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Fuzzy Control for Smart PV-Battery System Management to Stabilize Grid Voltage of 22 kV Distribution System in Thailand

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  • Kongrit Mansiri

    (School of Renewable Energy Technology, Naresuan University, Phitsanulok 65000, Thailand)

  • Sukruedee Sukchai

    (School of Renewable Energy Technology, Naresuan University, Phitsanulok 65000, Thailand)

  • Chatchai Sirisamphanwong

    (School of Renewable Energy Technology, Naresuan University, Phitsanulok 65000, Thailand)

Abstract

This paper presents a fuzzy logic based algorithm developed to bring smart functionality to an ordinary PV-battery system in order to maintain the grid voltage stability of the 22 kV distribution system in Thailand. This research focuses on minimizing grid voltage fluctuations by converting a typical PV system into a smart PV-battery system (SPVs-BSS). A SPVs-BSS will be able to control the electrical power from a PV system to maintain the grid voltage in case of unexpected events or emergencies. Grid support functions such as a variable reactive power control and active power control will be discussed, leading to strategies for charging and discharging the battery system in response to the status of grid voltage. Fuzzy Logic was used to develop this control algorithm, which is named the Voltage Stability Fuzzy Logic Algorithm (VSFL Algorithm). The methodology of this research consists of three parts. First, testing the grid inverter operated on grid support functions. Second, the VSFL algorithm was developed to manage both the grid inverter and the battery system. Third, a SPVs-BSS equipped with the VSFL algorithm was simulated by using DIgsilent PowerFactory software. Results showed that the SPVs-BSS equipped with the VSFL Algorithm successfully maintained grid voltage in target range.

Suggested Citation

  • Kongrit Mansiri & Sukruedee Sukchai & Chatchai Sirisamphanwong, 2018. "Fuzzy Control for Smart PV-Battery System Management to Stabilize Grid Voltage of 22 kV Distribution System in Thailand," Energies, MDPI, vol. 11(7), pages 1-19, July.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1730-:d:155714
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    2. Jun Deng & Jun Suo & Jing Yang & Shutao Peng & Fangde Chi & Tong Wang, 2019. "Adaptive Damping Control Strategy of Wind Integrated Power System," Energies, MDPI, vol. 12(1), pages 1-18, January.

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