Wind and solar power generation dataset

This dataset contains time-series data for analyzing and predicting wind and solar power generation. The data comes from wind farms and photovoltaic power plants in a certain location, covering detailed meteorological and power generation data for multiple quarters.

Dataset Usage:

Power generation prediction: This dataset can be used to train and evaluate machine learning models, especially deep learning models, to improve the prediction accuracy of wind and solar power generation.

Renewable energy management: helps optimize the scheduling of wind and solar power generation and improve the stability of grid connection.

Research analysis: Support academic research on the impact of meteorological conditions on renewable energy generation, and help understand the relationship between seasonal changes and power generation performance.

Content description:

Wind power data:

Input features: wind speed, air density, etc.
Output variable: Wind power generation.
Data frequency: recorded every hour.
Photovoltaic data:

Input features: temperature, humidity, ground irradiance, atmospheric irradiance, etc.
Output variable: photovoltaic power generation.
Data frequency: recorded every hour.