Solar Power Tower Lifetime Predictions: Lab to Computer and Back Again
Chelsea Harris, University of California, Berkeley
Solar power towers are a way of harnessing solar energy by using specialized mirrors called heliostats to direct sunlight onto a tower, where the light is converted into heat that powers a steam-driven turbine. The quality and lifetime of the heliostats govern the efficiency and profitability of these stations. Heliostat design tries to optimize quantities like the percentage of light reflected, the narrowness of the reflected beam and the time before the heliostat cracks due to stress and composition changes. Unfortunately, monitoring a set of mirrors for decades under realistic desert conditions is impractical for commercial time scales; therefore over the years, laboratory tests of the mirrors under an extreme version of natural conditions have been used to infer the desired quantities. These tests, however, cannot pinpoint precisely the physical reasons for degradation and might not reproduce the composition changes accurately. On the other hand, realistic computer simulations of heliostats in the desert can track the physical processes and assist in commercial heliostat design. The PREDICTS code in development at the National Renewable Energy Laboratory (NREL) does exactly this work, with the goal of tracking the chemical reactions that cause the composition of the heliostats (and therefore their reflective properties) to change over time. My project is to use the code to translate measurable heliostat properties (like reflectance and transmittance) into material properties (index of refraction) in a statistical framework. We can run a large suite of models on Peregrine, the supercomputer at NREL. We also are looking at using the code - along with visualization tools at NREL - to create fun visual models for fundraising and public education purposes.
Abstract Author(s): Chelsea Harris, Ross Larsen, Ray Grout