Voltage Regulation in an Islanded Microgrid using a GA-based Optimization Technique

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2022 by IJETT Journal
Volume-70 Issue-4
Year of Publication : 2022
Authors : H R Sridevi, Shreeram V Kulkarni, H M Ravikumar
  10.14445/22315381/IJETT-V70I4P202

MLA 

MLA Style: H R Sridevi, et al. "Voltage Regulation in an Islanded Microgrid using a GA-based Optimization Technique." International Journal of Engineering Trends and Technology, vol. 70, no. 4, Apr. 2022, pp. 15-20. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I4P202

APA Style: H R Sridevi, Shreeram V Kulkarni, H M Ravikumar. (2022). Voltage Regulation in an Islanded Microgrid using a GA-based Optimization Technique. International Journal of Engineering Trends and Technology, 70(4), 15-20. https://doi.org/10.14445/22315381/IJETT-V70I4P202

Abstract
The power industry is undergoing significant changes due to apprehensions about traditional energy prices and greenhouse emissions due to the use of fossil fuels. As a solution, numbers of Distributed Energy Resources (DERs) are connected to the grid. Accumulation loads and DERs constitute a microgrid as a small-scale grid compared to a conventional grid. In a conventional grid, regulation of voltage and frequency are controlled by the speed variation of alternators interconnected to the grid. As the usage of DERs in power networks grows, additional challenges emerge, like the frequency and voltage regulation problems. However, the voltage and frequency must be regulated independently of the main grid if the microgrid is detached from the main utility grid. In this paper, the deviation in voltage is regulated by utilizing a Genetic algorithm (GA) to optimize the droop coefficients. The work is carried out for various loads to regulate voltage variation and reactive power-sharing, and the responses are presented. The results for voltage deviations with and without GA optimizations are also presented.

Keywords
Distributed energy sources, Autonomous microgrid, Genetic algorithm, Voltage control, Reactive power-sharing.

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