期刊
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 12, 期 2, 页码 834-846出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2020.3022362
关键词
H-infinity control; lithium-ion batteries; microgrids; power system control; convex optimization; smart grids; voltage-source converter
资金
- Swiss Federal Commission for Innovation and Technology within the SCCER-FURIES
Islanded microgrids face challenges of low power generation capacity and inertia, making them susceptible to frequency and voltage deviations. Battery energy storage systems can be a solution, with a proposed data-driven grid-supporting control system optimizing performance without changes to the inverter's control loops. The data-driven controller is shown to significantly reduce voltage and frequency deviations in real-time simulations.
Islanded microgrids have low real and reactive power generation capacity and low inertia. This makes them susceptible to large frequency and voltage deviations, which deteriorate power quality and can cause frequency or voltage collapse. Grid-supporting battery energy storage systems are a possible solution as they are able to respond quickly to changes of their real and reactive power set-points. In this paper, a data-driven grid-supporting control system for battery energy storage systems, which requires no changes to the inverters inner real and reactive power control loops compared with a conventional grid-supporting inverter, is proposed. Tuning the data-driven controller does not require a dynamic model of the microgrid. Instead, the frequency response of the microgrid is identified and used directly to optimally tune the controller for H-infinity performance and robustness criteria. The performance of the data-driven controller is verified through real-time software-in-the-loop electromagnetic-transient simulation, where it is compared with an inverse-droop controller and is shown to significantly reduce voltage and frequency deviations.
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