Giulio Caprara

Dr. Giulio Caprara


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 February 2026 in Energies
Verified
Journal Article
Open access
PDF file
Diego AndreottiDiego Andreotti
Diego Andreotti
ABAlessandro Borghesi
Alessandro Borghesi
LSLorenzo Saguatti
Lorenzo Saguatti
MGMarco Gabba
Marco Gabba
GCGiulio Caprara
Giulio Caprara
Giuliano RancilioGiuliano Rancilio
Giuliano Rancilio
In recent years, renewable energy production has expanded rapidly, becoming an essential component of the global energy transition. However, the inherent variability and unpredictability of renewable generation require technologies that can provide grid stability and operational flexibility. Battery Energy Storage Systems (BESS) play a central role in addressing this challenge, but their long-term effectiveness depends on a thorough understanding of their degradation mechanisms. This work aims to model and predict the capacity and power degradation of a real-world BESS operating in the electricity market, bridging the gap between laboratory-based ageing studies and field applications. Several degradation indicators, such as available capacity evolution, DC efficiency evolution, conductivity loss, and loss of lithium inventory, were evaluated to determine which models best describe the system’s ageing behaviour. Some estimations were found inaccurate and subsequently excluded, while the remaining analyses enabled a detailed characterisation of BESS performance over time. Using operational data collected between November 2022 and October 2024, results indicate a linear capacity degradation reaching 4.57% over 23 months (490 equivalent cycles), from approximately 9600 kWh to 9150 kWh, with a Mean Absolute Percentage Error (MAPE) of 0.2%. DC efficiency exhibited a two-phase evolution, with an initial rise followed by a slow reduction trend. These findings confirm that ageing effects can be effectively evaluated using operational data, enabling reliable lifetime forecasting for BESS assets.