Considering Uncertainties in Research by Probabilistic Modeling

Abstract

Technical and economical evaluation of solar thermal power plants constantly gains more importance for industry and research. The reliability of the results highly depends on the assumptions made for the applied parameters. Reducing a power plant system to one single, deterministic number for evaluation, like the levelized cost of electricity (LCOE), might end in misleading results. Probabilistic approaches can help to better evaluate systems [1] and scenarios [2]. While industry looks for safety in investment and profitability, research is predominantly interested in the evaluation of concepts and the identification of promising new approaches. Especially for research, dealing with higher and hardly quantifiable uncertainties, it is desirable to get a detailed view of the system and its main influences. However, to get there, also a good knowledge on the stochastic interrelations and its interpretation is required. Therefore, this paper mainly assesses the influences of basic stochastic assumptions and suggests a methodology to consider suitable stochastic input, especially for parameters of systems still under research. As examples, the comparison between a parabolic trough plant with synthetic oil and direct steam generation is used.