Wind and solar power generation dataset
Description
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.