Machine Learning and Power System Planning: Opportunities and Challenges

Mohammad Hosein Asgharinejad Keisami, Sasan Azad, Reza Mohammadi Chabanloo, Morteza Nazari-Heris, Somayeh Asadi

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

Machine learning (ML) methods and their applications are among the most innovative and attractive engineering topics. The advent of artificial intelligence has given birth to various tools widely used in science and engineering. ML is utilized in solving various problems in the power system engineering community, such as power system planning and operation. In this chapter, the authors will investigate different machine learning methods, and we will discuss their applications in solving power system planning problems, including load forecasting. The authors will discuss different ML methods used in the power engineering field, and other ML applications in planning problems such as optimization problems will be studied. This chapter’s main objective is to serve as an introduction to ML for power system planning and the basic concepts of the ML methods commonly used in this field.

Original languageEnglish (US)
Title of host publicationPower Systems
PublisherSpringer Science and Business Media Deutschland GmbH
Pages45-59
Number of pages15
DOIs
StatePublished - 2021

Publication series

NamePower Systems
ISSN (Print)1612-1287
ISSN (Electronic)1860-4676

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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