光伏系统
Python(编程语言)
计算机科学
太阳辐照度
预处理器
元数据
太阳能
太阳能
环境科学
气象学
功率(物理)
可靠性工程
电气工程
人工智能
工程类
物理
操作系统
量子力学
作者
Tiechui Yao,Jue Wang,Haoyan Wu,Pei Zhang,Shigang Li,Yangang Wang,Xuebin Chi,Min Shi
出处
期刊:Solar Energy
[Elsevier BV]
日期:2021-10-18
卷期号:230: 122-130
被引量:32
标识
DOI:10.1016/j.solener.2021.09.050
摘要
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.
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