Meteorological Variables’ Influence on Electric Power Generation for Photovoltaic Systems Located at Different Geographical Zones in Mexico

Autor: Rafael Enrique Cabanillas-López, Enrique Fernando Velázquez-Contreras, Nun Pitalúa-Díaz, Jose A. Ruz-Hernandez, José Humberto Abril-García, Yasuhiro Matsumoto, Enrique J. Herrera-López, Fernando Arellano-Valmaña
Rok vydání: 2019
Předmět:
Meteorology
020209 energy
02 engineering and technology
010501 environmental sciences
lcsh:Technology
01 natural sciences
Wind speed
lcsh:Chemistry
0202 electrical engineering
electronic engineering
information engineering
meteorological variables
General Materials Science
Daylight
lcsh:QH301-705.5
Instrumentation
gradient descent
0105 earth and related environmental sciences
Fluid Flow and Transfer Processes
sustainable development
lcsh:T
Process Chemistry and Technology
Photovoltaic system
General Engineering
lcsh:QC1-999
Computer Science Applications
Power (physics)
Outdoor temperature
Electricity generation
lcsh:Biology (General)
lcsh:QD1-999
lcsh:TA1-2040
electric power
photovoltaic systems
Environmental science
Electric power
lcsh:Engineering (General). Civil engineering (General)
Gradient descent
lcsh:Physics
Zdroj: Applied Sciences
Volume 9
Issue 8
Applied Sciences, Vol 9, Iss 8, p 1649 (2019)
ISSN: 2076-3417
Popis: In this study, the relation among different meteorological variables and the electrical power from photovoltaic systems located at different selected places in Mexico were presented. The data was collected from on-site real-time measurements from Mexico City and the State of Sonora. The statistical estimation by the gradient descent method demonstrated that solar radiation, outdoor temperature, wind speed, and daylight hour influenced the electric power generation when it was compared with the real power of each photovoltaic system. According to our results, 97.63% of the estimation results matched the real data for Sonora and 99.66% the results matched for Mexico City, achieving overall errors less than 7% and 2%, respectively. The results showed an acceptable performance since a satisfactory estimation error was achieved for the estimation of photovoltaic power with a high determination coefficient R2.
Databáze: OpenAIRE
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