Power Tools for AI Engineers With Deadlines

Developed a reinforcement learning framework using Deep Q-Networks (DQN) to optimize scheduling in Wireless Sensor Networks (WSN), enhancing energy efficiency and state estimation through a custom simulation environment.

Software controller for efficient charging of electric vehicles using home solar power

Energy storage, PV(renewable) generation, Grid Optimization

AI based heat pump optimisation. Cheaper and greener heating

Intelligent Power Management & Task Scheduling for Real-Time Embedded Systems | Reinforcement Learning meets DVFS for Maximum Efficiency

This project uses machine learning to predict solar energy output based on historical weather and solar data. It includes data preprocessing, model training, and performance evaluation, providing insights to optimize energy production.

Optimize the charging of your car according to energy market prices

This repository contains Jupyter Notebooks focused on the simulation and analysis of synchronous machines, covering inductance calculations, magnetic fields, and comparative analyses of various models.

RESTful API for 'ewh-flex' project, developed within the scope of European Project ENERSHARE

Optimize Thermoelectric Water Heaters (EWH) schedules based on electricity consumption data, ensuring user comfort while minimizing operational costs.

A Python-based home energy system simulator for optimizing solar, battery, and grid power flows using configurable strategies

ESS dispatch & size optimisation with RES

"This repository contains codes, input files, output data, and analyses related to the energy optimization of molecular structures using software such as Gaussian, Orca, PELE, and OPTIM."

A collection of scientific papers and other documents about my research activity during my PhD in Electrical Engineering at Politecnico di Torino - Dipartimento Energia "Galileo Ferraris"

Customized environment utilizing the OpenAI Gym library for controlling battery energy storage systems in multi-microgrids

VAPOS (Vibrational and Power Optimizing Software)

Energy system simulation framework that optimizes generation portfolios using AI-based genetic algorithms. Models hourly power dispatch, battery management, and source failures over multi-year horizons to evaluate reliability and economic performance of diverse energy mixes.