Neural Multi-agent-based Approach for Preventing Blackouts in Power Systems

Michael Negnevitsky, Nikita Tomin, Daniil Panasetsky, Ulf Haeger, Nikolay Voropai, Christian Rehtanz, Victor Kurbatsky

2014

Abstract

A neural multi-agent-based approach for system monitoring and preventing large-scale emergencies in power systems is presented in this paper. The automatic emergency control process is represented as a neural multi-agent system with hierarchical architecture. The proposed system consist of two main parts: the alarm trigger, a Kohonen neural network-based system for early detection of possible alarm states in a power system, and the competitive–collaborative multi-agent control system. For demonstration purposes, we investigated conventional and neural multi-agent automatic control schemes. Results are presented and discussed.

Paper Citation

in Harvard Style

Negnevitsky M., Tomin N., Panasetsky D., Haeger U., Voropai N., Rehtanz C. and Kurbatsky V. (2014). Neural Multi-agent-based Approach for Preventing Blackouts in Power Systems . In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-015-4, pages 565-570. DOI: 10.5220/0004906505650570

in Bibtex Style

@conference{icaart14,
author={Michael Negnevitsky and Nikita Tomin and Daniil Panasetsky and Ulf Haeger and Nikolay Voropai and Christian Rehtanz and Victor Kurbatsky},
title={Neural Multi-agent-based Approach for Preventing Blackouts in Power Systems},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2014},
pages={565-570},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004906505650570},
isbn={978-989-758-015-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Neural Multi-agent-based Approach for Preventing Blackouts in Power Systems
SN - 978-989-758-015-4
AU - Negnevitsky M.
AU - Tomin N.
AU - Panasetsky D.
AU - Haeger U.
AU - Voropai N.
AU - Rehtanz C.
AU - Kurbatsky V.
PY - 2014
SP - 565
EP - 570
DO - 10.5220/0004906505650570