Enhancing grid resilience is proposed through the integration of distributed energy resources (DERs) with microgrids. Due to the diverse nature of DERs, there is a need to explore the optimal combined operation of these energy sources within the framework of microgrids. As such, this paper presents the design, implementation and validation of a Model Predictive Control (MPC)-based secondary control scheme to tackle two challenges: optimal islanded operation, and optimal re-synchronization of a microgrid. The MPC optimization algorithm dynamically adjusts input signals, termed manipulated variables, for each DER within the microgrid, including a gas turbine, an aggregate photovoltaic (PV) unit, and an electrical battery energy storage (BESS) unit. To attain optimal islanded operation, the secondary-level controller based on Model Predictive Control (MPC) was configured to uphold microgrid functionality promptly following the islanding event. Subsequently, it assumed the task of power balancing within the microgrid and ensuring the reliability of the overall system. For optimal re-synchronization, the MPC-based controller was set to adjust the manipulated variables to synchronize voltage and angle with the point of common coupling of the system. All stages within the microgrid operation were optimally achieved through one MPC-driven control system, where the controller can effectively guide the system to different goals by updating the MPC’s target reference. More importantly, the results show that the MPC-based control scheme is capable of controlling different DERs simultaneously, mitigating potentially harmful transient rotor torques from the re-synchronization as well as maintaining the microgrid within system performance requirements.
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Unfalsified Switching Adaptive Voltage Control for Islanded Microgrids
Microgrids voltage regulation is of particular importance during both grid-connected and islanded modes of operation. Especially, during the islanded mode, when the support from the upstream grid is lost, stable voltage regulation is vital for the reliable operation of critical loads. This paper proposes a robust and data-driven control approach for secondary voltage control of AC microgrids in the presence of uncertainties. To this end, unfalsified adaptive control (UAC) is utilized to select the best stabilizing controller from a set of pre-designed controllers with the minimum knowledge required from the microgrid. Two microgrid test systems are simulated in MATLAB to verify the effectiveness of the proposed method under different scenarios like load change and communication link failure.
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- Award ID(s):
- 1757207
- NSF-PAR ID:
- 10309596
- Date Published:
- Journal Name:
- IEEE Transactions on Power Systems
- ISSN:
- 0885-8950
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/TPWRS.2021.3133381
