Dynamic Voltage Restorer Controlled with Energy Minimized Compensation Method Based on Double Flying Capacitor Multicell Inverter

Arash Khoshkbar-Sadigh, Saleh Farzamkia, Vahid Dargahi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Nowadays, integration of intermittent and distributed renewable energy generations into power grid causes to have power quality problems as concern. These problems are usually causing very costly consequences such as production line and/or sensitive load interruption. Hence, it is crucial to have stable voltage with good quality. One of the most effective power-electronics-based approach to alleviate the mentioned problems is dynamic voltage restorer (DVR). DVR is capable to restore the voltage at load side whenever grid voltage is disturbed. This paper presents a DVR structure for medium-voltage power grid based on double flying capacitor multicell inverter. In the proposed DVR circuit, an energy storage connected to the dc link of the inverter provides the needed active power to restore the voltage quality. In order to minimize the required energy from energy storage, the energy optimized strategy is implemented to compensate the voltage sag. Furthermore, d-q synchronous reference frame-based method is implemented to calculate the DVR reference voltages. To validate the operation of the presented DVR circuit, simulation results are provided for different cases.

Original languageEnglish (US)
Title of host publicationClemson University Power Systems Conference, PSC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728193847
DOIs
StatePublished - Mar 2020
Event2020 Clemson University Power Systems Conference, PSC 2020 - Clemson, United States
Duration: Mar 10 2020Mar 13 2020

Publication series

NameClemson University Power Systems Conference, PSC 2020

Conference

Conference2020 Clemson University Power Systems Conference, PSC 2020
CountryUnited States
CityClemson
Period3/10/203/13/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Information Systems and Management
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization

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