Smart and Sustainable Grids Using Data-Driven Methods; Considering Artificial Neural Networks and Decision Trees

EasyChair Preprint no. 8401

Abstract

Sustainability is the essential part of smart grids and the ultimate future of energy systems. Providing a state-of-the-art review on the progress of advanced learning systems which contribute to the sustainability of smart grid is essential. This paper reviews the applications of data-driven methods of machine learning in sustainable smart grid systems. The machine learning methods had been classified and reviewed in various groups based on the proposed taxonomy. The applications and methods had been identified and systematically reviewed based on the PRISMA guideline.

Keyphrases: Machine Learning Algorithms, Smart Grid, Sustainability

@Booklet{EasyChair:8401,
  author = {Rituraj Rituraj and Diana Ecker and Varkonyi Koczy Annamaria},
  title = {Smart and Sustainable Grids Using Data-Driven  Methods; Considering Artificial Neural Networks  and Decision Trees},
  howpublished = {EasyChair Preprint no. 8401},

  year = {EasyChair, 2022}}