A photovoltaic power output dataset: Multi-source photovoltaic power output dataset with Python toolkit. (December 2021)

• Record Type: Journal Article
• Authors: Yao, Tiechui; Wang, Jue; Wu, Haoyan; Zhang, Pei; Li, Shigang; Wang, Yangang; Chi, Xuebin; Shi, Min
• Is Part Of: Solar energy. Volume 230(2021)
• Page Start: 122
• Page End: 130
• Publication Date: 2021-12
• Subjects: Photovoltaic power output dataset -- Open source -- Python toolkit -- Data article; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2021.09.050
• Languages: English
• ISSNs: 0038-092X

Abstract

Abstract: The power output of photovoltaic (PV) systems is chiefly affected by climate and weather conditions. In that, PV farm requires accurate weather data, particularly, solar irradiance, in order to predict its power output as a means to improve solar energy utilization. Nevertheless, publicly available datasets which consist both power and weather data are exceptionally few. This may be a combined effect of data propriety and cumbersome collection procedure. And the rarity of such data greatly hinders the progress of solar PV research. Indeed, most solar energy meteorology applications, such as solar forecasting or PV performance evaluation, can benefit from multi-source high-quality datasets. In view of that, we release a PV power output dataset (PVOD), which contains metadata, numerical weather prediction data, and local measurements data from 10 PV systems located in China. In PVOD, a Python toolkit with basic functions for data access and preprocessing is provided. Additionally, a case study on PV power output estimation is depicted to demonstrate the potential usage of the dataset. Highlights: A publicly available dataset named photovoltaic power output dataset (PVOD). A simple and extensible Python toolkit for PVOD. A PV power output modeling example based on PVOD and Python toolkit.