A new hourly dataset for photovoltaic energy production for the continental USA

Weiming Hu; Guido Cervone; Andre Merzky; Matteo Turilli; Shantenu Jha

doi:10.1016/j.dib.2022.107824

A new hourly dataset for photovoltaic energy production for the continental USA

Data Brief. 2022 Jan 13:40:107824. doi: 10.1016/j.dib.2022.107824. eCollection 2022 Feb.

Authors

Weiming Hu^{1

2}, Guido Cervone^{2

3

4}, Andre Merzky⁵, Matteo Turilli⁵, Shantenu Jha⁵

Affiliations

¹ Scripps Institution of Oceanography, University of California, San Diego, United States.
² Institute for Computational and Data Sciences, The Pennsylvania State University, United States.
³ Earth and Environmental Systems Institute, The Pennsylvania State University, United States.
⁴ Research Application Laboratory, National Center for Atmospheric Research, United States.
⁵ Department of Electrical and Computer Engineering, Rutgers University, United States.

Abstract

This new dataset is an ensemble of solar photovoltaic energy production simulations over the continental US. The simulations are carried out in three steps. First, a weather forecast system is used for the predictions of incoming insolation; then, forecast ensembles with 21 members are generated using the Analog Ensemble technique; finally, each ensemble member is used to simulate 13 different solar panels. In total, there are $21 \times 13 = 273$ simulated scenarios. Simulations are carried out for the entire year 2019, with a temporal resolution of one hour, and a spatial resolution of 12 km. The data provide a high spatio-temporal analysis of the power production under different weather and engineering scenarios. The size of the entire dataset is about 1 TB but can be openly accessed by days and scenarios. Details on how to access and use such a dataset are provided in this article.

Keywords: Distributed computing; Ensemble simulation; Renewable energy; Solar photovoltaic.