Characterization and optimal control of energy flexibility in industrial production plants

This research project focuses on defining a unified approach for identifying and exploiting the use of unexplored industrial energy flexibility. A need for this comes from the rapid increase in the penetration of renewable energy sources into the energy network, causing uncertainties in energy production. Consequently, there is a mismatch between the required and available flexibilities to maintain a reliable electricity system. Although demand response has been identified as a solution for this challenge, the flexibility offered by industrial production facilities is still not clearly defined. Therefore, the fundamental research revolves around 1) innovative methods to model industrial consumers in a way that all potential flexibility becomes available, 2) the control of this flexibility via state-of-the-art techniques based on Machine Learning, and 3) explore current and novel remuneration techniques for this flexibility. A byproduct of this research project will be an open-source tool that allows to model and optimize production planning and scheduling in industrial production plants by considering the constraints and dynamics of energy networks. This will result in reduced energy costs, a more reliable electricity system, and a potential reduction in the system’s carbon intensity.