Technical Integration

At TU Delft, we do research into the value of exergy analysis in sustainability assessments of future energy supply systems.

A major challenge in striving for a more sustainable society is the selection of technological systems. In order to assess which technological system is preferable, the loss of work potential, also known as exergy loss, can be compared for various technologies. Exergy analysis is a thermodynamic assessment method that makes visible where work potential is lost. The smaller the exergy loss, the more efficient a technologies works, in terms of resources and energy use. From a sustainability point of view, it is important to use exergy wisely. However, exergy analysis is not part of the regular sustainability assessment methods.

See more on this website.

For research on smart grids we team up with the TU Delft PowerWeb Platform, that comprises the integrated study of the underlying physical systems (hardware), the design of smart energy management systems (software), and the study of smart grids in relation to their societal and economic environment (peopleware). The aim is to model and design ICT systems that integrate energy production and consumption services in a robust way.

The major research challenges are the accurate prediction of supply and demand. We need to develop learning algorithms and advanced control systems to manage the uncertainties.

The energy transition requires much more efficient energy use and a matching of energy demand and supply. At a household level, this can be achieved through smart home appliances, and at a local level via smart grids. Smart meters and thermostats are already widely installed, but their potential is not fully exploited yet. Whereas home owners with solar panels often embrace smart meters to monitor the own energy production, many citizens are suspicious of the use of personal data. Future energy systems therefore need smart systems for monitoring and control, the underlying models need to be optimized constantly, and the ethical use of the data needs to be ensured.  Consumers participation is key in the successful implementation of these systems.

At TU Delft we work at research challenges related to smart energy systems: advanced energy diagnosis systems and self-learning and self-optimising energy management systems. In our optimisation studies, we target multiple levels, next to energy use also comfort, air quality and costs. We make use of big data for real-time performance assessment and a better understanding of occupant behaviour and energy rebound. In all systems we develop, we safeguard the user’s privacy by design.