Madrid - Solar PV statistics

monthly solar PV data for Madrid using PVGIS 5.2

Summary of different orientations of building integrated solar PV panels, using optimal inclinations versus ideal two axis tracking

Table 1: quarterly normalized energy distribution for different building integrated solar PV orientations in Madrid

Madrid	kWh/year	Q1+Q4	Q2+Q3	Q1	Q2	Q3	Q4
Two axis tracking	2261	40.0%	60.0%	20.8%	29.0%	31.0%	19.2%
Facing east, slope 2.0°	1321	32.3%	67.7%	17.7%	33.9%	33.8%	14.6%
Facing south, slope 37.0°	1562	43.0%	57.0%	22.3%	27.6%	29.4%	20.7%
Facing west, slope 1.0°	1320	32.4%	67.6%	17.7%	33.8%	33.8%	14.7%
Source: energy.at-site.be/pvgis52, non-commercial use permitted
Data source: PVGIS 5.2 © 2001-2023 European Communities - PVcalc tool
Two axis tracking and Building integrated with optimized fixed slope - Radiation model: PVGIS-SARAH2 - Loss=14%

Quarters: Q1 = Jan + Feb + Mar; Q2 = Apr + May + Jun; Q3 = Jul + Aug + Sep; Q4 = Oct, Nov, Dec

East facing building integrated solar PV, for different inclinations

Table 2: normalized cumulative and monthly energy distributions for different building integrated solar PV inclinations oriented to the east in Madrid

Madrid	kWh/kWpeak	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
Facing east; slope 2.0°; cumulative distribution	1321	4.2%	9.5%	17.7%	27.5%	39.1%	51.6%	64.7%	76.3%	85.4%	91.9%	96.3%	100%
Facing east: slope 2.0°; monthly distribution	1321	4.2%	5.4%	8.2%	9.8%	11.7%	12.4%	13.1%	11.6%	9.0%	6.6%	4.3%	3.7%
Facing east; slope 0.0°; cumulative distribution	1321	4.2%	9.6%	17.7%	27.5%	39.1%	51.5%	64.7%	76.3%	85.4%	91.9%	96.3%	100%
Facing east: slope 0.0°; monthly distribution	1321	4.2%	5.4%	8.1%	9.8%	11.7%	12.4%	13.2%	11.6%	9.0%	6.6%	4.3%	3.7%
Facing east; slope 30.0°; cumulative distribution	1262	4.4%	9.8%	18.1%	27.8%	39.5%	51.7%	64.6%	76.0%	85.0%	91.6%	96.1%	100%
Facing east: slope 30.0°; monthly distribution	1262	4.4%	5.5%	8.3%	9.7%	11.6%	12.3%	12.9%	11.5%	9.0%	6.7%	4.4%	4.0%
Facing east; slope 60.0°; cumulative distribution	1078	4.7%	10.3%	18.7%	28.4%	39.8%	51.7%	64.2%	75.5%	84.4%	91.2%	95.7%	100%
Facing east: slope 60.0°; monthly distribution	1078	4.7%	5.6%	8.4%	9.7%	11.4%	11.9%	12.4%	11.3%	8.9%	6.8%	4.6%	4.2%
Facing east; slope 90.0°; cumulative distribution	770	5.0%	10.8%	19.3%	29.0%	40.2%	51.8%	63.9%	75.1%	83.9%	90.9%	95.5%	100%
Facing east: slope 90.0°; monthly distribution	770	5.0%	5.8%	8.6%	9.7%	11.2%	11.6%	12.1%	11.2%	8.9%	6.9%	4.6%	4.5%
Data source: PVGIS 5.2 © 2001-2023 European Communities - PVcalc tool

South facing building integrated solar PV, for different inclinations

Table 3: normalized cumulative and monthly energy distributions for different building integrated solar PV inclinations oriented to the south in Madrid

