Abstract

Hourly resolution is essential to realistically address the matching of supply and demand for fluctuating energy sources like solar and wind. This work introduces a novel method to model energy variability in an Integrated Assessment Model building upon a previous work, where regression analysis was utilized to extract hourly -level information from an energy system model. The enhancements include: (1) improved experimental design and more efficient computing, and (2) modelling the management of variability in an integrated assessment model by (i) incorporating a portfolio of flexibility options, and (ii) offering the ability to regulate system curtailment by limiting the expansion of renewables. The scenarios focus on the electricity sector, mirroring current EU27 ' s policies that aim for higher renewable energy and electrification contributions by 2050. Without any variability control measures, significant curtailment (up to 60 %) is observed, the introduction of flexibility options reducing it to half (30 %). Controlling the capacity expansion of renewables is introduced to avoid this unrealistically high curtailment, allowing the model to achieve a penetration of renewables in electricity of 80 % and a 53 % reduction in greenhouse gas emissions compared to 2015 levels in the electricity system. In conclusion, the methodology employed yields broadly consistent outcomes.