Time Series and TMY data

How is a TMY dataset prepared?

Modified on: Tue, 17 Jan, 2017 at 16:02

The key concept of a TMY dataset is the reduction of several years of data to one representative year. In the Solargis method of preparing TMY data, we select 12 most representative months to create a typical year. The choice of representative months is made with the following objectives:

  1. The annual and monthly sums of the TMY data should be similar to the long-term averages calculated from multi-year time series data.
  2. The distribution of values should be preserved
  3. Consistency of all parameters in data file must be maintained
  4. Adequate weighting must be given to most relevant parameter when deciding on the similarity of statistical characteristics. For example, when preparing TMY data for PV applications - maximum focus is to preserve monthly average and distribution of Global Horizontal Irradiance values. Whereas when preparing TMY data for CSP applications, the maximum focus is on preserving monthly average and distribution of Direct Normal Irradiance values.

To learn more details about various methods of preparing TMY data, and about criteria for preparing TMY data for different probability scenarios (P50, P90, Pxx..) please refer to the following presentation:

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