Alejandro Andres Flores Chacon

I am a PhD candidate in the Heat and Power Technology division within the Department of Energy Technology. My research focuses on developing AI-driven methods to characterize and better understand the performance of stationary battery energy storage systems. The work explores the design of data-driven models for improved generalization and characterization of battery ageing, with the goal of effectively incorporating degradation effects into the dispatch optimization of battery assets across different operational strategies and electricity market participation schemes. The project is conducted within the ALT-BESS initiative and will include real life validation through access to the Live-In Lab case study. The research is carried out in collaboration with industrial and academic partners, such as EnBrilion and the University of Skövde.

Background

I have a background in Mechanical Engineering from Universidad Metropolitana in Caracas, Venezuela. In addition, I completed the Erasmus Mundus Joint Master's Degree in Smart Decentralized Energy Systems (DENSYS). The first year of the program focused on energy systems at Université de Lorraine in France, followed by a specialization track in Energy Storage and Power-to-X at Politecnico di Torino. I completed the program with a thesis on detailed degradation diagnosis of lithium-ion batteries using machine learning models trained on digital twin data.