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ANN Based Power System Restoration

Power System Restoration (PSR) has been a subject of study for many years. In recent years many techniques were proposed to solve the limitations of predetermined restoration guidelines and procedures used by a majority of system operators to restore a system following the occurrence of a wide area disturbance. This paper discusses limitations encountered in some currently used PSR techniques and a proposed improvement based on Artificial Neural Networks (ANNs). This proposed scheme has been tested on a 162-bus transmission system and compared with a breadth search transmission system. The results indicate that, this is a feasible option that should be considered for real time applications.

Artificial Neural Networks (ANNs) are computational techniques that try to obtain a performance similar to that of humanís performance when solving problems. The building block of ANN is Artificial Neuron, which has got structural & functional similarities with biological neurons. ANN is also an efficient alternative for problem solutions where it is possible to obtain data describing the problem behavior, but a mathematical description of the process is impossible. The proposed restoration scheme is composed of several Island Restoration Schemes (IRS). Each IRS is responsible for the development of an Island Restoration Plan when the power system is recovering from a wide area disturbance.


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Seminar Topics - Electrical - Electronics - Mechanical - Civil - Chemical - Computer - Automobile

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