Solar and wind power data from the Chinese State Grid Renewable Energy Generation Forecasting Competition.

ABSTRACT: 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. 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. Over two years (2019-2020), power generation and weather-related data were collected at 15-minute intervals. The dataset was used in the Renewable Energy Generation

SUBMITTER: Chen Y 

PROVIDER: S-EPMC9492786 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature