Reference:
M. Picallo,
A. Anta, and
B. De Schutter,
"Stochastic optimal power flow in distribution grids under uncertainty
from state estimation," Proceedings of the 57th IEEE Conference on
Decision and Control, Miami Beach, Florida, pp. 3152-3158, Dec.
2018.
Abstract:
The increasing amount of controllable generation and consumption in
distribution grids poses a severe challenge in keeping voltage values
within admissible ranges. Existing approaches have considered
different optimal power flow formulations to regulate distributed
generation and other controllable elements. Nevertheless, distribution
grids are characterized by an insufficient number of sensors, and
state estimation algorithms are required to monitor the grid status.
We consider in this paper the combined problem of optimal power flow
under state estimation, where the estimation uncertainty results into
stochastic constraints for the voltage magnitude levels instead of
deterministic ones. To solve the given problem efficiently and to
bypass the lack of load measurements, we use a linear approximation of
the power flow equations. Moreover, we derive a transformation of the
stochastic constraints to make them tractable without being too
conservative. A case study shows the success of our approach at
keeping voltage within limits, and also shows how ignoring the
uncertainty in the estimation can lead to voltage level violations.