Details
| Original language | English |
|---|---|
| Title of host publication | 2024 63rd IEEE Conference on Decision and Control (CDC) |
| Pages | 6519-6524 |
| ISBN (electronic) | 979-8-3503-1633-9 |
| Publication status | Published - 16 Dec 2024 |
| Event | 2024 IEEE 63rd Conference on Decision and Control (CDC) - Mailand, Italy Duration: 16 Dec 2024 → 19 Dec 2024 |
Publication series
| Name | Proceedings of the IEEE Conference on Decision & Control |
|---|---|
| ISSN (Print) | 0743-1546 |
| ISSN (electronic) | 2576-2370 |
Abstract
Sustainable Development Goals
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2024 63rd IEEE Conference on Decision and Control (CDC) . 2024. p. 6519-6524 (Proceedings of the IEEE Conference on Decision & Control).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Robust Model Predictive Control-Based Energy Management System for the Island Power System of Suðuroy, Faroe Islands
AU - Alferink, Marco
AU - Reus, Lucas
AU - Hofmann, Lutz
AU - Michels, Kai
N1 - Copyright © 2024, IEEE
PY - 2024/12/16
Y1 - 2024/12/16
N2 - In this paper a robust Model Predictive Control (MPC)-based Energy Management System (EMS) is developed and investigated for the case study of Suðuroy, Faroe Islands, under uncertainties resulting from real data. This island power system comprises volatile renewable energy sources, synchronous machines and a Battery Energy Storage System (BESS). In the presented robust MPC both uncertainties from the wind farm power and load demand forecasts are considered. Simulation results are derived from data of one week focusing on the diesel generators’ operational costs and the BESS usage. A comparison against a deterministic MPC-based EMS as well as historical grid operation data is performed. In the presented case study it is shown that both the deterministic MPC and the robust MPC provide significant economic benefits compared to the current grid operation. It is also found that the robust MPC achieves similar performance to the deterministic MPC regarding operational costs. Increased robustness gained through higher state of charge of the BESS is not traded for higher operational costs, highlighting the advantages of the robust MPC-based EMS.
AB - In this paper a robust Model Predictive Control (MPC)-based Energy Management System (EMS) is developed and investigated for the case study of Suðuroy, Faroe Islands, under uncertainties resulting from real data. This island power system comprises volatile renewable energy sources, synchronous machines and a Battery Energy Storage System (BESS). In the presented robust MPC both uncertainties from the wind farm power and load demand forecasts are considered. Simulation results are derived from data of one week focusing on the diesel generators’ operational costs and the BESS usage. A comparison against a deterministic MPC-based EMS as well as historical grid operation data is performed. In the presented case study it is shown that both the deterministic MPC and the robust MPC provide significant economic benefits compared to the current grid operation. It is also found that the robust MPC achieves similar performance to the deterministic MPC regarding operational costs. Increased robustness gained through higher state of charge of the BESS is not traded for higher operational costs, highlighting the advantages of the robust MPC-based EMS.
U2 - 10.1109/CDC56724.2024.10886828
DO - 10.1109/CDC56724.2024.10886828
M3 - Conference contribution
SN - 979-8-3503-1634-6
T3 - Proceedings of the IEEE Conference on Decision & Control
SP - 6519
EP - 6524
BT - 2024 63rd IEEE Conference on Decision and Control (CDC)
T2 - 2024 IEEE 63rd Conference on Decision and Control (CDC)
Y2 - 16 December 2024 through 19 December 2024
ER -