Determination of Renewable Generation Operation with the Aid of the ANN
| Autor: | Luis H. C. Ferreira, B.I.L. Lopes, Luiz F. R. Monteiro, Juliana R. Monteiro, A. C. Zambroni de Souza |
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| Rok vydání: | 2018 |
| Předmět: |
Artificial neural network
Computer science business.industry Voltage control Monte Carlo method 02 engineering and technology Renewable energy Reliability engineering Electric power system 020204 information systems 0202 electrical engineering electronic engineering information engineering Renewable generation 020201 artificial intelligence & image processing business Voltage |
| Zdroj: | 2018 13th IEEE International Conference on Industry Applications (INDUSCON). |
| DOI: | 10.1109/induscon.2018.8627201 |
| Popis: | The significant penetration of renewable generation, mainly wind and solar, in the electrical system bring new challenges for power systems operation due to their dependency to weather conditions. In this perspective, this paper proposes an Artificial Neural Network (ANN) approach to identify operating conditions that can lead to voltage limits violation, enabling one to perform control actions in order to mitigate these scenarios. For this sake, the ANN approach determines the generating units responsible for the voltage limits violation, so that the system operator can determine whether or not the renewable unit(s) should stay connected to the system. The methodology was tested for the IEEE 34-bus system considering two renewables generators. The data are obtained employing Monte Carlo simulation with the help of a scanning backward/forward technique to obtain the load flow solution. The results indicate a robust methodology capable of assisting in decision making of renewable units’ operation in power system to avoid voltage violations. |
| Databáze: | OpenAIRE |
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