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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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Optimal Sizing of Battery Energy Storage Systems for Small Modular Reactor based Microgrids
Battery energy storage systems (BESS) are increasingly deployed in microgrids due to their benefits in improving system reliability and reducing operational costs. Meanwhile, advanced small modular reactors (SMRs) offer many advantages, including relatively small physical footprints, reduced capital investment, and the ability to be sited in locations not possible for larger nuclear plants. In this paper, we propose a bi-level operational planning model that enables microgrid planners to determine the optimal BESS size and technology while taking into account the optimal long-term (a yearly simulation with a 15-min resolution) operations of a microgrid with SMRs and wind turbines. Case studies are performed using realistic BESS and grid data for two BESS technologies, i.e., Li-Ion battery and compressed air energy storage. Numerical results show the effectiveness of the proposed bi-level model. The pros and cons of the two BESS technologies are also revealed.
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- Award ID(s):
- 1856084
- PAR ID:
- 10322843
- Date Published:
- Journal Name:
- 2021 IEEE Kansas Power and Energy Conference (KPEC)
- 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
- Conference Paper:
- https://doi.org/10.1109/KPEC51835.2021.9446203
