Casagrande, Vittorio;
Boem, Francesca;
(2023)
Learning-based MPC using Differentiable Optimisation Layers for Microgrid Energy Management.
In:
2023 European Control Conference (ECC).
IEEE: Bucharest, Romania.
Preview |
Text
Casagrande_ECC2023.pdf - Accepted Version Download (309kB) | Preview |
Abstract
In this paper we present a learning-based Model Predictive Control (MPC) algorithm based on differentiable optimisation layers. Recent works show that it is possible to include an optimisation problem as a network layer in a Neural Network (NN) architecture. Here the MPC optimisation problem is integrated on the last layer of a NN which is used to estimate the uncertain parameters of the objective function. The NN is then trained online, end-to-end (E2E), based on previous control actions performance. We show that directly targeting the optimality of the control actions leads to improved control results with respect to the standard method of estimating the uncertain parameters and then perform the optimisation. The effectiveness of the proposed method is illustrated on a microgrid energy management problem where the future profile of the electricity price is not known
| Type: | Proceedings paper |
|---|---|
| Title: | Learning-based MPC using Differentiable Optimisation Layers for Microgrid Energy Management |
| Event: | 2023 European Control Conference (ECC) |
| Location: | Bucharest, Romania |
| Dates: | 13 Jun 2023 - 16 Jun 2023 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.23919/ecc57647.2023.10178300 |
| Publisher version: | https://doi.org/10.23919/ECC57647.2023.10178300 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Renewable energy sources, Uncertainty, Simulation, Artificial neural networks, Microgrids, Prediction algorithms, Energy management |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10174919 |
Archive Staff Only
 |
View Item |
