Abstract
This paper presents a framework to represent short-term operational phenomena associated with renewables capacity factors and final service demand distributions in a capacity-expansion and integrated energy system optimization model. The aim is to study the potential role of energy storage technologies coupled with renewable energy sources aiding the decarbonization of the overall energy system. The proposed methodology is implemented in an energy system optimization model named Tools for Energy Model Optimization and Analysis (TEMOA) and then tested in a case study focused on the Italian energy system. We examine a collection of scenarios that includes reference time scale scenarios, time scale sensitivity scenarios, and technology alternative scenarios. This paper's findings indicate that energy storage is crucial for fully decarbonizing the Italian power sector by 2050 in the absence of a low-carbon baseload. Additionally, it suggests that approximately 10 % of Italy's electricity generation in 2050 should be routed through short-term energy storage devices.
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CITATION STYLE
Nicoli, M., Faria, V. A. D., de Queiroz, A. R., & Savoldi, L. (2024). Modeling energy storage in long-term capacity expansion energy planning: an analysis of the Italian system. Journal of Energy Storage, 101. https://doi.org/10.1016/j.est.2024.113814
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