Methodology for Constructing Reduced-Order Power Block Performance Models for CSP Applications: Preprint

The inherent variability of the solar resource presents a unique challenge for CSP systems. Incident solar irradiation can fluctuate widely over a short time scale, but plant performance must be assessed for long time periods. As a result, annual simulations with hourly (or sub-hourly) timesteps are the norm in CSP analysis. A highly detailed power cycle model provides accuracy but tends tosuffer from prohibitively long run-times; alternatively, simplified empirical models can run quickly but don?t always provide enough information, accuracy, or flexibility for the modeler. The ideal model for feasibility-level analysis incorporates both the detail and accuracy of a first-principle model with the low computational load of a regression model. The work presented in this paperproposes a methodology for organizing and extracting information from the performance output of a detailed model, then using it to develop a flexible reduced-order regression model in a systematic and structured way. A similar but less generalized approach for characterizing power cycle performance and a reduced-order modeling methodology for CFD analysis of heat transfer from electronic deviceshave been presented. This paper builds on these publications and the non-dimensional approach originally described.