Benchmarking of five typical Meteorological year Datasets dedicated to Concentrated-PV Systems

Significance Statement

Accurate analysis of meteorological and pyranometric data for long-term prediction is the basis of the conception and development, so as decision-making for banks and investors, regarding solar energy conversion systems, either photovoltaic (PV) concentrated solar power (CSP) or concentrated photovoltaic (CPV). This has led to the development of methodologies for the generation of Typical Meteorological Years (TMY). A TMY is a customized weather dataset of one-year of meteorological data that aims at representing climatic conditions judged to be typical over a long-term period. A TMY dataset has 12 calendar months. The most representative block of monthly data for each calendar month is selected based on the smallest Filkenstein-Schafer distance measuring the difference of two cumulative distribution functions.

The “standard” method for solar energy conversion systems was proposed in 1978 by the Sandia Laboratory. In 2012, a new approach was proposed in the framework of the European project FP7 ENDORSE introducing the concept of “driver” time series defined by the user as a function of the pyranometric and meteorological relevant variables to improve the representativeness of the TMY datasets with respect the specific solar energy conversion system of interest.

Ana M. Realpe and colleagues from SOLAÏS, MINES ParisTech and NEOEN, in France benchmarked the classical Sandia method of TMY generation with innovative methods based on the driver concept, in the particular case of a given CPV system in a given site. The research work is now published in Energy Procedia.

According to the team, using 18-year data of the meteorological station Desert Rock (United States), five types of TMY were created using hourly and 1-minute data. The construction of the meteorological year is achieved by comparing the CDF of each block of data at a given month to the CDF of the concatenation of all blocks of data for this month over the long-term. The energy generation output of the concentrated photovoltaic system over the long-term 18-years period was the quantity used for the comparison between the different TMY datasets. The team used a simulation tool for each TMY as input to determine the yield of the concentrated photovoltaic system. Then two analyses were performed: one comparing the long-term average yield with the yield associated to the TMY datasets and another comparing the corresponding CDFs using the Kolmogorov-Smirnov test Integral parameter (KSI), in order to measure the distance between two cumulative distribution functions.

The team found out that the monthly results obtained from the drivers, with hourly and 1-min data, are significantly better than those obtained with the Sandia method. The maximum annual deviations obtained with the Sandia method and with the drivers have no consistent pattern. From the monthly KSI test, the team observed that the maximum monthly deviations from the Sandia method approach exceed twice the deviations obtained by the drivers. Considering the annual KSI, the simplified and filtered drivers provide relative KSI values systematically less than 45 % from 8-year data.

Researchers were able to compare the innovative method which is based on driver concept, by using classical Sandia method as reference point. They found the driver concept to be more promising and efficient than the classical Sandia method.

Benchmarking of five typical Meteorological year Datasets dedicated to Concentrated-PV Systems - Renewable energy global innovations

About the author

Ana Maria Realpe received her degree in Electrical Engineering from the Simon Bolivar University of Venezuela, in 2009. She carried out her research internship in the Fraunhofer Institute of Solar Energy in Germany, about the development of an encapsulation technique for Compact Concentrated Modules (CCM) used in high concentration photovoltaic (HCPV) systems. In 2011, she received her European Master’s degree in renewable energies (EUREC) from the Ecole MINES ParisTech in France, with a specialisation in hybrid systems at the Kassel University in Germany.

She joined SOLAÏS in 2012 where she has been continuously working in research and development projects with close collaboration with ARMINES / MINES ParisTech on various topics so as material assessment, mechanical structures and aerodynamic studies and solar resource analysis.

She is responsible of the innovation in SOLAÏS and leads the R&D activities related to the glare problematics regarding PV projects that may jeopardize the transportation safety (airports, networks of railways and motorways).

About the author

Sébastien Pitaval is graduated from Ecole Nationale Supérieure d’Electrotechnique, d’Electronique, d’Informatique, d’Hydraulique et de Télécommunications (2000, Toulouse, France), with specialization in fluid mechanics and energy. He started his career working in the space industry, for Alcatel Space Industries then Thalès Alenia Space (2000-2008), occupying successive management positions for Herschel and Planck satellites: propelling system, Attitude and Orbit Control Systems (AOCS) then system integration.

His interest and convictions regarding renewable energies and his entrepreneurial spirit led him to co-create SOLAÏS in 2008. He developed R&D, Engineering and Export activities while setting up Corporate Social Responsability (CSR) within the company. He is also judicial expert at the Court of Appeal of Aix-en-Provence (France).

About the author

Christophe Vernay is graduated from Ecole Supélec (1997), a general engineering school in France. He started his career by working in the space industry, for Alcatel Space Industries (1998-2001), as a Research Engineer in Attitude and Orbit Control Systems (AOCS). Then, he worked in the Telecom industry for Nortel Networks then Alcatel-Lucent (2001-2010) on several positions, from the integration to the engineering of 3G and 4G systems. His interest and convictions regarding renewable energies led him to attend photovoltaic and wind-power courses in 2010 at the Conservatoire national des arts et métiers (CNAM), Paris. In 2011, he post-graduated from Ecole Nationale Supérieure d’Arts et Métiers (ENSAM) with a specialized Master’s Degree in renewable energy.

He carried out its professional thesis in SOLAÏS, a French consulting company dedicated to photovoltaic, in collaboration with MINES ParisTech / Armines, about the characterizing of the measurements campaigns of the global irradiation. Since then, he is Technical Director in SOLAÏS, in charge of R&D, engineering, technical due diligence and commissioning.

Linkedin with publications 

About the author

Prof. Philippe BLANC is graduated from the engineering school Telecom Bretagne (Ecole Nationale Supérieure de Télécommunications de Bretagne) and received his PhD degree from the MINES ParisTech in 1999 in the field of engineering sciences and applied mathematics. He has been working as a research engineer for Thales Alenia Space in signal and image processing and data fusion for Earth Observation systems and various projects where scientific support in signal and image processing, statistics, algorithmic prototyping and applied mathematics is required. He joined ARMINES / MINES ParisTech in 2007. He is working on the modelling of solar radiation and its assessment from in situ measurements or/and satellite images.

He is the head of the research group involved in renewable energy resource assessment within the research center Observation, Impacts, Energy. He has passed in 2015 his professoral habilitation (Habilitation à Diriger des Recherches) and is Professor at MINES ParisTech since then. In addition, he is currently a sub-task Leader of the Task 16 of the International Energy Agency program PVPS and associate editor for the Elsevier journal Solar Energy of the International Solar Energy Society (ISES).

Online access to publications 


Ana M. Realpe1, Christophe Vernay1, Sébastien Pitaval1, Camille Lenoir2, Philippe Blanc3, Benchmarking of five typical Meteorological year Datasets dedicated to Concentrated-PV Systems, Energy Procedia 97 ( 2016 ) 108 – 115.

Show Affiliations
  1. SOLAÏS, 400 avenue Roumanille, BP 309, F-06906 Sophia Antipolis Cedex, France.
  2. NEOEN, 4 rue Euler, 75008 Paris, France.
  3. MINES ParisTech, PSL Resear University, O.I.E. – Center of Observation, Impacts, Energy, 1 Rue Claude Daunesse, CS 10207, F-06904 Sophia Antipolis Cedex, France.


Go To Energy Procedia

Check Also


Bio-Inspired Modeling for H2 Production