ABSTRACT
In solar energy applications, a complete knowledge and detailed analysis of the solar radiation potential is a prerequisite. In this paper, two different photovoltaic (PV) potential analysis approaches are compared. The first approach is based on a simulation of PV array and six different solar radiation estimation models. The outputs of these models are compared with hourly ground measured data by using statistical error methods. The most suitable solar radiation model which gives more accurate results is used to calculate the PV potential of Engineering Faculty of Eskişehir Technical University. The PV panel simulation is implemented in Matlab/Simulink besides that a suitable algorithm is selected to calculate the possible amount of PV panel energy generation based on the hourly measured wind speed (WS), air pressure, global solar radiation (GSR), and temperature values. In the second approach, building roof surface PV potential of the selected area is calculated and the available roof area for PV installation is determined by using Aeronautical Geographical Information System (ArcGIS) software. When the performances of the methods are compared, these methods obtained satisfactory results. Furthermore, it is clear that the algorithms and effective factors of the two methods are different. The results of ArcGIS outperform the PV array simulation based on Badescu model by the reason of its suitability of selecting optimal site for PV installation.
Nomenclature
Slope angle
Maximum voltage coefficient
Open circuit voltage coefficient
Thermal voltage of PV
Temperature difference from data sheet
Difference between of PV temperatures
Sunrise hour angle
Sunset hour angle
Hour angle
Latitude of the zone
Ground reflectance coefficient
Declination angle
Angle of incidence
Zenith angle
Coefficients from PV array data sheet
Anisotropy index
Coefficients of air mass factor
Maximum current coefficient
Short circuit current coefficient
Angle between the sun and module
Incident angle coefficients
Coefficients regarding
Coefficients regarding
Equation of time
Modulating function
View factor for diffused radiation
Planck constant
Direct solar radiation on horizontal surface
Nominal solar radiation, generally 1000
Total GSR on sloped surface
Measured solar radiation on PV
Direct solar radiation on sloped surface
Diffused solar radiation on sloped surface
Reflected solar radiation on sloped surface
Output current of the PV array
Current at the maximum-power point
Saturation current of the PV array
Light-generated current at
PV current of the PV array
Nominal short-circuit current
Short-circuit current
Boltzmann’s constant
Hourly diffuse fraction
Hourly clearness index
Local longitude
Standard time meridian
Local standard time
Air mass depend on and air pressure
Coefficient providing the irradiance dependence for the temperature coefficient,
Coefficient providing the irradiance dependence for the temperature coefficient
Standard air mass
Day of the year
Ideality factor of the diode
Number of cells in parallel in PV
Number of cells in series in PV
Total number modules in the parallel
Total number modules in the series
Measured air pressure
Nominal pressure 760
Maximum measured peak output power
Calculated maximum power
Power at maximum-power point ()
Electron charge
Parallel resistance in PV
Series resistance in PV
Solar time
Measured temperature for ideal PV simulation
Measured ambient air temperature
Cell temperature inside module
Back-surface module temperature
Nominal cell temperature
Output voltage of the PV array
Thermal voltage
Voltage at maximum-power point ()
Nominal open circuit voltage data sheet
Open-circuit voltage ()
Wind speed measured at 10-m height
Diffused solar radiation
Extraterrestrial solar irradiation
Measured solar radiation on horizontal surface
Direct radiation conversion coefficient
Total PV panel area ()
Solar energy potential ()
Annual solar radiation ()
Number of hours
Performance ratio coefficient
PV panel yield
Calculated solar radiation
Measured solar radiation
Acknowledgments
This study is supported in part by the Scientic Research Projects Commission of Eskişehir Technical University under the general purpose grant 19ADP005.
Thanks to Earth and Space Sciences Institute of Eskişehir Technical University that provided us Digital Elevation Data and Aerial Image of the Campus.
Additional information
Notes on contributors
Kübra Bitirgen
Kübra Bitirgen graduated from Anadolu University in Turkey as an Electrical and Electronics Engineer in 2016. She got MSc from Anadolu University in 2018. She is currently a PhD student in Electrical and Electronics Engineering in Eskişehir Technical University. Her special fields of interest include power systems, electrical machines, energy systems, intelligent systems, and renewable energy.
Ümmühan Başaran Filik
Ümmühan Başaran Filik graduated from Anadolu University in Turkey as an Electrical and Electronics Engineer in 2002. She got MSc and PhD degree from Anadolu University in 2004 and 2010, respectively. She is currently an associate professor on Power System Analysis in Eskişehir Technical University. Her special fields of interest include power system analysis–optimization, renewable energy systems, and smart grids.