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Congestion management optimization in electric transmission system

Citation

Semshchikov, E and Negnevitsky, M, Congestion management optimization in electric transmission system, Proceedings of The Australasian Universities Power Engineering Conference (AUPEC 2018), 27-30 November 2018, Auckland, New Zeeland, pp. 1-5. (2018) [Refereed Conference Paper]


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Copyright Statement

Copyright 2018 IEEE

Official URL: http://dx.doi.org/10.1109/AUPEC.2018.8757932

Abstract

Congestion management in electric transmission systems is one of the most important challenges for power systems with high penetration of renewable energy. System congestion occurs when the desired power flow cannot be transmitted through the network without violating system operating limits. In order to prevent severe system damage, a significant number of congestion management methods have been developed, including nodal pricing, load shedding, curtailment of renewable energy generation, generator rescheduling, optimal transmission switching, etc. Most of these methods, however, do not comply with the optimal operation of conventional power plants subjected to dynamic constraints (manoeuvrability, start-up and shut down times, etc.). In this paper, the rescheduling generation (or re-dispatch optimization) problem is solved using a modified particle swarm optimization (PSO) algorithm which accounts for start up as well as shut down times, and the manoeuvrability of conventional power plants.

Item Details

Item Type:Refereed Conference Paper
Keywords:Congestion management, Particle swarm optimization, Transmission system
Research Division:Engineering
Research Group:Electrical and Electronic Engineering
Research Field:Renewable Power and Energy Systems Engineering (excl. Solar Cells)
Objective Division:Energy
Objective Group:Renewable Energy
Objective Field:Renewable Energy not elsewhere classified
UTAS Author:Semshchikov, E (Mr Evgenii Semshchikov)
UTAS Author:Negnevitsky, M (Professor Michael Negnevitsky)
ID Code:130791
Year Published:2018
Deposited By:Engineering
Deposited On:2019-02-12
Last Modified:2019-10-23
Downloads:1 View Download Statistics

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