Abstract
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.
Highlights
The smart grid concept involves the inclusion of renewable sources of electric generation and the use of devices for control and communication, leading to a more efficient and reliable electric supply for final users [1]
Just as in the previous case, all the values significantly vary from one section of the total harmonic distortion (THD) signal to another, confirming the fact that the piecewise approach implemented in this work helps to increase the reliability of the methodology
1 were used toinestimate delivered power these 4 days, the results presented weights presented
Summary
The smart grid concept involves the inclusion of renewable sources of electric generation and the use of devices for control and communication, leading to a more efficient and reliable electric supply for final users [1]. It has been reported that the inclusion of PV generation is associated with harmonic contamination [5,6], because it is necessary to use power inverters for converting the DC signals delivered by the PV panels into AC signals, which can be used by the final users. From the smart grid point of view, these are major issues, as the variability makes the generation process unreliable, and the harmonic content compromises the quality of the power supply. In this sense, several methodologies have been reported for the proper measurement
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