Research Paper
Reducing Solar Project Uncertainty with an Optimized Resource Assessment Tuning Methodology
The use of satellite data for energy estimates has become more prevalent in the solar industry, and is often combined with ground data to remove local and seasonal biases, and lower the uncertainty. Determining the uncertainty of the final dataset can be challenging, however, as traditional statistical uncertainty and error calculation methods have proven to be unrepresentative.
This paper describes procedures suitable for the optimal combination of ground-based and satellite-based irradiance data to reduce the overall uncertainty of the solar resource assessment. It presents a case study depicting the application of these approaches, and illustrates the benefits of proper solar resource tuning methods to ensure the production of a robust solar resource dataset.
This paper describes procedures suitable for the optimal combination of ground-based and satellite-based irradiance data to reduce the overall uncertainty of the solar resource assessment. It presents a case study depicting the application of these approaches, and illustrates the benefits of proper solar resource tuning methods to ensure the production of a robust solar resource dataset.
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