Journal
APPLIED SCIENCES-BASEL
Volume 10, Issue 2, Pages -Publisher
MDPI
DOI: 10.3390/app10020542
Keywords
genetic algorithms; parameter estimation; photovoltaic systems; power quality; total harmonic distortion
Categories
Funding
- CONACYT [415315]
- FOFI-UAQ 2018 [FIN201812]
- PRODEP [UAQ-PTC-385]
- University of Valladolid
- Rene de J. Romero-Troncoso
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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.
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