Madrid	kWh/kWpeak	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
Facing south; slope 37.0°; cumulative distribution	1562	6.6%	13.6%	22.3%	31.0%	40.4%	49.9%	60.2%	70.3%	79.3%	87.2%	93.5%	100%
Facing south: slope 37.0°; monthly distribution	1562	6.6%	7.0%	8.6%	8.8%	9.4%	9.5%	10.3%	10.1%	9.1%	7.9%	6.3%	6.5%
Facing south; slope 0.0°; cumulative distribution	1321	4.2%	9.6%	17.7%	27.5%	39.1%	51.5%	64.7%	76.3%	85.4%	91.9%	96.3%	100%
Facing south: slope 0.0°; monthly distribution	1321	4.2%	5.4%	8.1%	9.8%	11.7%	12.4%	13.2%	11.6%	9.0%	6.6%	4.3%	3.7%
Facing south; slope 30.0°; cumulative distribution	1553	6.3%	13.1%	21.6%	30.5%	40.2%	50.1%	60.8%	71.1%	80.2%	87.9%	93.9%	100%
Facing south: slope 30.0°; monthly distribution	1553	6.3%	6.8%	8.6%	8.9%	9.7%	9.9%	10.7%	10.3%	9.1%	7.7%	6.0%	6.1%
Facing south; slope 60.0°; cumulative distribution	1465	7.8%	15.7%	24.6%	32.9%	41.2%	49.2%	58.0%	67.2%	76.3%	84.9%	92.2%	100%
Facing south: slope 60.0°; monthly distribution	1465	7.8%	7.9%	9.0%	8.3%	8.3%	8.0%	8.7%	9.3%	9.1%	8.6%	7.3%	7.8%
Facing south; slope 90.0°; cumulative distribution	1050	10.1%	19.6%	29.2%	36.7%	42.9%	48.1%	53.8%	61.3%	70.5%	80.6%	89.7%	100%
Facing south: slope 90.0°; monthly distribution	1050	10.1%	9.5%	9.6%	7.5%	6.2%	5.2%	5.7%	7.5%	9.2%	10.0%	9.2%	10.3%
Data source: PVGIS 5.2 © 2001-2023 European Communities - PVcalc tool

West facing building integrated solar PV, for different inclinations

Table 4: normalized cumulative and monthly energy distributions for different building integrated solar PV inclinations oriented to the west in Madrid

Madrid	kWh/kWpeak	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
Facing west; slope 1.0°; cumulative distribution	1320	4.2%	9.6%	17.7%	27.5%	39.1%	51.5%	64.7%	76.3%	85.4%	91.9%	96.3%	100%
Facing west: slope 1.0°; monthly distribution	1320	4.2%	5.4%	8.1%	9.8%	11.7%	12.4%	13.2%	11.6%	9.0%	6.6%	4.3%	3.7%
Facing west; slope 0.0°; cumulative distribution	1321	4.2%	9.6%	17.7%	27.5%	39.1%	51.5%	64.7%	76.3%	85.4%	91.9%	96.3%	100%
Facing west: slope 0.0°; monthly distribution	1321	4.2%	5.4%	8.1%	9.8%	11.7%	12.4%	13.2%	11.6%	9.0%	6.6%	4.3%	3.7%
Facing west; slope 30.0°; cumulative distribution	1234	4.4%	10.0%	18.1%	27.8%	39.1%	51.2%	64.1%	75.6%	84.6%	91.4%	95.9%	100%
Facing west: slope 30.0°; monthly distribution	1234	4.4%	5.6%	8.1%	9.7%	11.3%	12.1%	12.9%	11.5%	9.0%	6.7%	4.6%	4.1%
Facing west; slope 60.0°; cumulative distribution	1044	4.7%	10.5%	18.7%	28.3%	39.2%	50.9%	63.5%	74.7%	83.8%	90.7%	95.6%	100%
Facing west: slope 60.0°; monthly distribution	1044	4.7%	5.9%	8.2%	9.6%	10.9%	11.7%	12.6%	11.3%	9.0%	7.0%	4.8%	4.5%
Facing west; slope 90.0°; cumulative distribution	736	4.9%	11.1%	19.4%	28.8%	39.2%	50.4%	62.7%	73.7%	82.8%	90.0%	95.1%	100%
Facing west: slope 90.0°; monthly distribution	736	4.9%	6.2%	8.3%	9.4%	10.4%	11.2%	12.2%	11.0%	9.1%	7.2%	5.1%	4.8%
Data source: PVGIS 5.2 © 2001-2023 European Communities - PVcalc tool

Acknowledgement: many thanks to the PVGIS team for open access to PVGIS 5.2 PVcalc tool. Source - "Photovoltaic Geographic Information System (PVGIS)", European Commission, Joint Research Centre (JRC). Online tool available at re.jrc.ec.europa.eu/pvgis.html - PVGIS Ⓒ European Communities, 2001-2023.

