STATCOM Interface for Renewable Energy Sources with Power Quality Improvement

Ilango, K.; Bhargav, Allu; Trivikram, A.; Kavya, P.S.; Mounika, G.; Vivek, N.; Nair, Manjula G.

doi:10.1016/j.aasri.2012.09.016

Cited by 6 publications

(1 citation statement)

References 7 publications

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“…The authors have verified the proposed model on the IEEE 33‐bus distribution system under a voltage sag condition. The authors 23 implemented a power electronic‐based grid interfacing inverter to meet the IEEE 1547 standards for power quality improvement. The researchers developed a digital controller based on the “Icosϕ” algorithm to set up the grid interface and CPDs.…”

Section: Introductionmentioning

confidence: 99%

Gray wolf optimization‐based optimal grid connected solar photovoltaic system with enhanced power quality features

Nagadurga

Narasimham

Vakula

et al. 2021

Concurrency and Computation

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In recent times, regional renewable energy sources (RES) are increasingly integrated with the existing electric power grid by onboarding certain superior power quality features, thereby helping them in meeting massive electrical demand. This grid integration drastically reduces the use of fossil fuels, besides preventing environmental hazards as well. However, in grid‐connected systems, with RES such as photovoltaic (PV) systems and wind energy systems, many power quality issues (PQ) still crop up. In this paper, Gray Wolf Optimization (GWO), in conjunction with a static synchronous compensator (STATCOM) is suggested to address such challenges in the RES integrated grid‐connected PV systems. The intermittent nature of solar PV power under shading conditions can be harnessed by using the GWO approach. STATCOM is one of many specialized power electronic devices that effectively reduce power quality concerns such as voltage sag/swell and Total Harmonic Distortions. The fast‐acting PI controller is intended to drive a STATCOM by using some tuned parameters for maintaining the DC link voltage as constant. The best findings are attained after these results are compared with PI. The test system is modeled using the MATLAB/Simulink environment.

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Section: Introductionmentioning

confidence: 99%