  Reliable prediction of system status is a highly demanded functionality of
smart energy systems, which can enable users or human operators to react
quickly to potential future system changes. By adopting the multi-timescale
nexting method, we develop an architecture of human-in-the-loop energy control
system, which is capable of casting short-term predictive information about the
specific smart energy system. The developed architecture does either require a
system model nor additional acquisition of (sensor) data in the existing system
configuration. Our first experiments demonstrate the performance of the
proposed control architecture in an electrical heating system simulation. In
the second experiment, we verify the effectiveness of our developed structure
in simulating a heating system in a thermal model of a building, by employing
natural EnergyPlus temperature data.
