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.
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BibTeX
@inproceedings{PicAnt:18-017,
author = {Picallo, Miguel and Anta, Adolfo and De Schutter, Bart},
title = {Stochastic Optimal Power Flow in Distribution Grids Under
Uncertainty from State Estimation},
booktitle = {Proceedings of the 57th IEEE Conference on Decision and
Control},
address = {Miami Beach, Florida},
pages = {3152--3158},
month = dec,
year = {2018}
}