1. Description of Work (2011)

 


© SAM/NREL

Definition and objective: the service is entitled “generation of highly spatially-resolved Typical Meteorological Year (TMY) data sets for the design and the performance assessment of complex solar energy based systems for electricity production”. It will generate TMYs by exploiting the service “local atlases”. It will add the air humidity parameter to the existing databases of irradiance and air temperature, and possibly wind speed if requested and possible.

The product is a solar energy-related TMY. A TMY is a series of meteorological values, typically one per hour, covering one full year. It is a synthesis of the meteorological situation of a past period spanning over several years, typically 10. It is made of observed values, and not averages for instance, which are selected according to specifications by user. For instance, a TMY may represent the median situation or the worst situation with respect to energy production.

The product is a highly spatially-resolved Typical Meteorological Year (TMY) data set for the design and the performance assessment of complex or not, solar energy-based systems for electricity production.

Actually, several products TMYs will be made in a first step to be gauged by prime-users, following two categories and two sets of meteorological parameters. One category will be made of median situations, i.e., the typical situation encountered during a period of several years; the second category will be made of pessimistic situations, i.e. a representative of the worst situations encountered in this period. By running simulations with both TMYs, users would obtain a range of performances: median, and worst cases.

Two sets of meteorological parameters will be produced: one with radiation only, one with other parameters such as ambient temperature or wind speed.

Usage of a TMY: An accurate assessment of the value of the utility electricity generation (UEG) in the early stages of a large investment project is very important since this figure is the basis of many other calculations that define the profitability of this project and therefore the “go-no-go” decision made by banks and investors.

Involved partners and contacts:

  • Partner in charge of the development of the product: ARMINES - Philippe Blanc (philippe.blanc(-at-)mines-paristech.fr) and Bella Espinar (bella.espinar(-at-)mines-paristech.fr)
  • Partner in charge of the development of the service: TRANSVALOR - Laurent Saboret (laurent.saboret(-at-)transvalor.com), Etienne Wey (etienne.wey(-at-)transvalor.com) and Claire Thomas (claire.thomas(-at-)transvalor.com).

Prime-users:

  • A consultant in Solar Energy, Mr. Dominique Clément
  • A large company in Energy (Total)

Expectations of the prime-users:

  • Parameters: irradiance (1), air temperature (2), wind speed (3) and air humidity (4),
  • Accuracy: rmse < 25 % (1), rmse < 4 °C (2), rmse < 5 m/s (3), rmse < 20 % (4),
  • Space resolution: 2 km (for all),
  • Time resolution: hour (for all),
  • Time coverage: preferably more than 15 years (for all),
  • Product format: Excel file, or CSV format. One line per hour. Date: format ISO-19115 (YYYY-MM-DDThh:mm:ss) or year month, day, decimal hour,
  • Product availability: less than 1 day after request to the SoDa Service,
  • Metadata: the geographical location of the time series, temporal description, content, units, provider, intellectual property rights and lineage, quality.

Area of interest: the targeted geographical area for these products in the initial phase is the Provence region in France.

 

State-of-the-art: One important point is that the energy companies and banks have agreed to use typical meteorological years (TMY) data sets rather than complete data sets spanning over 10-15 years as inputs to the model.

The current TMYs have two drawbacks. Either they are complete, i.e., including irradiance, air temperature, air humidity and wind speed, but are very few with gaps in space. Or they are incomplete, e.g., only global irradiance, but are more numerous.

TMY3 is both a method and a format of TMY. It is described here: "Users Manual for TMY3 Data Sets" - emails from Chalmers University.

The starting point of the method developed within the framework of ENDORSE is Kalogirou, 2003. Renewable Energy 28 (2003) 2317-2334.

Exploited GMES downstream services:

  • The solar radiation database HelioClim3
  • The national networks of weather stations such as Meteofrance

Expected Innovation: The main innovations of this service are:

  • to offer complete TMY for virtually any location.
  • to propose TMY tailored to users's needs.
  • to standardise the process and the definition of a modular content in order to ensure the replicability of the service.