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1. Time Delay of Wide Area Damping Control in Urban Power Grid: Model-Based Analysis and Data-Driven Compensation

   https://doi.org/10.3389/fenrg.2022.895163  

   She, Buxin; Dong, Yuqing; Liu, Yilu (April 2022, Frontiers in Energy Research)

   Due to the rapid development of economies, large urban cities consume an increasing amount of energy and have a higher requirement for power quality. Voltage source converter based high voltage direct current (VSC-HVDC) is a promising device to transmit clean power from remote regions to urban power systems, while also providing wide area damping control (WADC) for frequency stabilization. However, the time-delay naturally existing in the VSC-HVDC system may degrade the performance of WADC and even result in instability. To address this issue, this paper develops a time-delay correction control strategy for VSC-HVDC damping control in urban power grids. First, a small signal model of WADC is built to analyze the negative impacts of time delay. Then, a data-driven approach is proposed to compensate for the inherent time delay in VSC-HVDC damping control. The extensive training data will be generated under various disturbances. After offline training, the long short-term memory network (LSTM) can be implemented online to predict the actual frequency deviation based on real-time measurements. Finally, the proposed method is validated through MATLAB-Simulink in a two-area four-machine system. The results indicate that the data-driven compensation has a strong generalization ability for random delay time constants and can improve the performance of WADC significantly. 

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2. Frequency Scan–Based Mitigation Approach of Subsynchronous Control Interaction in Type-3 Wind Turbines

   https://doi.org/10.3390/en14154626  

   Alatar, Faris; Mehrizi-Sani, Ali (August 2021, Energies)

   null (Ed.)

   Integration of wind energy resources into the grid creates several challenges for power system dynamics. More specifically, Type-3 wind turbines are susceptible to subsynchronous control interactions (SSCIs) when they become radially connected to a series-compensated transmission line. SSCIs can cause disruptions in power generation and can result in significant damage to wind farm (WF) components and equipment. This paper proposes an approach to mitigate SSCIs using an online frequency scan, with optimized phase angles of voltage harmonic injection to maintain steady-state operation, to modify the controllers or the operating conditions of the wind turbine. The proposed strategy is simulated in PSCAD/EMTDC software on the IEEE second benchmark model for subsynchronous resonance. Simulation results demonstrate the effectiveness of this strategy by ensuring oscillations do not grow. 

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3. Impedance Profile Prediction for Grid-Connected VSCs With Data-Driven Feature Extraction

   https://doi.org/10.1109/TPEL.2024.3495214  

   Wu, Yang; Wu, Heng; Cheng, Li; Zhou, Jianyu; Zhou, Zichao; Chen, Minjie; Wang, Xiongfei (February 2025, IEEE Transactions on Power Electronics)

   Data-driven approach is promising for predicting impedance profile of grid-connected voltage source converters (VSCs) under a wide range of operating points (OPs). However, the conventional approaches rely on a one-to-one mapping between operating points and impedance profiles, which, as pointed out in this article, can be invalid for multiconverter systems. To tackle this challenge, this article proposes a stacked-autoencoder-based machine learning framework for the impedance profile predication of grid-connected VSCs, together with its detailed design guidelines. The proposed method uses features, instead of OPs, to characterize impedance profiles, and hence, it is scalable for multiconverter systems. Another benefit of the proposed method is the capability of predicting VSC impedance profiles at unstable OPs of the grid-VSC system. Such prediction can be realized solely based on data collected during stable operation, showcasing its potential for rapid online state estimation. Experiments on both single-VSC and multi-VSC systems validate the effectiveness of the proposed method. 

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4. Wind farms providing secondary frequency regulation: evaluating the performance of model-based receding horizon control

   https://doi.org/10.5194/wes-3-11-2018  

   Shapiro, Carl R.; Meyers, Johan; Meneveau, Charles; Gayme, Dennice F. (January 2018, Wind Energy Science)

   This paper is an extended version of our paper presented at the 2016 TORQUE conference (Shapiro et al., 2016). We investigate the use of wind farms to provide secondary frequency regulation for a power grid using a model-based receding horizon control framework. In order to enable real-time implementation, the control actions are computed based on a time-varying one-dimensional wake model. This model describes wake advection and wake interactions, both of which play an important role in wind farm power production. In order to test the control strategy, it is implemented in a large-eddy simulation (LES) model of an 84-turbine wind farm using the actuator disk turbine representation. Rotor-averaged velocity measurements at each turbine are used to provide feedback for error correction. The importance of including the dynamics of wake advection in the underlying wake model is tested by comparing the performance of this dynamic-model control approach to a comparable static-model control approach that relies on a modified Jensen model. We compare the performance of both control approaches using two types of regulation signals, RegA and RegD, which are used by PJM, an independent system operator in the eastern United States. The poor performance of the static-model control relative to the dynamic-model control demonstrates that modeling the dynamics of wake advection is key to providing the proposed type of model-based coordinated control of large wind farms. We further explore the performance of the dynamic-model control via composite performance scores used by PJM to qualify plants for regulation services or markets. Our results demonstrate that the dynamic-model-controlled wind farm consistently performs well, passing the qualification threshold for all fast-acting RegD signals. For the RegA signal, which changes over slower timescales, the dynamic-model control leads to average performance that surpasses the qualification threshold, but further work is needed to enable this controlled wind farm to achieve qualifying performance for all regulation signals. 

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5. A 99.7% Efficient 300 W Hard Disk Drive Storage Server with Multiport Ac-Coupled Differential Power Processing (MAC-DPP) Architecture

   https://doi.org/10.1109/ECCE.2019.8911853  

   Wang, Ping; Chen, Yenan; Kushima, Parker; Elasser, Youssef; Liu, Ming; Chen, Minjie (September 2019, 2019 IEEE Energy Conversion Congress and Exposition (ECCE))

   High performance computing needs high performance power electronics. This paper presents the design of an ultra-efficient series-stacked hard-disk-drive (HDD) data storage server with a multiport ac-coupled differential power processing (MAC-DPP) architecture. A large number of HDDs are connected in series and ac-coupled through a multi-winding transformer with a single flux linkage. The MAC-DPP architecture offers very low power conversion stress, can achieve extremely high efficiency, and can reduce the magnetic size and the component count. A hybrid time-sharing and distributed phase-shift control strategy is developed to modulate the ac-coupled multi-input-multi-output (MIMO) power flow. A 10-port MAC-DPP prototype was designed to support a 300 W data storage system with 10 series-stacked voltage domains. The MAC-DPP converter was tested with a 50-HDD 12TB testbench, which can maintain normal operation of the server against the worst hot-swapping scenario. The 300 W MAC-DPP prototype can achieve 99.7% peak system efficiency and over 100 W/in 3 power density. 

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