PV 2012/2013. Radiation from the Sun Atmospheric effects Insolation maps Tracking the Sun PV in urban environment

Transcription

1 SOLAR RESOURCE Radiation from the Sun Atmospheric effects Insolation maps Tracking the Sun PV in urban environment 1

2 is immense Human energy use: 4.0x10 14 kwh/year on Earth s surface: 5.5x10 17 kwh/year is immense Human energy use: 4.0x10 14 kwh/year on Earth s surface: 5.5x10 17 kwh/year ia.org/wiki/file:solar_land_area.png Local solar irradiance averaged over three years from 1991 to 1993 (24 hours a day) taking into account the cloud coverage available from weather satellites Solar power systems covering the areas defined by the dark disks could provide more than the world's total primary energy demand (assuming a conversion efficiency of 8%). 2

3 is immense Human energy use: 4.0x10 14 kwh/year on Earth s surface: 5.5x10 17 kwh/year is global and democratic is relatively constant but depends on atmospheric effects, including absorption and scattering local variations in the atmosphere, such as water vapour, clouds, and pollution latitude of the location the season of the year and the time of day P 0 T Rsun Total radiative power (Stefan Boltzman) T=5762K Surface area of sun Power radiated per unit area 5.96x10 7 W/m 2 3

4 P 0 T Rsun Ratio of surface areas of the 2 spheres Solar constant average energy flux incident at the Earth s orbit: 1366 W/m 2 4 R S 4 D 2 sun 2 P 0 Distance Sun-Earth P 0 T Rsun R sun D avg R Earth 6.96x10 5 km 1.5x10 8 km 6.35x10 3 km Energy incident on Earth Total area of Earth 4 R S 4 D S R 2 4 R 2 Earth Earth 2 sun 2 P 0 S 4 Average energy incident per unit area of surface of Earth: 342 W/m 2 4

5 Earth-Sun motion 23.7 º Polar axis 365 days and 6 hours H 360n cos S 365 H(W/m2) is radiant power density outside the atmosphere; S is solar constant; n is day of the year Earth-Sun motion Solar declination: angle between line joining centres of Earth and Sun and the equatorial plane Polar axis 0º +23º 27 5

6 Earth-Sun motion Solar declination: angle between line joining centres of Earth and Sun and the equatorial plane Polar axis 0º +23º 27 Autumnal equinox Earth-Sun motion Solar declination: angle between line joining centres of Earth and Sun and the equatorial plane Polar axis 0º +23º 27 Autumnal equinox -23º 27 6

7 Earth-Sun motion Solar declination: angle between line joining centres of Earth and Sun and the equatorial plane Polar axis +23º 27 0º Vernal and automnal equinox -23º 27 Earth-Sun motion Solar declination: angle between line joining centres of Earth and Sun and the equatorial plane the equatorial plane n sin Declination in radians; n is the number of the day (Jan 1st = 1) 7

8 Earth-Sun motion sin sin sin cos cos sin sin sin cos cos cos 0º solar azimuth S 0º solar elevation 90º O N E -90º Optimum orientation: facing south (north in the southern hemisphere) Optimum inclination: local latitude but not quite 8

9 Atmospheric effects Atmospheric effects on solar radiation at the Earth's surface: a reduction in the power of the solar radiation due to absorption, scattering and reflection in the atmosphere; scattering and reflection in the atmosphere; a change in the spectral content of the solar radiation due to greater absorption or scattering of some wavelengths; the introduction of a diffuse or indirect component into the solar radiation; and local variations in the atmosphere (such as water vapour, clouds and pollution) which have additional effects on the incident power, spectrum and directionality. 9

10 Air Mass is a measure of the reduction in the power of light as it passes through the atmosphere and is absorbed by air and dust AM 1 cos AM0 - Extraterrestrial Wm -2 nm AM1.5 - Global AM1.5D - Direct Wavelength (nm) 10

11 Wm -2 nm Photon flux [photons/s/m 2 ] Power density H[W/m 2 ] Spectal irradiance F [W/m 2 /m] is the power density at a given (m) H F photons 2 m s hc 1.24 E m d F W hc H 2 m W hc F 2 2 m m 0 i Wavelength (nm) 11

