Review on Distribution System State Estimation Considering Renewable Energy Sources

Hanshan Qing, Abhinav Kumar Singh () and Efstratios Batzelis
Additional contact information
Hanshan Qing: Faculty of Engineering and Physical Sciences, School of Electronics and Computer Science, University of Southampton, Highfiled Campus, Southampton SO17 1BJ, UK
Abhinav Kumar Singh: Faculty of Engineering and Physical Sciences, School of Electronics and Computer Science, University of Southampton, Highfiled Campus, Southampton SO17 1BJ, UK
Efstratios Batzelis: Faculty of Engineering and Physical Sciences, School of Electronics and Computer Science, University of Southampton, Highfiled Campus, Southampton SO17 1BJ, UK

Energies, 2025, vol. 18, issue 10, 1-20

Abstract: Power system state estimation (PSSE) is critical for accurately monitoring and managing electrical networks, especially with the increasing integration of renewable energy sources (RESs). This review aims to explicitly evaluate and compare state estimation techniques specifically adapted to handle RES-related uncertainties, providing both theoretical insights and clear practical guidance. It categorizes and analytically compares physical-model-based, forecasting-aided, and neural network-based approaches, summarizing their strengths, limitations, and ideal application scenarios. The paper concludes with recommendations for method selection under different practical conditions, highlighting opportunities for future research.

Keywords: review; distribution system state estimation; renewable energy resource (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: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/10/2524/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/10/2524/ (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:18:y:2025:i:10:p:2524-:d:1655117

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 ().