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.
Published Version
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