Multi-market participation & optimization with battery storage in a virtual power plant

This project intends to demonstrate the potential of a data-driven method to improve the profitability and resource efficiency of battery storage systems integrated with a virtual power plant.

The project intends to develop statistical models using machine learning to enable multi-market optimization for battery storage systems connected to a virtual power plant. Markets that are investigated are ancillary services for frequency containment run by Svenska kraftnät.

The aim of the project is to show an improved control method and profitability for battery storage systems and thereby increase the willingness to invest and accelerate the energy transition by increasing the supply of flexibility in the energy system.