Power balancing in a DC microgrid elevator system through constrained optimization
Authors
T. Hung Pham, I. Prodan, D. Genon-Catalot, L. Lefèvre
Abstract
This paper considers the problem of power balancing in a DC microgrid. A PH (port Hamiltonian) formalism is used to describe the system components and interconnections. Energy and power conservation are kept for the discretized model. An economic model predictive controller is used for scheduling the microgrid power management. The proposed approach is validated through simulation results on a particular DC microgrid elevator system.
Keywords
DC microgrid; Port-Hamiltonian systems on graphs; MPC (Model Predictive Control)
Citation
- Journal: IFAC-PapersOnLine
- Year: 2017
- Volume: 50
- Issue: 1
- Pages: 19–24
- Publisher: Elsevier BV
- DOI: 10.1016/j.ifacol.2017.08.004
- Note: 20th IFAC World Congress
BibTeX
@article{Pham_2017,
title={{Power balancing in a DC microgrid elevator system through constrained optimization}},
volume={50},
ISSN={2405-8963},
DOI={10.1016/j.ifacol.2017.08.004},
number={1},
journal={IFAC-PapersOnLine},
publisher={Elsevier BV},
author={Pham, T. Hung and Prodan, I. and Genon-Catalot, D. and Lefèvre, L.},
year={2017},
pages={19--24}
}
References
- Biegler, L. T. & Zavala, V. M. Large-scale nonlinear programming using IPOPT: An integrating framework for enterprise-wide dynamic optimization. Computers & Chemical Engineering vol. 33 575–582 (2009) – 10.1016/j.compchemeng.2008.08.006
- Lagorse, J., Paire, D. & Miraoui, A. A multi-agent system for energy management of distributed power sources. Renewable Energy vol. 35 174–182 (2010) – 10.1016/j.renene.2009.02.029
- Lifshitz, D. & Weiss, G. Optimal Control of a Capacitor-Type Energy Storage System. IEEE Transactions on Automatic Control vol. 60 216–220 (2015) – 10.1109/tac.2014.2323136
- Lifshitz, D. & Weiss, G. Optimal energy management for grid-connected storage systems. Optimal Control Applications and Methods vol. 36 447–462 (2014) – 10.1002/oca.2119
- Löfberg, YALMIP: A toolbox for modeling and optimization in MATLAB. (2004)
- Parisio, A., Rikos, E. & Glielmo, L. Stochastic model predictive control for economic/environmental operation management of microgrids: An experimental case study. Journal of Process Control vol. 43 24–37 (2016) – 10.1016/j.jprocont.2016.04.008
- Prodan, I., Zio, E. & Stoican, F. Fault tolerant predictive control design for reliable microgrid energy management under uncertainties. Energy vol. 91 20–34 (2015) – 10.1016/j.energy.2015.08.009
- Schiffer, J. et al. A survey on modeling of microgrids—From fundamental physics to phasors and voltage sources. Automatica vol. 74 135–150 (2016) – 10.1016/j.automatica.2016.07.036
- Touretzky, C. R. & Baldea, M. A hierarchical scheduling and control strategy for thermal energy storage systems. Energy and Buildings vol. 110 94–107 (2016) – 10.1016/j.enbuild.2015.09.049
- van der Schaft, A. J. & Maschke, B. M. Port-Hamiltonian Systems on Graphs. SIAM Journal on Control and Optimization vol. 51 906–937 (2013) – 10.1137/110840091
- Zhao, J. & Dörfler, F. Distributed control and optimization in DC microgrids. Automatica vol. 61 18–26 (2015) – 10.1016/j.automatica.2015.07.015