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Soft-Computing Techniques for Voltage Regulation of Grid-Tied Novel PV Inverter at Different Case Scenarios

  • T. Lova LakshmiEmail author
  • M. Gopichand Naik
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 898)

Abstract

In this paper, the voltage regulation of large-scale grid-tied photovoltaic power plant (GTPVPP) operating during nonlinear PV generation has been discussed. This research proposes the comparative voltage regulation of a novel multilevel inverter with soft-computing techniques such as fuzzy and adaptive neuro-fuzzy inference system (ANFIS)-based control for regulating the voltage of GTPVPP. Due to the interruptible PV generation and at worst-case scenarios, the proposed control scheme is useful to satisfy the load demand by grid integration. In this comparison, the ANFIS-based control scheme improves the dynamic performance, reduces the THD, and improves the efficiency. The fuzzy and proposed ANFIS-based control schemes are developed in MATLAB/Simulink environment and are compared at worst-case solar generation, rapid change of loads, and grid faults.

Keywords

Solar PV generation DC–DC converter Resonant switched-capacitor converter (RSCC) Multilevel inverter Soft-computing techniques 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Andhra UniversityVisakhapatnamIndia

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