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Neuro-Fuzzy Control Algorithm for Harmonic Compensation of Quality Improvement for Grid Interconnected Photovoltaic System

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1045))

Abstract

Current quality compensation is the major task in solar photovoltaic system. Several control algorithms have been discussed in the literature survey for reducing the power quality compensation. In the proposed system, neuro-fuzzy algorithm is implemented for reactive power compensation. The incremental conductances technique is used for extracting maximum power from the PV system by adjusting the duty cycle of the IGBT. The DC-DC boost converter is used for increasing the extracted power from PV system. The DC bus capacitor is used for maintaining constant PV voltage in the system. The voltage source converter is used for DC to AC conversion. The IGBT section of the VSC is controlled by the neuro-fuzzy controller. The neural network control algorithm is used for extracting reference currents for ZVR operation.

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Correspondence to B. Pragathi .

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Pragathi, B., Nayak, D.K., Poonia, R.C. (2020). Neuro-Fuzzy Control Algorithm for Harmonic Compensation of Quality Improvement for Grid Interconnected Photovoltaic System. In: Luhach, A., Kosa, J., Poonia, R., Gao, XZ., Singh, D. (eds) First International Conference on Sustainable Technologies for Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1045. Springer, Singapore. https://doi.org/10.1007/978-981-15-0029-9_49

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