Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S

• Published in: Applied energy 2025-01, Vol.377, p.124698, Article 124698
• Main Authors: Zeng, Zhaoyun, Stackhouse, Paul, Kim, Ji-Hyun (Jeannie), Muehleisen, Ralph T.
• Format: Article
• Language: English
• Subjects: NASA POWER; Photovoltaic system; Renewable energy; System advisor model; Typical meteorological year; Weather data; Wind turbine
• ISSN: 0306-2619
• DOI: 10.1016/j.apenergy.2024.124698

Weather data plays a critical role in renewable energy analysis. Compared to using multiple Actual Meteorological Years, simulations using a single typical year require significantly fewer computational resources. Previous efforts to create typical weather datasets for renewable energy analysis either lack justified or optimized strategies for selecting and weighting different weather parameters or are limited to a few specific locations. In this study, we developed a dataset comprising Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for over 2000 locations across the U.S., based on data from NASA's POWER project. The strategies for creating TSYs and TWYs were optimized based on the simulated outputs of various PV systems and wind turbines in 16 representative cities. This dataset provides an efficient means for the rapid evaluation and optimization of renewable energy systems throughout the entire U.S. Additionally, the optimal strategies identified in this study can be directly applied to create near-optimal TSYs and TWYs for most locations worldwide. However, readers can also employ the optimization approach presented in this work to develop optimal strategies tailored for particular regions. •Typical Solar Years and Typical Wind Years are created for the entire U.S.•The solar and meteorological data are sourced from NASA's POWER project.•This dataset provides an efficient means for evaluating renewable energy systems.•The generation methods are optimized based on renewable energy system simulations.•The generation method can be applied to other regions worldwide.