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  5. Optimization and Visualization Tools for Situational Awareness in Highly Renewable Power Systems
 
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Optimization and Visualization Tools for Situational Awareness in Highly Renewable Power Systems

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Author(s)
Cuffe, Paul 
Uri
http://hdl.handle.net/10197/11725
Date Issued
01 October 2020
Date Available
24T16:39:56Z November 2020
Abstract
This paper proposes new tools for predicting and visualising the plausible near term shifts in branch loading that may arise due to output fluctuations from renewable generators. These tools are proposed to enhance situational awareness for control room operators, by providing early warnings of where bottlenecks may manifest in a transmission system. For predicting plausible branch loading shifts, a linear optimal power flow formulation is presented which uses a novel objective function to characterise the maximum loading a branch could be exposed to in the short term. This analysis therefore identifies which branches could become overloaded due to shifts in output from volatile generators. Equivalently, these branches can be seen as congestion bottlenecks which may cause curtailment of renewable generation. To allow the system operator to maintain awareness of such potentialities, these congestable branches are highlighted on a system diagram which is drawn to explicitly portray the electrical distance between components in the network.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2020 IEEE
Keywords
  • Power systems

  • Renewable energy sour...

  • Branch loading envelo...

  • Network visualisation...

DOI
10.1109/energycon48941.2020.9236524
Web versions
https://web.cvent.com/event/5569bdf7-1e9a-43c8-9f19-d068c2ef2267
Language
English
Status of Item
Peer reviewed
Part of
2020 6th IEEE International Energy Conference (ENERGYCon)
Description
The 6th IEEE International Energy Conference (EnergyCon 2020), Gammarth, Tunisia (held online due to coronavirus outbreak), 28 September - 1 October 2020
ISBN
978-1-7281-2956-3
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Electrical and Electronic Engineering Research Collection
Scopus© citations
1
Acquisition Date
Feb 4, 2023
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