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Voltage Quality Enhancement of Grid-Integrated PV System Using Battery-Based Dynamic Voltage Restorer

Author

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  • Emiyamrew Minaye Molla

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, 43, Sec. 4, Keelung Rd., Da’an District, Taipei City 10607, Taiwan)

  • Cheng-Chien Kuo

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, 43, Sec. 4, Keelung Rd., Da’an District, Taipei City 10607, Taiwan)

Abstract

The advancement of power electronic-based sensitive loads drives the power utilities’ devotion to power quality issues. The voltage disturbance could be happening due to fault conditions, switching of loads, energizing of transformers, or integration of highly intermittent energy sources such as PV systems. This research work attempts to enhance the voltage fluctuation of a sensitive load connected to a grid-integrated PV system using a battery-based dynamic voltage restorer (DVR). The proposed battery energy storage-based DVR has two separate controlling stages that are implemented at the DC–DC buck/boost converter of the battery and voltage source converter (VSC) system. Charging and discharging of the battery is operated based on the state-of-charge (SOC) value of the battery and the measured root mean square (RMS) voltage at the point of common coupling (PCC). The VSC of the DVR detection and reference generation control is done appropriately. In the detection control of the VSC, a combination of RMS and dq0 measurement techniques is used, whereas in the reference generation control, pre-fault strategy is implemented to restore both phase jump and magnitude distortions. Symmetrical and asymmetrical voltage sags scenarios are considered and the compensation demonstration is carried out using power system computer-aided design (PSCAD/EMTDC) software.

Suggested Citation

  • Emiyamrew Minaye Molla & Cheng-Chien Kuo, 2020. "Voltage Quality Enhancement of Grid-Integrated PV System Using Battery-Based Dynamic Voltage Restorer," Energies, MDPI, vol. 13(21), pages 1-16, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:21:p:5742-:d:439001
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    References listed on IDEAS

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    1. Saïd-Romdhane, M. Ben & Naouar, M.W. & Belkhodja, I. Slama. & Monmasson, E., 2016. "Simple and systematic LCL filter design for three-phase grid-connected power converters," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 130(C), pages 181-193.
    2. Abdelbasset Krama & Laid Zellouma & Boualaga Rabhi & Shady S. Refaat & Mansour Bouzidi, 2018. "Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm," Energies, MDPI, vol. 11(12), pages 1-26, December.
    3. K. Muthuvel & M. Vijayakumar, 2020. "Solar PV Sustained Quasi Z-Source Network-Based Unified Power Quality Conditioner for Enhancement of Power Quality," Energies, MDPI, vol. 13(10), pages 1-26, May.
    4. Agalar, Sener & Kaplan, Yusuf Alper, 2018. "Power quality improvement using STS and DVR in wind energy system," Renewable Energy, Elsevier, vol. 118(C), pages 1031-1040.
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    Cited by:

    1. M. Osama abed el-Raouf & Soad A. A. Mageed & M. M. Salama & Mohamed I. Mosaad & H. A. AbdelHadi, 2023. "Performance Enhancement of Grid-Connected Renewable Energy Systems Using UPFC," Energies, MDPI, vol. 16(11), pages 1-22, May.
    2. Zhenyu Li & Ranchen Yang & Xiao Guo & Ziming Wang & Guozhu Chen, 2022. "A Novel Voltage Sag Detection Method Based on a Selective Harmonic Extraction Algorithm for Nonideal Grid Conditions," Energies, MDPI, vol. 15(15), pages 1-21, July.
    3. Uthra R. & Suchitra D., 2021. "Fault Ride Through in Grid Integrated Hybrid System Using FACTS Device and Electric Vehicle Charging Station," Energies, MDPI, vol. 14(13), pages 1-21, June.
    4. Shen, Boyang & Chen, Yu & Li, Chuanyue & Wang, Sheng & Chen, Xiaoyuan, 2021. "Superconducting fault current limiter (SFCL): Experiment and the simulation from finite-element method (FEM) to power/energy system software," Energy, Elsevier, vol. 234(C).
    5. Cheng-I Chen & Yeong-Chin Chen & Chung-Hsien Chen & Yung-Ruei Chang, 2020. "Voltage Regulation Using Recurrent Wavelet Fuzzy Neural Network-Based Dynamic Voltage Restorer," Energies, MDPI, vol. 13(23), pages 1-19, November.

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