![](bg8.png)
used as the disturbance (P_res-P_loads) in the smart
grids as in Fig.1.
The evaluation results are presented in Fig. 15.
One can see that the maximal power of the
renewable energy sources minus other loads is
130kW, but the maximal power of agent0 (through
transformer) is only 70kW. This evaluation results
prove that the architecture and principles (in
particular the virtual agent as presented in this
paper) can optimize (flatten) the average power flow
in the electric power distribution networks.
7 CONCLUSIONS
Market based operation in smart grids will ensure
fair transaction of electricity and enable more time
shift-able sources and loads involving in the
reconciliation of power imbalance. Particularly,
agent-based control and event-based control in smart
grids will change the characteristics of electric
power networks.
However, the power balance only between the
sources and the loads in agent-based control is not
sufficient to guarantee an appropriate power flow in
the electric power distribution networks. By
introducing a virtual agent, the principle of power
management in smart grids has been enhanced and
presented in this paper. The evaluation results show
that the average power flow in case of the
integration of renewable energy sources and
fluctuated loads can effectively be optimized by
applying our method of power management.
As there is a significant response time in demand
side management (via the ICT infrastructures), short
duration energy storage might be required, to ensure
the power quality in the smart grids, if the power
fluctuation due to the renewable energy sources (e.g.
PVs) or/and other fast varied loads is significant. In
this case, the possibly time shift-able and
controllable sources and loads of office building
(e.g. plug-in electric vehicles with super capacitors)
can be treated as another means of grid control. As a
result, power balance in smart grids can be achieved
in the different time scales with less additional
energy storages.
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