Balancing supply and demand in future energy systems

Dynamic pricing can be used to balance future energy grids which depend on renewable energy. CWI researcher Nicolas Höning developed several market mechanisms and pricing strategies which are useful for planning and balancing electricity supply and demand.

Publication date: 17-06-2016

Dynamic pricing can be used to balance future energy grids which depend on renewable energy. CWI researcher Nicolas Höning developed several market mechanisms and pricing strategies which are useful for planning and balancing electricity supply and demand. He defended his thesis on this topic on Friday 27 May at the Delft University of Technology.

Our future energy system is expected to steer away from fossil fuels towards renewable energy, such as solar and wind power. This development will make planning and balancing of supply and demand more challenging. On the supply side, energy generation will become largely dependent on weather conditions. And on the demand side, the mobility patterns of electrical vehicle users will for instance greatly influence energy consumption. Currently, supply and demand are balanced through coordinated generation in power plants. With energy generation spread over solar panels and wind turbines with numerous owners, new mechanisms need to be developed to balance supply and demand.

In his thesis, Höning develops market mechanisms and dynamic pricing strategies that can deal with this challenge. He addresses the peaks that can occur during intervals with very high power flow, or with high differences between demand and supply. Such peaks can result in steep price movements and even infrastructural problems due to overload. Höning develops market mechanisms that enable the planning of consumption and generation of energy ahead of time and also encourage short-term adaptations. He also investigates mechanisms that protect small participants from high risks when participating in the energy market, and the use of smart storage devices for network protection. For all these issues, Höning proposes solutions using agent-based models, and evaluates these solutions using computer simulations.

This research was carried out in the Intelligent Systems group at CWI under supervision of Prof. Han La Poutré (CWI/TU Delft), and was funded by Rijskdienst voor Ondernemend Nederland (RVO).