guiSmo: Guidelines for CSP performance modeling – present status of the SolarPACES Task-1 project

Due to the high capacity of solar thermal power plants (50 MWel and more) and large required investment, concentrating solar power (CSP) projects are subject to an extensive project development process. Predicting the energy yield of a CSP plant is a crucial task in this process. Mathematical models predicting the system’s energy yield are required to assess single CSP projects (e.g. feasibility or due diligence studies), compare different plant options (e.g. technology, site), optimise technology configuration (e.g. solar field size, storage capacity), investigate the influence of component characteristics (e.g. receiver characteristics), and to assess system performance during commissioning, among other things. The models used for these tasks differ in complexity and required accuracy, e.g. a model used for project assessment during commissioning has to be more rigorous than a model used for a pre-feasibility study. At the moment, numerous modelling approaches exist, and project developers use their own internal system models and assessment methodology. These models often lack validation, and no standard or benchmark for comparison yet exists for electricity yield analysis of CSP plants. In addition, most current models of CSP system performance do not treat uncertainties inherent in parameters and processes of the complex system. These conditions may fail to alleviate concerns about technology risk and hinder the acceptance of CSP technology by potential investors. To solve this problem, an international working group is being initiated within SolarPACES Task I to define guidelines for performance prediction of CSP plants. This working group started in 2010 with the definition of a structural framework for the performance prediction. In parallel, several partners have performed a benchmarking of their performance models. At the end of this benchmarking process a work-shop was held to discuss the results of the benchmarking and to identify the major effects to be considered for the performance prediction of parabolic trough solar thermal power plants. This paper presents the major effects identified so far.