Engineering Papers⌕ Search

DOE OSTI · 1783567

Chapter 15: Summary and Outlook

Abstract

In the various chapters of this book, numerous characterization techniques are presented that can be applied to thin-film solar cells to determine (micro)structural, compositional, electrical, and optoelectronic properties. What has yet to be more fully elucidated is to what extent these characterization techniques can be combined, in a correlative way, to enhance the information gathered on materials and devices. Indeed, it is valuable to consider combining techniques to verify the relevance of the measured materials properties or to obtain them on different length scales-to compare surface with bulk properties, or to correlate structure and composition of materials with electrical and optoelectronic properties.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Abou-Ras, Daniel, Harvey, Steve (ORCID:0000000161207062). 2020-09-01. Chapter 15: Summary and Outlook. https://doi.org/10.1049/pbpo166e_ch15

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Assessment of Cloud Mask Forecasts from the WRF-Solar Ensemble Prediction System: Preprint

Numerical weather prediction (NWP) models are important tools used by government agencies and the renewable energy enterprise to forecast solar radiation. Cloud prediction, a key process of NWP models, has the highest impact on the accuracy of solar forecasting. This study uses satellite observations from the National Solar Radiation Data Base (NSRDB) to evaluate the cloud mask forecast by the WRF-Solar Ensemble Prediction System (WRF-Solar EPS). Preliminary analysis of the data in 2018 demonstrates the need of further improvement in predicting thin and low-level clouds. The information obtained from this work will be used to enhance the WRF-Solar EPS in reproducing the cloud field over the contiguous U.S. and reducing solar forecasting errors.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Evaluating Cell Temperature Models and the Effect of Wind Speed in PV System Capacity Testing: Preprint

Capacity testing is a routine procedure for assessing a photovoltaic system's performance relative to expectations. The most common test method involves fitting a regression model that predicts system output power using operating weather conditions including wind speed. Structural modifications to the regression model to incorporate wind in different ways improved the model's ability to fit measured system performance, but the observed improvements were small and unlikely to change the result of a capacity test. However, the results showed that the choice of reporting wind speed and inclusion or exclusion of wind speed in the performance model used as the test benchmark can significantly change the test result.

41 EE - Solar Energy Technologies Office (EE-4S)↗