Incorporating VRE into long-term planning in Arab countries
In light of ambitious targets set by governments in the MENA region, an accurate representation of variable renewable power generation in long-term models for power sector transition has become critical to ensure the reliability of supply.
IRENA Members, including several countries in the MENA region, have expressed a keen interest in improving their energy planning practices to better account for the variability of wind and solar power. In order to address this specific challenge, IRENA initiated the Addressing Variable Renewable Energy in Long-Term Energy Planning (AVRIL) project in 2013. Building on the expertise gained through various discussions and sessions held under the AVRIL project, IRENA released its Planning for the Renewable Future – long-term modelling and tools to expand variable renewable power in emerging economies report in January 2017.
Building on this report, the five-day regional training addressed renewable energy planning through a targeted training focused on energy planners on capacity expansion planning with variable renewable energy to exchange on best practices for using modelling tools and available renewable energy data to discuss VRE planning. The training was facilitated though the support of IRENA, along with regional partners including LAS, RCREEE and IsDB, thus highlighting the importance of addressing variability in renewable energy systems.
The primary objective was to exchange and discuss the regional - as well as global - best practices to enhance capacity expansion planning to achieve significant RE deployment. Participants encountered novel, cutting-edge approaches, and emerged with new ideas that could be applied in their national and/or regional planning contexts. The workshop identified major planning gaps, which could potentially be addressed through follow-up bilateral technical cooperation projects.
Introduction and workshop overview
Key long-term planning consideration with a higher share of VRE
System Flexibility: Representation in energy planning models