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conference paper
Optimization and learning of load restoration strategies
1996
PSCC. Proceedings of the Twelfth Power Systems Computation Conference
This paper describes an application of optimization and machine learning to load restoration in a generation-transmission system. An optimization procedure, combining a genetic algorithm and a power system dynamic simulator, generates the appropriate sequence of operations for each state of the power system. A machine learning technique (induction of decision trees) is applied to extract decision criteria that will guide the load restoration after a generalised black-out. The paper also presents the results of applying these techniques to a power system of realistic size
Type
conference paper
Authors
Publication date
1996
Published in
PSCC. Proceedings of the Twelfth Power Systems Computation Conference
Volume
1
Start page
276
End page
84
Peer reviewed
REVIEWED
EPFL units
Available on Infoscience
April 4, 2007
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