Balanced smart grid optimization

The project aims to develop many-objective control algorithms for batteries, heat pumps, and ultimately integrated combinations of these devices. The resulting algorithms will support both the development of gas-free residential neighborhoods, even under grid congestion constraints, and the efficient decarbonization of existing neighborhoods. 

• Development of a many-objective control algorithm for battery systems.
• Development of a many-objective control algorithm for heat pumps.
• Development of a many-objective control algorithm for the coordinated control of multiple devices at the neighborhood level

The algorithms will be developed and validated through real-world case studies, such as EnergieRijk Den Haag and Merwede Utrecht. Development and simulation will be conducted in Python, using state-of-the-art optimization tools for the implementation and evaluation of the proposed algorithms.

Co-funding

The project is co-funded through the PhD voucher program of HU University of Applied Sciences Utrecht.

Many challenges in the energy transition appear to be conflicting: residential comfort, low energy costs and reduced emissions, while also ensuring a stable electricity grid. This project explores how these objectives can be pursued simultaneously. By developing intelligent many-objective control algorithms, it creates new opportunities for energy companies, municipalities, and housing associations to support the sustainable and practical decarbonization of residential neighborhoods.