Solar power datset

Instructions for Dataset Utilization:

1. Download the Dataset

   • The dataset is available in CSV format. To download, click on the link provided in the Data Availability Statement. The file can be opened in spreadsheet software (e.g., Microsoft Excel) or used in Python (via Pandas) or R for data analysis.

2. Dataset Overview

   • The dataset contains multiple columns including:

     • Year: The year of data collection.

     • Julian Day: The day of the year (1–365/366).

     • Day Length (seconds): The total daylight duration in seconds.

     • Precipitation (mm): Precipitation levels recorded in millimeters.

     • Solar Radiation (Langley): Solar radiation in Langley.

     • Snow Water Equivalent (mm): Snow water equivalent.

     • Temperature: Maximum and minimum temperatures in Celsius.

     • Vapor Pressure (Pa): Atmospheric vapor pressure in Pascals.

3. Data Preprocessing

   • Before using the dataset, ensure that all missing or outlier data points are addressed. You may need to:

     • Handle missing values either by interpolation or imputation.

     • Normalize or standardize the data depending on your analysis needs.

4. Application

   • The dataset can be used for:

     • Solar Power Forecasting: Build predictive models for solar energy generation based on weather and solar radiation.

     • Climate Analysis: Study how temperature, precipitation, and solar radiation correlate with each other and affect solar power production.

     • Weather Impact Studies: Understand the role of daily and seasonal weather patterns in renewable energy forecasting.

5. Software Requirements

   • To work with this dataset, you may need data analysis libraries in Python (e.g., Pandas, Matplotlib, Scikit-learn) or R for statistical modeling.