12 Insolation: Incoming Solar Radiation Typical units: kwh/m 2 /day Affected by latitude, local weather patterns, Šúri M., Huld T.A., Dunlop E.D. Ossenbrink H.A., Potential of solar electricity generation in the European Union member states and candidate countries. Solar Energy, 81, , 12

13 Yearly sum of global irradiation on vertical surface (kwh/m 2 ) period

14 Yearly sum of global irradiation on horizontal surface (kwh/m 2 ) period Yearly sum of global irradiation on optimally-inclined surface (kwh/m 2 ) period

15 Yearly sum of global irradiation on 2-axis tracking surface (kwh/m 2 ) period

16 Coastal areas and higher mountains face wider variations (up to 10%) Winter is much more variable (up to x6) than summer months Šúri M., Huld T., Dunlop E.D., Albuisson M., Lefèvre M., Wald L., Uncertainties in photovoltaic electricity yield prediction from fluctuation of solar radiation. Proceedings of the 22nd European Photovoltaic Solar Energy Conference, Milano, Italy

17 PV 2012/2013 Solar tracking Compared to PV with modules fixed at optimum angle: Changing inclination twice a year contributes only marginally Comparison of electricity yield from fixed and suntracking PV systems in Europe [JRC, 2008] Solar tracking Comparison of electricity yield from fixed and suntracking PV systems in Europe [JRC, 2008] 17

18 Solar tracking Comparison of electricity yield from fixed and suntracking PV systems in Europe [JRC, 2008] Solar tracking Compared to PV with modules fixed at optimum angle: Changing inclination twice a year contributes only marginally (2-4%) 1-axis tracking PV with vertical or South-inclined axis generates only 1-4% less than 2-axis tracking system 1-axis tracking PV with horizontal axis oriented E-W typically performs only slightly better than fixed mounting systems Comparison of electricity yield from fixed and suntracking PV systems in Europe [JRC, 2008] 18

19 Solar tracking 1.5x10-4 Hourly energy produced by PV system with 2-axes tracking [kwh/wp] 0 110º Incidence angle on fixed panel with optimum inclination 100% Ratio between energy produced using system with 2-axes tracking and fixed panel with optimum inclination Gaspar et al, Exploring One-Axis Tracking Configurations For CPV Application, CPV7, Las Vegas 2011 Configuration Tracking angle Incidente angle on PV receptor Energy produced compared with 2-axis tracking S N º -90º During the summer, in the North- South horizontal axis, the misalignment between module and the position of the sun reaches 40º. S N In a North-South inclined axis, the position of the module is perfect twice a year, in spring and autumn, and misalignment never exceeds 30º. E W Horizontal East-West axis is particularly suitable for midday hours, when insolation is at a maximum, but misses early and late hours. In a vertical axis with inclined panel, the misalignment will be lowest when the insolation is highest. Gaspar et al, Exploring One-Axis Tracking Configurations For CPV Application, CPV7, Las Vegas

20 Solar tracking kwh/wp/year An inclined axis tracking system orientated in the north-south direction is able to closely follow the Sun 500 throughout the year, and have a relatively high acceptance for CPV applications. 0 The vertical 2-axes tracking, NS inclined with Vertical optimum NS horinclination, EW features Fixed a similar performance that an inclined axis tracking system orientated in the north-south direction. Gaspar et al, Exploring One-Axis Tracking Configurations For CPV Application, CPV7, Las Vegas 2011 Solar tracking 20

21 Solar tracking of blobal irradiation kwh/m Solar tracking PVGIS exercise: Lisbon Fixed angle 0º Fixed angle 33º Vertical axis 33º Inclined axis 33º 2-axis tracking Average sum of blobal irradiation kwh/m2 A 200% 150% 100% 50% 0% Fixed Fixed Vertical Inclined 2-axis angle 0º angle 33º axis 33º axis 33º tracking Average sum Month 21

22 Solar tracking Shadowing effect Ground cover ratio = PV area / total area Inclined tracking 2-axis tracking Horizontal tracking GCR = PV density 1 /GCR E. Narvarte et al, Tracking and Ground Cover Ratio, Prog. Photovolt: Res. Appl. 2008; 16: PV in urban environment Carnaxide (38.43 N, 9.8 W) N. Gomes et al, PV potential in urban environment using LIDAR data, 2010, Solar Energy 22

