Imperial College London
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ProfessorBikashPal

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Power Systems
 
 
 
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Contact

 

+44 (0)20 7594 6172b.pal Website CV

 
 
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Assistant

 

Miss Guler Eroglu +44 (0)20 7594 6170

 
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Location

 

1104Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Nogueira:2019:10.1049/iet-gtd.2018.5284,
author = {Nogueira, EM and Portelinha, RK and Lourenco, EM and Tortelli, OL and Pal, BC},
doi = {10.1049/iet-gtd.2018.5284},
journal = {IET Generation, Transmission and Distribution},
pages = {1970--1978},
title = {Novel approach to power system state estimation for transmission and distribution systems},
url = {http://dx.doi.org/10.1049/iet-gtd.2018.5284},
volume = {13},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This article proposes a power system state estimation (PSSE) capable of dealing with distribution and transmission networks. The proposed approach combines decoupled techniques, complex per unit (cpu) system, and a switching branch representation to meet the increasing complexity of state estimation issue when associated with the emerging electrical systems. The result is an efficient tool that can easily deal with distributed generation, closed loop, or meshed operation and manoeuvres in distribution systems (DS) keeping the efficiency and ability of the fast decoupled estimator to process transmission systems (TS). Results obtained with several simulations carried out on two distribution test systems, a 136-node Brazilian feeder and a 907-node European feeder, and on the IEEE 14-bus TS, demonstrate the effectiveness of the proposed methodology.
AU  - Nogueira,EM
AU  - Portelinha,RK
AU  - Lourenco,EM
AU  - Tortelli,OL
AU  - Pal,BC
DO  - 10.1049/iet-gtd.2018.5284
EP  - 1978
PY  - 2019///
SN  - 1350-2360
SP  - 1970
TI  - Novel approach to power system state estimation for transmission and distribution systems
T2  - IET Generation, Transmission and Distribution
UR  - http://dx.doi.org/10.1049/iet-gtd.2018.5284
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000471025300024&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2018.5284
UR  - http://hdl.handle.net/10044/1/82036
VL  - 13
ER  -
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