Solar and wind generation data from on-site sources are beneficial for the development of data-driven forecasting models. In this paper, an open dataset consisting of data collected from on-site renewable energy stations, including six wind farms and eight solar stations in China, is provided.
Accurate solar and wind generation forecasting along with high renewable energy penetration in power grids throughout the world are crucial to the days-ahead power scheduling of energy systems. It is difficult to precisely forecast on-site power generation due to the intermittency and fluctuation characteristics of solar and wind energy.
Wind power generation data are in the wind_farms folder, which includes six Microsoft Excel files. The real-time power generation and weather conditions are recorded in these files. The basic information about each wind farm is listed in Table 1.
Table 2 describes the meaning of column headings. The nominal solar generation capacity varied from 30 MW to 130 MW, and the average real output ranged from 4.2 MW to 29.8 MW. The statistics of each solar station can be seen in Table 5.
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Learn MoreThis dataset was collected from six wind farms and eight solar stations in China. Based on this approach, solar and wind power forecasting models can be conveniently trained …
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