EconPapers    
Economics at your fingertips  
 

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 and Yasuhiro Hayashi
Additional contact information
Yu Fujimoto: Advanced Collaborative Research Organization for Smart Society, Waseda University, Tokyo 169-8555, Japan
Akihisa Kaneko: Graduate School of Advanced Science and Engineering, Waseda University, Tokyo 169-8555, Japan
Yutaka Iino: Advanced Collaborative Research Organization for Smart Society, Waseda University, Tokyo 169-8555, Japan
Hideo Ishii: Advanced Collaborative Research Organization for Smart Society, Waseda University, Tokyo 169-8555, Japan
Yasuhiro Hayashi: Graduate School of Advanced Science and Engineering, Waseda University, Tokyo 169-8555, Japan

Energies, 2023, vol. 16, issue 3, 1-26

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.

Keywords: smart inverters; distributed energy resources; machine/deep learning; power grid operation; coordination; net zero (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/3/1330/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/3/1330/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:3:p:1330-:d:1047929

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1330-:d:1047929