Examinando por Autor "Chong, Kil"

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    Ítem
    Gradient Descent Optimization Based Parameter Identification for FCS-MPC Control of LCL-Type Grid Connected Converter
    (Institute of Electrical and Electronics Engineers Inc., 2022-03-01) Long, Bo; Zhu, Zilin; Yang, Wandi; Chong, Kil; Rodriguez, Jose; Guerrero, Josep M.
    Aging and temperature changes in the passive components of an LCL-filter grid connected converter system (GCCs) may lead to parameter uncertainties, which can in turn influence its modeling accuracy for finite-control-set model predictive control (FCS-MPC). The presence of model errors will change the resonance point and deteriorate the power quality of the grid current, in turn degrading the active damping performance. In this situation, there is a serious possibility that the GCCs may malfunction and automatically disconnect from the grid, causing great challenges to the system stability. To solve this problem, first, prediction error analysis in FCS-MPC due to the model parameter errors is presented. Second, to achieve high accuracy and fast filter parameter estimation in utility, an adaptive online parameter identification method based on gradient descent optimization (GDO) has been proposed. Finally, to further reduce the searching time needed by the optimal iteration step, a variable iteration step searching method based on the root-mean-square-prop (RMSprop) GDO method is proposed. Experimental studies of an LCL-GCCs prototype in the laboratory have been conducted to validate the effectiveness of the proposed method.
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    Ítem
    MPC-Controlled Virtual Synchronous Generator to Enhance Frequency and Voltage Dynamic Performance in Islanded Microgrids
    (Institute of Electrical and Electronics Engineers Inc., 2021-03) Long, Bo; Liao, Yong; Chong, Kil; Rodríguez, José; Guerrero, Josep M.
    The use of high penetration converter-interfaced renewable energy (RE) based microgrids (MGs), due to the absence of rotational masses from conventional synchronous generators (SGs), may lead to a lack of inertia, which may lead the steeper frequency and voltage fluctuations that may in turn cause instability issues and challenges the normal operation of sensitive loads. To suppress these fluctuations and enhance the MGs stability, a novel model predictive control (MPC)-controlled virtual synchronous generator (VSG) for an energy storage system (ESS) is introduced. The proposed method can provide inertia support during transient states and enhance the dynamic characteristics of system voltage and frequency. By establishing the prediction model of VSG and designing the cost function for frequency and power, the increments of the needed active and reactive power are calculated then superposed on the power reference of VSG. The results show that the suppression performance of the voltage and frequency variations under loading transition with the proposed method is better than those of other techniques. Simulation and hardware-in-the-loop (HIL) results further demonstrate the effectiveness of the proposed method.