Optimization of Battery Energy Storage Systems for Energy Markets and Future Energy Communities

The increasing integration of Renewable Energy Sources (RES) into electrical grids presents also challenges related to grid stability and market dynamics. Battery Energy Storage Systems (BESS) have emerged as a potential solution to these challenges, offering capabilities for energy storage and support services that enhance grid reliability. This paper explores the optimization of the operations of such components with a case study in the Italian electricity market context. The research employs a Mixed-Integer Linear Programming (MILP) model to optimize the participation of BESS in the Day-ahead market, under the specific regulatory framework of a stock martket tender. By analyzing historical data and simulating BESS operations, this study identifies proper strategies to maximize economic returns and enhance the competitive positioning of storage systems in a specific European market context.

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Publication Details

Published
2025-03-07
DOI
https://doi.org/10.1109/icgea64602.2025.11009440
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.73
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article

Optimization of Battery Energy Storage Systems for Energy Markets and Future Energy Communities

Francesco Grimaccia, Sonia Leva, Augustin Marie Thibaut Gillot
1 citations
Electric Vehicles and Infrastructure
0.73
article

Optimization of Battery Energy Storage Systems for Energy Markets and Future Energy Communities

Francesco Grimaccia, Sonia Leva, Augustin Marie Thibaut Gillot
article en
1 citations

Abstract

The increasing integration of Renewable Energy Sources (RES) into electrical grids presents also challenges related to grid stability and market dynamics. Battery Energy Storage Systems (BESS) have emerged as a potential solution to these challenges, offering capabilities for energy storage and support services that enhance grid reliability. This paper explores the optimization of the operations of such components with a case study in the Italian electricity market context. The research employs a Mixed-Integer Linear Programming (MILP) model to optimize the participation of BESS in the Day-ahead market, under the specific regulatory framework of a stock martket tender. By analyzing historical data and simulating BESS operations, this study identifies proper strategies to maximize economic returns and enhance the competitive positioning of storage systems in a specific European market context.

Politecnico di Milano (IT)
Affordable and clean energy
Openalex Percentile: Top 28%
Electric Vehicles and Infrastructure
0.73
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