RT info:eu-repo/semantics/article
T1 Genetic algorithm methodology for the estimation of generated power and harmonic content in photovoltaic generation
A1 Elvira Ortiz, David Alejandro
A1 Jaen Cuellar, Arturo Yosimar
A1 Moríñigo Sotelo, Daniel
A1 Morales Velázquez, Luis
A1 Osornio Ríos, Roque A.
A1 Romero Troncoso, René de Jesús
K1 Genetic algorithms
K1 Algoritmos genéticos
K1 Photovoltaic systems
K1 Sistema fotovoltaicos
AB Renewable generation sources like photovoltaic plants are weather dependent and it is hard to predict their behavior. This work proposes a methodology for obtaining a parameterized model that estimates the generated power in a photovoltaic generation system. The proposed methodology uses a genetic algorithm to obtain the mathematical model that best fits the behavior of the generated power through the day. Additionally, using the same methodology, a mathematical model is developed for harmonic distortion estimation that allows one to predict the produced power and its quality. Experimentation is performed using real signals from a photovoltaic system. Eight days from different seasons of the year are selected considering different irradiance conditions to assess the performance of the methodology under different environmental and electrical conditions. The proposed methodology is compared with an artificial neural network, with the results showing an improved performance when using the genetic algorithm methodology.
PB MDPI
SN 2076-3417
YR 2020
FD 2020
LK https://uvadoc.uva.es/handle/10324/53032
UL https://uvadoc.uva.es/handle/10324/53032
LA eng
NO Applied Sciences, 2020, vol. 10, n. 2, 542
NO Producción Científica
DS UVaDOC
RD 06-ago-2024