23 PV in urban environment N. Gomes et al, PV potential in urban environment using LIDAR data, 2010, Solar Energy PV in urban environment N. Gomes et al, PV potential in urban environment using LIDAR data, 2010, Solar Energy 23

24 PV in urban environment N. Gomes et al, PV potential in urban environment using LIDAR data, 2010, Solar Energy PV in urban envir 24

25 PV in urban envir PV in urban envir 25

26 PV in urban envir PV in urban environment NW N 20% 15% NE Orientation distribution of roof area (black line). Irradiation distribution as a function of roof orientation (red line). 10% 5% W 0% E SW SE S Roof area Irradiation 100% 80% 93% 60% 58% Distribution of footprint area (dark boxes) and estimated population (white boxes) according to building typology. 40% 20% 0% 28% 14% 7% 0% House Flats Uninhabited N. Gomes et al, PV potential in urban environment using LIDAR data, 2010, Solar Energy 26

27 PV in urban environment 100% 80% % available energy 60% 40% 24% 57% 20% 13% 0% 0% 20% 40% 60% 80% 100% % available area Fraction of available irradiation as a function of occupied roof area, for the SDM (black line) and TDM (red line). N. Gomes et al, PV potential in urban environment using LIDAR data, 2010, Solar Energy PV in urban environment 115% 110% SDM/TDM 105% 102% 100% 95% 0% 20% 40% 60% 80% 100% % available area Ratio of cumulative irradiation for SDM and TDM as a function of occupied area (solid line). Red line indicates overall ratio (assuming 100% roof coverage) and dashed line indicates 100% for easier reading. N. Gomes et al, PV potential in urban environment using LIDAR data, 2010, Solar Energy 27

28 PV in urban environment MWh/m2/year % 0.0 0% 20% 40% 60% 80% 100% % available area Annual irradiation per unit area as a function of roof area. Dotted line indicates annual irradiation per unit area on a horizontal surface for the same location. N. Gomes et al, PV potential in urban environment using LIDAR data, 2010, Solar Energy PV in urban environment Procedure for estimating the PV potential of an urban region using LiDAR data based on the Solar Analyst extension for ArcGIS. PV potential of the 538 buildings to be around 11.5 GWh/year for an installed capacity of 7MW, which corresponds to 48 % of the local electricity demand. For low PV penetration (about 10% of total roof area) the PV potential is well estimated by considering no shade and the local optimum inclination andorientation. For high PV penetration (i.e. covering close to all roof area) the PV potential is well estimated by considering a horizontal surface with the footprint area of the buildings. N. Gomes et al, PV potential in urban environment using LIDAR data, 2010, Solar Energy 28

29 PV in urban environment Each point of the DSM will cast a shadow along the line opposite to the position of the sun at that particular time. This shadow line is interrupted when a DSM cell along that line features a Z value higher that the shadow line at that position. P. Redweik et al, PV potential estimation using 3D local scale solar radiation model based on urban LIDAR data, PVSEC 2011 PV in urban environment Combining the shadow height for the façades with the shadow map for the ground. North is upwards. Shadows on January 1 st, at 9:00am. P. Redweik et al, PV potential estimation using 3D local scale solar radiation model based on urban LIDAR data, PVSEC

30 PV in urban environment Monthly radiation (kwh/m 2 ) for all months of the year (January top left to December bottom right). Colour code is the same for all maps. P. Redweik et al, PV potential estimation using 3D local scale solar radiation model based on urban LIDAR data, PVSEC 2011 PV in urban environment 30

31 Next class Further reading M. Šúri,et al, Potential of solar electricity generation in the European Union member states and candidate countries. Solar Energy, 81 (2007) M. Šúri et al, Uncertainties in photovoltaic electricity yield prediction from fluctuation of solar radiation. Proc. 22nd European Photovoltaic Solar Energy Conference, Milano, Italy 2007 T. Huld et al, Comparison of Potential Solar Electricity Output from Fixed- Inclined and Two-Axis Tracking Photovoltaic Modules in Europe, Prog. Photovolt: Res. Appl. 2008; 16:47 59 E. Narvarte et al, Tracking and Ground Cover Ratio, Prog. Photovolt: Res. Appl. 2008; 16: