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Using Artificial Neural Network to Speed Up the Study of the State of Electrical Systems


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DOI: https://doi.org/10.15866/iree.v17i5.22216

Abstract


The objective of this article is to use Artificial Intelligence (AI) method to study the state of electrical networks. The state of a network is described by its state variables, such as the voltage at the buses of a network or the currents flowing in the sections of a network. Power flow analysis is a basic tool for planning an electrical power system. Power flow is a non-linear problem. Therefore, the solution to this type of problem can be found using iterative numerical methods or Artificial Intelligence methods. In this paper, the method of Artificial Neural Network (ANN) has been used to predict voltage magnitudes and voltage phase angles of the I3E 14 bus system and a real network of Morocco ONEE 24 bus system. After testing several Neural Network models, it has been possible to propose an architecture with one hidden layer and Levenberg-Marquardt backpropagation as a training function. The results obtained by using this method have been positive and precise compared with the results obtained by the reference method Newton-Raphson. This means that this method can be used to get results in real time, in case of lack of data from the studied system and also where the deterministic methods do not converge.
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Keywords


Artificial Intelligence; Power Flow Analysis; Artificial Neural Network; Voltage Magnitudes; Voltage Phase Angles

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