Reference
T. Pippia, J. Sijs, and B. De Schutter, "A parametrized model predictive
control approach for microgrids,"
Proceedings of the 57th IEEE
Conference on Decision and Control, Miami Beach, Florida, pp. 3171-3176,
Dec. 2018.
Abstract
We propose a parameterized Model Predictive Control (MPC) approach for optimal
operation of microgrids. The parameterization expresses the control input as a
function of the states, variables, and parameters. In this way, it is possible
to apply an MPC approach by optimizing only the parameters and not the inputs.
Moreover, the value of the binary control variables in the model is assigned
according to parameterized heuristic rules, thus obtaining a formulation for
the optimization problem that is more scalable compared to standard approaches
in the literature. Furthermore, we propose a control scheme based on one single
controller that uses two different sampling times and prediction models. By
doing so, we can include both fast and slow dynamics of the system at the same
level. This control approach is applied to an operational control problem of a
microgrid, which includes local loads, local production units, and local energy
storage systems and results show the effectiveness of the proposed approach.
Publisher page
Downloads
BibTeX
@inproceedings{PipSij:18-019,
author = {Pippia, Tom{\'{a}}s and Sijs, Joris and De Schutter, Bart},
title = {A Parametrized Model Predictive Control Approach for
Microgrids},
booktitle = {Proceedings of the 57th IEEE Conference on Decision and
Control},
address = {Miami Beach, Florida},
pages = {3171--3176},
month = dec,
year = {2018}
}