Casagrande, V;
Ferianc, M;
Rodrigues, M;
Boem, F;
(2024)
Learning-based MPC with uncertainty estimation for resilient microgrid energy management.
In:
IFAC-PapersOnLine.
(pp. pp. 556-561).
Elsevier BV
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Abstract
To enhance fault resilience in microgrid systems at the energy management level, this paper introduces a novel proactive scheduling algorithm, based on uncertainty modelling thanks to a specifically designed neural network. The algorithm is trained and deployed online and it estimates uncertainties in predicting future load demands and other relevant profiles. We integrate the novel learning algorithm with a stochastic model predictive control, enabling the microgrid to store sufficient energy to adaptively deal with possible faults. Experimental results show that a reliable estimation of the unknown profiles' mean and variance is obtained, improving the robustness of proactive scheduling strategies against uncertainties.
| Type: | Proceedings paper |
|---|---|
| Title: | Learning-based MPC with uncertainty estimation for resilient microgrid energy management |
| Event: | 19th IFAC World Congress |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.ifacol.2024.07.277 |
| Publisher version: | https://doi.org/10.1016/j.ifacol.2024.07.277 |
| Language: | English |
| Additional information: | © 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
| Keywords: | Energy Management Systems, Microgrid, Model Predictive Control, Online Learning, Uncertainty Estimation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10197014 |
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