies that enable interactive data visualisation on screens of the power plant characteristics and predicted variables over a four-day time frame (two days prior, current day, and a day ahead). The performance of the REMS was evaluated using the actual power output data from Masdar City 10 MW solar photovoltaic power plant and Shams 100 MW concentrated solar power plant in Abu Dhabi, the United Arab Emirates (UAE). The obtained results show the applicability and accuracy of the modelling framework. Currently, REMS simulates the performance of any set of renewable energy scenarios considering daily day-ahead forecasts. But the eventual use of the system in daily operations coupled with decision-making procedures will ensure efficient monitoring and management of renewable assets over time.

Original languageBritish English
Article number111334
JournalRenewable and Sustainable Energy Reviews
StatePublished - Oct 2021


  • Concentrated solar power
  • Forecast
  • Management system
  • Photovoltaic
  • Power generation
  • Renewables


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