Load profiling using grey relational analysis for power system state estimation
Load profiling using grey relational analysis for power system state estimation
Power system state estimation (PSSE) is a critical tool for power system operation. Load/generation profiles are essential for performing accurate PSSE, and enable PSSE algorithms to handle errors in real and pseudo measurements. The classic approach of modelling the measurement error in PSSE is applying the mixture reduction algorithm to Gaussian mixture models (GMMs) fitted to existent load/generation profiles. However, this approach has inherent limitations in the mixing process. We propose a novel algorithm based on grey relational analysis (GRA) to derive a smaller load/generation profile from the original extensive profiles based on the forecast results of the next day. Our algorithm addresses the issues of mixture reduction and is applied before mixture reduction to improve PSSE accuracy. A case study is presented to evaluate the performance of the proposed algorithm in improving the accuracy of PSSE.
Power system state estimation, grey relational analysis, load/generation profiling
Qing, Hanshan
3e2f5e64-d095-495b-8c68-236d53f9c3ac
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Batzelis, Efstratios
2a85086e-e403-443c-81a6-e3b4ee16ae5e
October 2024
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
(2024)
Load profiling using grey relational analysis for power system state estimation.
IEEE PES ISGT Europe 2024 (ISGT Europe 2024), , Srebreno, Croatia.
14 - 17 Oct 2024.
5 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Power system state estimation (PSSE) is a critical tool for power system operation. Load/generation profiles are essential for performing accurate PSSE, and enable PSSE algorithms to handle errors in real and pseudo measurements. The classic approach of modelling the measurement error in PSSE is applying the mixture reduction algorithm to Gaussian mixture models (GMMs) fitted to existent load/generation profiles. However, this approach has inherent limitations in the mixing process. We propose a novel algorithm based on grey relational analysis (GRA) to derive a smaller load/generation profile from the original extensive profiles based on the forecast results of the next day. Our algorithm addresses the issues of mixture reduction and is applied before mixture reduction to improve PSSE accuracy. A case study is presented to evaluate the performance of the proposed algorithm in improving the accuracy of PSSE.
Text
Load_Profiling_using_Grey_Relational_Analysis_for_Power_System_State_Estimation
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Accepted/In Press date: 17 July 2024
Published date: October 2024
Venue - Dates:
IEEE PES ISGT Europe 2024 (ISGT Europe 2024), , Srebreno, Croatia, 2024-10-14 - 2024-10-17
Keywords:
Power system state estimation, grey relational analysis, load/generation profiling
Identifiers
Local EPrints ID: 494807
URI: http://eprints.soton.ac.uk/id/eprint/494807
PURE UUID: c40364cb-e61e-4871-b65b-bfb04fcd13f8
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Date deposited: 15 Oct 2024 17:04
Last modified: 16 Oct 2024 02:05
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Contributors
Author:
Hanshan Qing
Author:
Abhinav Kumar Singh
Author:
Efstratios Batzelis
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