Dual Fuzzy-Sugeno Controlled Grid-Forming Voltage-Source Inverter for Hybrid Wind-Solar Systems in Weak Grid Integration

In this paper, a new Dual Fuzzy-Sugeno based control technique is introduced to a Grid-Forming Voltage-Source Inverter (VSI) connecting the hybrid wind-solar energy systems to weak grids. The suggested method increases the stability of voltage and power quality and efficiency of energy transfer under weak grid conditions. The system is more reliable since it provides continual energy because of the interested sources of wind and solar energy and the Dual Fuzzy Sugeno controller enhances the dynamic behavior and robustness. In control scheme, two Fuzzy-Sugeno controllers are utilized, which are a voltage control and an active-reactive balance control with different grid conditions. This two controller strategy will improve the flexibility with changes in wind speed, solar irradiance and grid voltage, giving optimum grid support. The simulations carried out through MATLAB/Simulink assure that the given controller can effectively normalize the voltage and frequency deviation and seriously decrease Total Harmonic Distortion (THD) in grid voltage and current. Based on performance comparisons, it is observed that the performance closely outperforms the existing systems and THD values were minimized by 5.34 to 3.56 in grid current, 6.00 to 3.33 in grid voltage, 5.52 to 3.19 in load voltage, and 5.65 to 2.88 in load current. All these results underline the effectiveness of the suggested system in increasing grid stability and reliability when dealing with hybrid renewable energy images onto weak grids.

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Published
2025-06-27
DOI
https://doi.org/10.1109/apci65531.2025.11137215
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Dual Fuzzy-Sugeno Controlled Grid-Forming Voltage-Source Inverter for Hybrid Wind-Solar Systems in Weak Grid Integration

T. Penchalaiah, Therala Krishna Chaithanya, M.E. Harikumar, A Harshitha. et al.
Microgrid Control and Optimization
article

Dual Fuzzy-Sugeno Controlled Grid-Forming Voltage-Source Inverter for Hybrid Wind-Solar Systems in Weak Grid Integration

T. Penchalaiah, Therala Krishna Chaithanya, M.E. Harikumar, A Harshitha., N Arunsai.
article en

Abstract

In this paper, a new Dual Fuzzy-Sugeno based control technique is introduced to a Grid-Forming Voltage-Source Inverter (VSI) connecting the hybrid wind-solar energy systems to weak grids. The suggested method increases the stability of voltage and power quality and efficiency of energy transfer under weak grid conditions. The system is more reliable since it provides continual energy because of the interested sources of wind and solar energy and the Dual Fuzzy Sugeno controller enhances the dynamic behavior and robustness. In control scheme, two Fuzzy-Sugeno controllers are utilized, which are a voltage control and an active-reactive balance control with different grid conditions. This two controller strategy will improve the flexibility with changes in wind speed, solar irradiance and grid voltage, giving optimum grid support. The simulations carried out through MATLAB/Simulink assure that the given controller can effectively normalize the voltage and frequency deviation and seriously decrease Total Harmonic Distortion (THD) in grid voltage and current. Based on performance comparisons, it is observed that the performance closely outperforms the existing systems and THD values were minimized by 5.34 to 3.56 in grid current, 6.00 to 3.33 in grid voltage, 5.52 to 3.19 in load voltage, and 5.65 to 2.88 in load current. All these results underline the effectiveness of the suggested system in increasing grid stability and reliability when dealing with hybrid renewable energy images onto weak grids.

Annamalai University (IN), Anna University, Chennai (IN)
Openalex Percentile: Top 71%
Microgrid Control and Optimization
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Dual Fuzzy-Sugeno Controlled Grid-Forming Voltage-Source Inverter for Hybrid Wind-Solar Systems in Weak Grid Integration — T. Penchalaiah, Therala Krishna Chaithanya, et al. · (2025) | TGRS Research Map | TGRS