SC²S Colloquium - December 17, 2009

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Date: December 3
Room: 02.07.023
Time: 14:00 pm, s.t.

Sergey Matushkin: Sensitivity and Uncertainty analysis for PV systems

The main source of all renewable energy plants is nature factors, for the PV plants it is sun irradiation, which gives the output energy. Reliable energy yield predictions play an essential role during planning and design of (large scale) photovoltaic systems, as they form the basis of many economical and technical decisions. Therefore it is very important to understand the uncertainty of inputs and model parameters entering into energy yield predictions and their effect on the prediction result and try to avoid or reduce artificial error made during computational process. The uncertainties can greatly change the output energy and to lead to wrong economical decision, so this is in great interest to understand the limitation of the difference between predicted energy yield and real one.

For this propose in this work I'll concentrate on:

- most important weather factors (irradiance and temperature) variances and estimations

- models for energy yield predictions and technical uncertainties(PV module)

- data processing of input data(binning process, averaging process)

- sensitivity and uncertainty analyses methods