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The Application of Artificial Neural Networks to Pseudo Measurement Modeling in Distribution Networks

Distribution system state estimation is becoming an increasingly important feature in the modern power grid, but the lack of real measurements makes its implementation particularly difficult. A solution for this problem could be the generation of accurate pseudo measurements. For this purpose, an Artificial Neural Network based reactive power pseudo measurement generating algorithm (PMG-ANN) was created, which was implemented in a distribution system state estimation. After testing, it was concluded that the artificial neural network based pseudo measurement generator has successfully made the distribution network observable and achieved a high accuracy in the examined predictions. However, some points were identified where further improvements could be made.