To reduce the effects of global warning, our energy system has to undergo a transformation to a system with sustainable, de-carbonized energy generation based on local renewable energy sources. To achieve this goal, it is necessary to coordinate a complex system of energy generators, distribution, storage and consumers.
“With background in self-organizing systems and networked systems, we are in an excellent position to contribute to various aspects of smart grids,” Wilfried Elmenreich states. Lakeside Labs projects in this domain address prediction of energy generation and demand, control of smart microgrids, smart metering, detection of legacy devices, and privacy aspects.
Elmenreich and his team developed the microgrid simulator RAPSim, which enables users to implement their own grid objects and control algorithms. His PhD student Dominic Egarter developed algorithms for non-intrusive load monitoring based on load disaggregation of the power draw. “These algorithms can be installed on an embedded system such as our smart energy meter YOMO,” Elmenreich concludes.
Lakeside Labs also led the Austrian-Italian project MONERGY, funded by the European Commission, which collected a fine-grained energy consumption dataset of power drains for households.
Proficiency of power values for load disaggregation
IEEE Transactions on Instrumentation and Measurement, 2016
Integration of legacy appliances into home energy management systems
Journal of Ambient Intelligence and Humanized Computing, 2015
PALDi: Online load disaggregation via particle filtering
IEEE Transactions on Instrumentation and Measurement, 2015
Novel simplified hourly energy flow models for photovoltaic power systems
Energy Conversion and Management, 2014.
HEMS: A home energy market simulator
Computer Science Research and Development, 2014.