Mathematics for energy systems: modeling, simulation and analysis
As society embraces renewable energy, decentralized and volatile energy production, driven by solar and wind power stations, presents challenges in grid topology, system management, load planning, and storage capacity.
This project aims to propose control schemes addressing these issues. Our approach combines data-driven and theoretical strategies, involving synthetic data generation for mining and mean-field games approaches for energy producers and consumers. Validation of the proposed methodologies relies on data acquired from our industry collaborators actively immersed in the SOLVE project. Solving challenges involves finding optimal incentives to address congestion and energy shortages, validated through data.
Funding has been provided by the Swedish Energy Agency through the project Solar Electricity Research Centre, Sweden (SOLVE), grant number 52693-1.
Research Group Members: PhD Nicklas Jävergård, Professor in Mathematics Adrian Muntean and Assistant Professor of Mathematics Grigor Nika.
