Thesis
Model predictive control of DC microgrids
Washington State University
Master of Science (MS), Washington State University
2018
Handle:
https://hdl.handle.net/2376/100671
Abstract
In this thesis, first, a model predictive control (MPC) of a fuel cell-based DC microgrid for vehicular applications is discussed. The MPC improves the transient response of the FC-based DC microgrid. In this microgrid, a unidirectional converter controls the current of a proton exchange membrane (PEM) fuel cell, and a bidirectional converter controls the output DC link voltage by regulating the battery current. The proposed MPC structure in the continuous control set (CCS) scheme has a fixed switching frequency and employs two different sampling frequencies to provide MPC for both inner and outer control loops. This controller provides a fast response to the changes in the reference values of the control variables or system transients such as load transients. It is also robust against parameter mismatch. Offline and real-time simulation results validate the proposed controller via several simulation case studies. Then, a control of multi-port DC microgrids with a fast transient response and online parameter adaptation is investigated. This DC microgrid can handle connection and disconnection of several energy generation units (e.g., fuel cell or photovoltaic units) and battery energy storage units to provide a DC load. To control several unidirectional and bidirectional converters of this microgrid, a scalable model predictive control (MPC) with online parameter adaptation capability is proposed. This adaptive model predictive control (AMPC), which provides fast MPC control for both inner and outer control loops, obviates the need to have a good knowledge about system parameters (as required by conventional MPC controllers). The estimated values of system parameters are deployed in the MPC controllers to ensure fast transient response of the system. This controller increases the scalability of the system to add or remove new power units with unknown parameters. Simulation case studies validate the proposed controller structure.
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Details
- Title
- Model predictive control of DC microgrids
- Creators
- Asal Zabetian Hosseini
- Contributors
- Ali Mehrizi-Sani (Degree Supervisor)
- Awarding Institution
- Washington State University
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University; [Pullman, Washington] :
- Identifiers
- 99900525006701842
- Language
- English
- Resource Type
- Thesis