267843
20190812204805.0
CONF
Performance Assessment of Linearized OPF-based Distributed Real-time Predictive Control
2019-06-25
2019-06-25
Conference Papers
We consider the problem of controlling heterogeneous controllable resources of a distribution network with the objective of achieving a certain power flow at the grid connection point while respecting local grid constraints. The problem is formulated as a model predictive control (MPC), where a linearized grid model, to retain convexity, based on sensitivity coefficients (SCs) is used to model the grid constraints. We consider and compare the modelling performance of three different update policies for the SCs: when they are updated once per day considering static injections, updated once per day considering point prediction of the nodal injections, and recursively estimated using on-line measurements. Simulations are performed considering the CIGRÉCIGR´CIGRÉ low voltage benchmark network. Performance is evaluated in terms of convergence speed, tracking error, and constraints modeling errors. Further, we perform a sensitivity analysis on the dominant model w.r.t. the length of the predictive horizon and number of controllable units.
CC BY-SA
Distributed control, energy storage, photovoltaic(PV), linear optimal power flow, sensitivity coefficients.
260528
Gupta, Rahul Kumar
268765
Sossan, Fabrizio
Paolone, Mario
IEEE PES PowerTech
Milan Italy
June 2019
580094
PREPRINT
http://infoscience.epfl.ch/record/267843/files/Performance%20Assessment%20of%20Linearized%20OPF-based%20Distributed%20Real-time%20Predictive%20Control.pdf
rahul.gupta@epfl.ch
252423
darius.farman@epfl.ch
DESL
U12494
Marselli, Béatrice
oai:infoscience.epfl.ch:267843
STI
conf
rahul.gupta@epfl.ch
fantin.reichler@epfl.ch
EPFL
REVIEWED
CONF
overwrite