battery aging 1battery degradation 1deep learning 1degradation cost 1energy arbitrage 1energy storage systems 1heterogeneous subsystems 1optimization 1probabilistic modeling 1uncertainty quantification 1
From the 2 of 3 linked papers with an AI index.
3 papers
eess.SY2026
Predicting BESS Degradation with Uncertainty Quantification: A Probabilistic Framework for Battery Energy Storage Systems
Melina Graner, Holger Hesse, Andreas Jossen
The paper presents a deep‑learning based probabilistic framework that predicts battery state‑of‑health and quantifies uncertainty, scaling from cell‑level data to whole‑system degr…
eess.SY2026
Accounting for Subsystem Aging Variability in Battery Energy Storage System Optimization
Melina Graner, Martin Cornejo, Holger Hesse +1
The paper proposes an optimization framework for multi‑string battery energy storage systems that incorporates subsystem‑level aging and degradation costs, showing that accounting…
eess.SY2025
Evaluating the Impact of Model Accuracy for Optimizing Battery Energy Storage Systems
Martin Cornejo, Melina Graner, Holger Hesse +1
This study investigates two models of varying complexity for optimizing intraday arbitrage energy trading of a battery energy storage system using a model predictive control approa…