Photovoltaic techno-economical potential on roofs in regions and islands: The case of the Canary Islands. Methodological review and methodology proposal

The literature review shows a wide range of methodologies aiming at determining the photovoltaic (PV) potential. Very often, the methodology scale is too large (continents, countries or large regions) or too small (cities) or it is based on specific and non-commonly available software tools. This is why the proposed methodology to determine the PV roof potential in regions and/or islands can be useful. This methodology has been applied to the Canary Islands. Firstly, the available roof area for PV systems is determined, based on the total roof surface (using real data from the Spanish Cadastre) and utilization factors according to the municipality type. The methodology proposed to calculate the available roof surface is then compared to other well-known methods, including potential improvements using Geographical Information Systems. Secondly, the mean annual global solar radiation per municipality on inclined surfaces has been determined. To do so, a review of different methodologies has been assessed in a comprehensible manner, seeking for the ones that provide accuracy and simplicity. Thirdly, the yearly PV production per municipality has been calculated. For this, a step-by-step method to calculate the PV system efficiency, based on existing literature, has been detailed. Three different scenarios depending on the shared use of the available roof surface are defined and the corresponding PV production is calculated. A sensitivity analysis is also included, analyzing PV production in two cases: depending on back ventilation of the roof-mounted PV systems and on PV cell type (poly-crystalline to mono-crystalline). Finally, an economic assessment based on cost-resource curves is carried out. The spirit of the paper is to develop a methodology based on accuracy and, at the same, simplicity, understanding such as a method where all the calculations can be easily done using pen and paper, calculator and common office software programs.

[1]  R. Vardimon Assessment of the potential for distributed photovoltaic electricity production in Israel , 2011 .

[2]  Ha T. Nguyen,et al.  Quantifying Rooftop Solar Photovoltaic Potential for Regional Renewable Energy Policy , 2010, Comput. Environ. Urban Syst..

[3]  Silvia Sobral García La caracterización de un espacio turístico a través de un sig , 2008 .

[4]  E. Karatepe,et al.  Development of a suitable model for characterizing photovoltaic arrays with shaded solar cells , 2007 .

[5]  Eduardo Lorenzo,et al.  Radiación solar y dispositivos fotovoltaicos: conceptos de electricidad. La célula solar , 2012 .

[6]  M. H. Macagnan,et al.  SOLAR RADIATION IN MADRID , 1994 .

[7]  Anne Mirjam Held,et al.  Modelling the Future Development of Renewable Energy Technologies in the European Electricity Sector Using Agent-based Simulation , 2011 .

[8]  J. Duffie,et al.  Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation , 1982 .

[9]  Gustavo Nofuentes,et al.  Tools for the profitability analysis of grid‐connected photovoltaics , 2002 .

[10]  W. V. Sark,et al.  Technical potential for photovoltaics on buildings in the EU-27 , 2012 .

[11]  M. K. Fuentes,et al.  Performance evaluation of large-scale photovoltaic systems , 1984 .

[12]  H. Kambezidis,et al.  DIFFUSE SOLAR IRRADIATION MODEL EVALUATION IN THE NORTH MEDITERRANEAN BELT AREA , 2001 .

[13]  Eduardo Lorenzo,et al.  Solar Electricity: Engineering of Photovoltaic Systems , 1994 .

[14]  Michael Doneus,et al.  Identification of roof areas suited for solar energy conversion systems , 1997 .

[15]  Germán Martínez,et al.  Analysis of the photovoltaic solar energy capacity of residential rooftops in Andalusia (Spain) , 2010 .

[16]  T. Santos,et al.  Photovoltaic potential in a Lisbon suburb using LiDAR data , 2012 .

[17]  L. Bergamasco,et al.  Scalable methodology for the photovoltaic solar energy potential assessment based on available roof surface area: application to Piedmont Region (Italy) , 2011 .

[18]  D. Robinson Urban morphology and indicators of radiation availability , 2006 .

[19]  M. Hoogwijk On the global and regional potential of renewable energy sources , 2004 .

[20]  Simon Roberts,et al.  Building Integrated Photovoltaics , 2005 .

[21]  Thomas Huld,et al.  PV-GIS: a web-based solar radiation database for the calculation of PV potential in Europe , 2005 .

[22]  W. Warta,et al.  Solar cell efficiency tables (version 35) , 2010 .

[23]  W. Beckman,et al.  Evaluation of hourly tilted surface radiation models , 1990 .

[24]  D. L. King,et al.  Analysis of factors influencing the annual energy production of photovoltaic systems , 2002, Conference Record of the Twenty-Ninth IEEE Photovoltaic Specialists Conference, 2002..

[25]  Bill Jeppesen Rooftop solar power , 2004 .

[26]  J. Hay Calculating solar radiation for inclined surfaces: Practical approaches , 1993 .

[27]  Thomas Huld,et al.  Solar Resource Modelling for Energy Applications , 2007 .

[28]  P. Ineichen,et al.  A new simplified version of the perez diffuse irradiance model for tilted surfaces , 1987 .

[29]  Benjamin Y. H. Liu,et al.  The interrelationship and characteristic distribution of direct, diffuse and total solar radiation , 1960 .

[30]  E. Ghisi Potential for potable water savings by using rainwater in the residential sector of Brazil , 2006 .

[31]  K. Gopinathan Solar radiation on variously oriented sloping surfaces , 1991 .

[32]  J. Kaňuk,et al.  Assessment of photovoltaic potential in urban areas using open-source solar radiation tools , 2009 .

[33]  N. Fueyo,et al.  A method for estimating the geographical distribution of the available roof surface area for large-scale photovoltaic energy-potential evaluations , 2008 .

[34]  A. Rabl,et al.  The average distribution of solar radiation-correlations between diffuse and hemispherical and between daily and hourly insolation values , 1979 .

[35]  N. Martín,et al.  Calculation of the PV modules angular losses under field conditions by means of an analytical model , 2001 .

[36]  Henry Kelly,et al.  Renewable energy : sources for fuels and electricity , 1993 .

[37]  Todd Otanicar,et al.  A hierarchical methodology for the mesoscale assessment of building integrated roof solar energy systems , 2011 .

[38]  E. Caamaño-Martín,et al.  Assessing the solar irradiation potential for solar photovoltaic applications in buildings at low latitudes - Making the case for Brazil , 2012 .

[39]  E. Lorenzo,et al.  Modelling and financial analysis tools for PV grid‐connected systems , 1996 .

[40]  Parreño Castellano,et al.  Análisis geográfico de la vivienda en Canarias : la promoción privada de protección oficial en el área metropolitana de La Palmas de Gran Canaria (España) , 2011 .

[41]  Jaroslav Hofierka,et al.  A New GIS‐based Solar Radiation Model and Its Application to Photovoltaic Assessments , 2004, Trans. GIS.

[42]  Ceridwen Owen,et al.  Outside the square: Integrating wind into urban environments , 2004 .

[43]  Bent Sørensen,et al.  GIS management of solar resource data , 2001 .

[44]  J. Jägermeyr,et al.  Calculation of bright roof-tops for solar PV applications in Dhaka Megacity, Bangladesh , 2010 .

[45]  Manuel Castro,et al.  On the complexity of radiation models for PV energy production calculation , 2008 .

[46]  Ricardo Rüther,et al.  The potential of building-integrated (BIPV) and building-applied photovoltaics (BAPV) in single-family, urban residences at low latitudes in Brazil , 2012 .

[47]  Agis M. Papadopoulos,et al.  Photovoltaics in urban environment: A case study for typical apartment buildings in Greece , 2012 .