Now that the use of renewable energy sources within our electricity network is on the increase, there is a growing demand for new technologies and processes that enable those energy sources to be integrated within the existing model. Interoperability forms a crucial challenge with regard to the energy market of tomorrow.

Identifying and smartly controlling flexible consumers is essential, both to provide load-balancing on a system level and to prevent or resolve local network issues. Buildings equipped with local (PV) production, batteries (stationary or in the form of an electric vehicle) and electrical (heat-pump based) heating, cooling and hot water production systems are highly suitable for this. Utilising and valorising this flexibility also dovetails with the vision and ambition to engage prosumers as more active participants in the energy system by allowing them to valorise their available flexibility as a support service.

Publications

Thermal load forecasting in district heating networks using deep learning and advanced feature selection methods
Year: 
2018
Journal: 
ENERGY
Suryanarayana, G; Lago, J; Geysen, D; Aleksiejuk, P; Johansson, C
Valuing Demand Response Controllability via Chance Constrained Programming
Year: 
2018
Journal: 
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Bruninx, K; Dvorkin, Y; Delarue, E; D'haeseleer, W; Kirschen, DS
Operational thermal load forecasting in district heating networks using machine learning and expert advice
Year: 
2018
Journal: 
ENERGY AND BUILDINGS
Geysen, D; De Somer, O; Johansson, C; Brage, J; Vanhoudt, D
Applicability of a Clustered Unit Commitment Model in Power System Modeling
Year: 
2018
Journal: 
IEEE TRANSACTIONS ON POWER SYSTEMS
Meus, J; Poncelet, K; Delarue, E

Pages