Modeling energy storage in long-term capacity expansion energy planning: an analysis of the Italian system

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.

Authors

Institutions

Publication Details

Journal
Journal of Energy Storage
Published
2024-09-19
DOI
https://doi.org/10.1016/j.est.2024.113814
Citations
22
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
4.59

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling energy storage in long-term capacity expansion energy planning: an analysis of the Italian system

Laura Savoldi, Matteo Nicoli, Victor Faria, Anderson Rodrigo de Queiroz
22 citations
Journal of Energy Storage
Integrated Energy Systems Optimization
4.59
article

Modeling energy storage in long-term capacity expansion energy planning: an analysis of the Italian system

Laura Savoldi, Matteo Nicoli, Victor Faria, Anderson Rodrigo de Queiroz
article en
22 citations

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.

Journal of Energy StorageVol. 101
North Carolina Central University (US), North Carolina State University (US), Politecnico di Torino (IT)
Eni
Affordable and clean energy
Openalex Percentile: Top 5%
Integrated Energy Systems Optimization
4.59
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.