Challenges in Smartizing Operational Management of Functionally-Smart Inverters for Distributed Energy Resources: A Review on Machine Learning Aspects

Yu Fujimoto*, Akihisa Kaneko, Yutaka Iino, Hideo Ishii, Yasuhiro Hayashi

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)

Abstract

The widespread introduction of functionally-smart inverters will be an indispensable factor for the large-scale penetration of distributed energy resources (DERs) via the power system. On the other hand, further smartization based on the data-centric operation of smart inverters (S-INVs) is required to cost-effectively achieve the same level of power system operational performance as before under circumstances where the spatio-temporal behavior of power flow is becoming significantly complex due to the penetration of DERs. This review provides an overview of current ambitious efforts toward smartization of operational management of DER inverters, clarifies the expected contribution of machine learning technology to the smart operation of DER inverters, and attempts to identify the issues currently open and areas where research is expected to be promoted in the future.

Original languageEnglish
Article number1330
JournalEnergies
Volume16
Issue number3
DOIs
Publication statusPublished - 2023 Feb

Keywords

  • coordination
  • distributed energy resources
  • machine/deep learning
  • net zero
  • power grid operation
  • smart inverters

ASJC Scopus subject areas

  • Control and Optimization
  • Energy (miscellaneous)
  • Engineering (miscellaneous)
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Fuel Technology
  • Renewable Energy, Sustainability and the Environment

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