Estimación del margen de estabilidad de voltaje en el sistema nacional interconectado S.N.I., utilizando herramientas de aprendizaje automático.

Abstract

Voltage stability margin assessment of a power system can be done through conventional methods such as: continuation power flows, PV curves, among others. However, when this type of analysis is required in real time, it is inconvenient to apply all these methods due to the large amount of information that is handled during the development of the algorithms. In this sense, the generation of a reliable database of the entire system that considers a considerable number of operating scenarios, together with the application of artificial intelligence algorithms, can be the solution to avoid the complications of time and computational effort. The aim of this degree work is to design a voltage stability evaluation tool capable of operating online, by structuring of a database for power system, and the subsequent estimation of the voltage stability margin. This is done through the implementation of artificial intelligence algorithms available in the Python programming language, with the purpose of optimizing calculation times and reducing the computational load that voltage stability analysis requires through conventional methods.