1. Modeling of Harmonic Current in Electrical Grids with Photovoltaic Power Integration Using a Nonlinear Autoregressive with External Input Neural Networks
- Author
-
Roberto L. Avitia, Adán Alberto Jumilla-Corral, Zulma Yadira Medrano-Hurtado, Carlos Pérez-Tello, Héctor Enrique Campbell-Ramírez, and Pedro Mayorga-Ortiz
- Subjects
Technology ,Control and Optimization ,model ,prediction ,inverters ,photovoltaic systems ,artificial neural networks ,nonlinear autoregressive with external input ,Computer science ,Group method of data handling ,Computer Science::Neural and Evolutionary Computation ,Energy Engineering and Power Technology ,02 engineering and technology ,0202 electrical engineering, electronic engineering, information engineering ,Electronic engineering ,Electrical and Electronic Engineering ,Engineering (miscellaneous) ,Total harmonic distortion ,Artificial neural network ,Renewable Energy, Sustainability and the Environment ,020208 electrical & electronic engineering ,Photovoltaic system ,Grid ,Power (physics) ,Harmonic ,020201 artificial intelligence & image processing ,Electric power ,Energy (miscellaneous) - Abstract
This research presents the modeling and prediction of the harmonic behavior of current in an electric power supply grid with the integration of photovoltaic power by inverters using artificial neural networks to determine if the use of the proposed neural network is capable of capturing the harmonic behavior of the photovoltaic energy integrated into the user’s electrical grids. The methodology used was based on the use of recurrent artificial neural networks of the nonlinear autoregressive with external input type. Work data were obtained from experimental sources through the use of a test bench, measurement, acquisition, and monitoring equipment. The input–output parameters for the neural network were the current values in the inverter and the supply grid, respectively. The results showed that the neural network can capture the dynamics of the analyzed system. The generated model presented flexibility in data handling, allowing to represent and predict the behavior of the harmonic phenomenon. The obtained algorithm can be transferred to physical or virtual systems for the control or reduction of harmonic distortion.
- Published
- 2021