Optimization and Visualization Tools for Situational Awareness in Highly Renewable Power Systems
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|Title:||Optimization and Visualization Tools for Situational Awareness in Highly Renewable Power Systems||Authors:||Cuffe, Paul||Permanent link:||http://hdl.handle.net/10197/11725||Date:||1-Oct-2020||Online since:||2020-11-24T16:39:56Z||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.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||IEEE||Copyright (published version):||2020 IEEE||Keywords:||Power systems; Renewable energy sources; Branch loading envelopes; Network visualisations||DOI:||10.1109/energycon48941.2020.9236524||Other versions:||https://web.cvent.com/event/5569bdf7-1e9a-43c8-9f19-d068c2ef2267||Language:||en||Status of Item:||Peer reviewed||Is part of:||2020 6th IEEE International Energy Conference (ENERGYCon)||Conference Details:||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/|
|Appears in Collections:||Electrical and Electronic Engineering Research Collection|
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