Methods: in this work, monthly data for various solar panel orientations is combined. An explanation of PVGIS data sources and calculation methods is available in [1]. Papers [2][3][4][5] provide additional background on the PVGIS methods and references [6][7][8][9] detail the used solar radiation models. In this work we use the proposed (default) solar radiation model per region of PVGIS and we use city names to refer to specific coordinates on the world map. Ocean locations are not modelled in the PVGIS tool, hence we limit ourselves to the land mass of the planet. Both free standing and building integrated (rooftop) solar panels are simulated, with a slope of 0 a horizontal panel and a slope of 90 degrees a vertical oriented panel, for example to mount on a wall. The used PVcalc simulation does not take into account detailed local shadowing effects. Also the invertor is not modelled in detail, and grid saturation is not taken into account as well as dirt on the panels. All these aspects can decrease the effective yield of the PV solar panels. A limitation of PVGIS5.2 is that the optimal inclination of a solar panel is not correctly computed for building integrated solar panels facing west.

References:

[1]

Overview of PVGIS data sources and calculation methods.

joint-research-centre.ec.europa.eu/pvgis-photovoltaic-geographical-information-system/getting-started-pvgis/pvgis-data-sources-calculation-methods_en

[2]

Huld, T.; Müller, R.; Gambardella, A. A new solar radiation database for estimating PV performance in Europe and Africa. Solar Energy 2012, 86, 1803-1815.

doi: 10.1016/j.solener.2012.03.006

[3]

Gracia Amillo, A.; Huld, T.; Müller, R. A New Database of Global and Direct Solar Radiation Using the Eastern Meteosat Satellite, Models and Validation. Remote Sensing 2014, 6, 8165-8189.

doi:10.3390/rs6098165

[4]

Huld, T.; Gracia Amillo, A. Estimating PV Module Performance over Large Geographical Regions: the role of Irradiance, Air Temperature, Wind Speed and Solar Spectrum. Energies 2015, 8, 6, 5159-5181.

doi:10.3390/en8065159

[5]

A.M. Gracia Amillo, N. Taylor, A.M. Martinez, E.D. Dunlop, P. Mavrogiorgios, F. Fahl, G. Arcaro, I. Pinedo (2021): Adapting PVGIS to Trends in Climate, Technology and User Needs, Proc. 38th European Photovoltaic Solar Energy Conference and Exhibition, p. 907-911

doi:10.4229/EUPVSEC20212021-5BO.6.1

[6]

Müller, Richard; Pfeifroth, Uwe; Träger-Chatterjee, Christine; Cremer, Roswitha; Trentmann, Jörg; Hollmann, Rainer (2015): Surface Solar Radiation Data Set - Heliosat (SARAH) - Edition 1, Satellite Application Facility on Climate Monitoring.

doi: 10.5676/EUM_SAF_CM/SARAH/V001

[7]

Pfeifroth, Uwe; Kothe, Steffen; Trentmann, Jörg; Hollmann, Rainer; Fuchs, Petra; Kaiser, Johannes; Werscheck, Martin (2019): Surface Radiation Data Set - Heliosat (SARAH) - Edition 2.1, Satellite Application Facility on Climate Monitoring

doi: 10.5676/EUM_SAF_CM/SARAH/V002_01

[8]

Hersbach, H, Bell, B, Berrisford, P, et al. The ERA5 global reanalysis. Q J R Meteorol Soc. 2020; 146: 1999– 2049.

doi: 10.1002/qj.3803

[9]

Manajit Sengupta, Yu Xie, Anthony Lopez, Aron Habte, Galen Maclaurin, James Shelby, The National Solar Radiation Data Base (NSRDB), Renewable and Sustainable Energy Reviews, Volume 89, 2018, Pages 51-60.

doi: 10.1016/j.rser.2018.03.003

Additional PVGIS publications are available at: ec.europa.eu/jrc/en/PVGIS/about/who.