Artificial neural network based static security assessment module using PMU measurements for smart grid application

Power system security is one of the key issues in the operation of smart grid system. Evaluation of power system security is a big challenge considering all the contingencies, due to huge computational efforts involved. Phasor measurement unit plays a vital role in real time power system monitoring...

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Bibliographic Details
Published in2016 International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS) pp. 1 - 5
Main Authors Paramathma, M. Krishna, Devaraj, D., Reddy, B. Subba
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.02.2016
Subjects
Artificial Neural network
Genetic algorithm
Genetic algorithms
Neurons
Phasor Measurement unit
Phasor measurement units
Power system security
Real-time systems
Security
Training
Voltage measurement
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Summary:Power system security is one of the key issues in the operation of smart grid system. Evaluation of power system security is a big challenge considering all the contingencies, due to huge computational efforts involved. Phasor measurement unit plays a vital role in real time power system monitoring and control. This paper presents static security assessment scheme for large scale inter connected power system with Phasor measurement unit using Artificial Neural Network. Voltage magnitude and phase angle are used as input variables of the ANN. The optimal location of PMU under base case and critical contingency cases are determined using Genetic algorithm. The performance of the proposed optimization model was tested with standard IEEE 30 bus system incorporating zero injection buses and successful results have been obtained.
DOI:10.1109/ICETETS.2016.7603086