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 competitiveâcollaborative multi-agent control system. For demonstration purposes, we investigated conventional and neural multi-agent automatic control schemes. Results are presented and discussed.
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Neural Multi-agent-based Approach for Preventing Blackouts in Power Systems
Semantic Scholar · Computer Science · 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 competitiveâcollaborative multi-agent control system. For demonstration purposes, we investigated conventional and neural multi-agent automatic control schemes. Results are presented and discussed.