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  5. Local and Remote Estimations Using Fitted Polynomials on Distribution Systems
 
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Local and Remote Estimations Using Fitted Polynomials on Distribution Systems

Author(s)
Murphy, Conor  
Keane, Andrew  
Uri
http://hdl.handle.net/10197/8153
Date Issued
2016-11-18
Date Available
2016-11-28T14:45:02Z
Abstract
This work describes a technique to define a single parametric equation that estimates remote conditions within a distribution network, in an online setting, without dedicated telemetry. In this novel approach, a departure from conventional state estimation is explored to facilitate a fully decentralized operation. Derived based on fundamental treatment of ac power flow, the electrical behavior of a section of network is defined to a tractable constraint space using regression analysis. In this non-iterative technique, a measurement set consisting of the local voltage magnitude, active and reactive power injections at a single node are the input to pre-computed polynomials. Remote current flow, active power and reactive power flow as well as remote and local voltages and sensitivities are estimated in a direct calculation from period to period. Accurate estimations are also found in the presence of transducer errors. To assess the applicability of this technique at differing voltage levels a range of reactance to resistance ratios are considered.
Sponsorship
Science Foundation Ireland
Type of Material
Journal Article
Publisher
IEEE
Journal
IEEE Transactions on Power Systems
Volume
32
Issue
4
Copyright (Published Version)
2016 IEEE
Subjects

Distributed estimatio...

Energy resources

Multivariable functio...

Power distribution

Voltage measurement

DOI
10.1109/TPWRS.2016.2630743
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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Local and Remote Estimations using Fitted Polynomials in Distribution Systems_ucd_repository.pdf

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Checksum (MD5)

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Owning collection
Electrical and Electronic Engineering Research Collection
Mapped collections
Energy Institute Research Collection•
ERC Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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