Response-based Control through Dynamic Optimization in Large-scale Power Systems

Sergio Bruno, Matteo D'Aloia, Massimo La Scala

2013

Abstract

Modern real-time measurement equipments and associated communication/computing networks allow developing advanced power system control architectures able to identify dangerous states of power systems, and, when necessary, evaluate and apply remedial control actions. An approach, derived by a dynamic optimization methodology, for evaluating response-based control actions and enhance power system security, is presented. In this paper, studies performed for wide-area control of transient phenomena are reviewed. Despite severe computational efforts and time requirements, the authors’ position is that the nowadays technology can make the approach feasible.

References

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Paper Citation


in Harvard Style

Bruno S., D'Aloia M. and La Scala M. (2013). Response-based Control through Dynamic Optimization in Large-scale Power Systems . In Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-8565-69-3, pages 210-216. DOI: 10.5220/0004593202100216


in Bibtex Style

@conference{simultech13,
author={Sergio Bruno and Matteo D'Aloia and Massimo La Scala},
title={Response-based Control through Dynamic Optimization in Large-scale Power Systems},
booktitle={Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2013},
pages={210-216},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004593202100216},
isbn={978-989-8565-69-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Response-based Control through Dynamic Optimization in Large-scale Power Systems
SN - 978-989-8565-69-3
AU - Bruno S.
AU - D'Aloia M.
AU - La Scala M.
PY - 2013
SP - 210
EP - 216
DO - 10.5220/0004593202100216