Artificial Neural Networks Applicable to Estimate Solar Radiation to Calculate the Reliability Charge in Photovoltaic Plants


Authors

DOI:

https://doi.org/10.22517/23447214.16481

Keywords:

Artificial Neural Networks, Base Load Power Reliability Charge, Photovoltaic Systems

Abstract

The Comisión de Energía y Gas (CREG) published in 2016 the guidelines to calculate the reliability charge for solar plants. The methodology indicates that in order to calculate the base load power for the reliability charge, it is required ten years of information with solar radiation and ambient temperature. In Colombia there is not such information, thus it is required to use strategies to estimate the required information from available data. In this paper Artificial Neutral Networks are used to estimate solar radiation considering ambient temperature, relative humidity and month of the year.

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Author Biographies

Valentina Triviño Castañeda, Universidad Tecnologica de Pereira

Ingeniera Electricista

Andres Escobar Mejía, Universidad Tecnológica de Pereira

Ingeniero Electricista

Henry Giovanny Valdes Jaramillo, Empresa de Energía de Pereira

Ingeniero Electricista

References

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Published

2018-03-30

How to Cite

Castañeda, V. T., Escobar Mejía, A., & Valdes Jaramillo, H. G. (2018). Artificial Neural Networks Applicable to Estimate Solar Radiation to Calculate the Reliability Charge in Photovoltaic Plants. Scientia Et Technica, 23(1), 11–17. https://doi.org/10.22517/23447214.16481

Issue

Vol. 23 No. 1 (2018)

Section

Eléctrica

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