| Title | Power Systems Security Assessment Based on Artificial Neural Networks |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Tudose, Andrei, Micu, Robert, Picioroaga, Irina, Sidea, Dorian, Mandis, Alexandru, Bulac, Constantin |
| Conference Name | 2022 International Conference and Exposition on Electrical And Power Engineering (EPE) |
| Date Published | oct |
| Keywords | artificial neural network, composability, Contingency management, Dynamical Systems, Metrics, Multilayer Perceptron, N-1 contingency analysis, Power system dynamics, power system reliability, power system security, power system stability, Power systems security, pubcrawl, renewable energy sources, resilience, Resiliency, Stability analysis |
| Abstract | Power system security assessment is a major issue among the fundamental functions needed for the proper power systems operation. In order to perform the security evaluation, the contingency analysis is a key component. However, the dynamic evolution of power systems during the past decades led to the necessity of novel techniques to facilitate this task. In this paper, power systems security is defined based on the N-l contingency analysis. An artificial neural network approach is proposed to ensure the fast evaluation of power systems security. In this regard, the IEEE 14 bus transmission system is used to verify the performance of the proposed model, the results showing high efficiency subject to multiple evaluation metrics. |
| DOI | 10.1109/EPE56121.2022.9959761 |
| Citation Key | tudose_power_2022 |
Power Systems Security Assessment Based on Artificial Neural Networks