The future of distribution networks tends to include more and more computational power, embedded intelligence and smart metering on the high voltage level as well as the low voltage micro-grids. Several hardware solutions appeared to implement the so-called smart grids with measurement devices delivering data about the state of networks on various levels.
This work introduces the use of a specific energetic signature for power converters in order to be able to get information on consumption profiles in a non-invasive manner in a residential area where prosumers generate their own energy with photovoltaic cells on their roofs. Technically speaking, the switching elements of power converters inject several harmonics which can be controlled in such a way that information can be transmitted to measurement devices,
A simulated residential grid with several loads and PV converters has been run real-time with 1us sampled data, for being able to retrieve information through data mining methods. A dedicated controller for two power converters has been implemented in such a way that users can be differentiated by looking at the harmonic content of both current and voltage at the point of common coupling.
FUNDING AND PARTNERS
COGENER – Fond SIG-NER
imperix SA, Switzerland
HIL simulation of a microgrid
Grid connected converter with controlled harmonics
Use of Data-mining and pattern recognition