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Static Security Constrained Generation Scheduling Using Sensitivity Characteristics of Neural Network
2008
Iranian Journal of Electrical & Electronic Engineering
unpublished
This paper proposes a novel approach for generation scheduling using sensitivity characteristic of a Security Analyzer Neural Network (SANN) for improving static security of power system. In this paper, the potential overloading at the post contingency steady-state associated with each line outage is proposed as a security index which is used for evaluation and enhancement of system static security. A multilayer feed forward neural network is trained as SANN for both evaluation and enhancement
fatcat:itf6qwouo5ddbmqjpxtvffszei