Lars Herre received his B.Sc. degree in Renewable Energy Engineering from the University of Stuttgart, Germany in 2013. He then pursued his Master study at Royal Institute of Technology, Sweden and Technical University of Eindhoven, the Netherlands. He received his M.Sc. degree in Smart Electrical Networks and Systems in 2015. Lars started his PhD research in the Department of Electric Power and Energy Systems at KTH in 2015 and was a visiting researcher at the Michigan Power and Energy Laboratory at the University of Michigan in 2017.
The Role of Flexible Consumers in a Future Power System based on 100% Renewable Energy
In Sweden there is a possibility to have a very high share of renewable power generation. The volatile production of wind and solar power poses challenges to maintaining the balance in the power system. In a power system, the balance must be maintained continuously between total production and consumption. In the current Swedish power system, hydropower is predominantly used for balancing. However, with increasing volatile production the need for balancing reserves increases as well.
A possible resource for balancing reserves is constituted by flexible consumption. With smart meters and progress in ICT infrastructure there is a wide spectrum of opportunities for consumers to become active participants in the electricty market and dynamically adjust their consumption. The purpose of this project is to implement optimization and control methods to the Swedish power system in order to (1) quantify the potential of customer flexibility and (2) explore means to unlock this this potential.
The project is a part of the collaborative research program Energy Systems (Forskarskolan Energisystem). In a parallel project, interviews and surveys are conducted to estimate consumers' ability and willingness to contribute to this flexibility in a future renewable power system. KTH contributes with optimization models to study flexible consumers in a future Swedish power system with large amounts of solar and wind power. The model includes (a) uncertainty in electricity prices, (b) electricity trading in the wholesale market, (c) uncertainty in consumer behavior and availability, (d) uncertainty in ambient temperatures, (e) forecasting/prediction errors, and (f) consumers' capability depending on the devices and individual comfort settings.