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Review on distribution system state estimation considering renewable energy sources

Review on distribution system state estimation considering renewable energy sources
Review on distribution system state estimation considering renewable energy sources
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.
distribution system state estimation, renewable energy resource, review
1996-1073
Qing, Hanshan
3e2f5e64-d095-495b-8c68-236d53f9c3ac
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Batzelis, Efstratios
2a85086e-e403-443c-81a6-e3b4ee16ae5e
Qing, Hanshan
3e2f5e64-d095-495b-8c68-236d53f9c3ac
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Batzelis, Efstratios
2a85086e-e403-443c-81a6-e3b4ee16ae5e

Qing, Hanshan, Singh, Abhinav Kumar and Batzelis, Efstratios (2025) Review on distribution system state estimation considering renewable energy sources. Energies, 18 (10), [2524]. (doi:10.3390/en18102524).

Record type: Article

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.

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Accepted/In Press date: 11 May 2025
Published date: 13 May 2025
Keywords: distribution system state estimation, renewable energy resource, review

Identifiers

Local EPrints ID: 502214
URI: http://eprints.soton.ac.uk/id/eprint/502214
ISSN: 1996-1073
PURE UUID: 5682ed8c-e126-4918-84d3-f8998123a75e
ORCID for Abhinav Kumar Singh: ORCID iD orcid.org/0000-0003-3376-6435
ORCID for Efstratios Batzelis: ORCID iD orcid.org/0000-0002-2967-3677

Catalogue record

Date deposited: 18 Jun 2025 16:38
Last modified: 04 Sep 2025 02:31

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Contributors

Author: Hanshan Qing
Author: Abhinav Kumar Singh ORCID iD
Author: Efstratios Batzelis ORCID iD

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