https://github.com/paulhex6/wind-turbine

Analysis of wind turbine data for a given location
https://github.com/paulhex6/wind-turbine

climate climate-data energy-analysis open-meteo-api renewable-energy renewables streamlit wind wind-turbine windturbine

Last synced: about 1 month ago
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Analysis of wind turbine data for a given location

• Host: GitHub
• URL: https://github.com/paulhex6/wind-turbine
• Owner: PaulHex6
• Created: 2024-08-09T16:00:04.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-08-20T15:42:56.000Z (almost 2 years ago)
• Last Synced: 2025-07-07T19:53:35.437Z (12 months ago)
• Topics: climate, climate-data, energy-analysis, open-meteo-api, renewable-energy, renewables, streamlit, wind, wind-turbine, windturbine
• Language: Python
• Homepage:
• Size: 27.3 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

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README

          
# ⚡ Wind Turbine Analysis Tool

![Python](https://img.shields.io/badge/Python-3.8%2B-blue)

![Streamlit](https://img.shields.io/badge/Streamlit-1.0%2B-red)

![License](https://img.shields.io/badge/License-Apache%202.0-green)

## Overview

A Python-based Streamlit application for wind energy analysis. This renewable energy tool calculates potential energy generation from historical wind data, provides climate analysis, and visualizes results with interactive graphs.

Live demo [![Open in Streamlit](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://wind-turbine.streamlit.app)

## Features

- **Address-Based Location Selection**: Input an address, and the app automatically fetches the corresponding latitude and longitude.

- **Wind Data Retrieval**: Retrieves historical daily wind speed and gust data from the Open-Meteo API.

- **Wind Turbine Energy Calculation**: Estimates the total energy generation of a wind turbine based on the wind data and turbine specifications.

- **Interactive Graphs**: Visualize daily wind speed and gust data with Plotly, including indicators for exceeding the turbine's maximum wind speed.

- **Performance Metrics**: Compare the wind data to average values and assess the turbine's performance.

## Installation

1. **Clone the repository**:

    ```bash

    git clone https://github.com/your-username/wind-turbine-analysis.git

    cd wind-turbine-analysis

    ```

2. **Install the required dependencies**:

    ```bash

    pip install -r requirements.txt

    ```

3. **Run the application**:

    ```bash

    streamlit run main.py

    ```

## Usage

1. **Set Wind Turbine Parameters**:

    - Adjust the start wind speed, max wind speed, rated wind speed, and rated power from the sidebar.

2. **Enter Location and Date Range**:

    - Input the address (e.g., "Warszawa, Aleje Jerozolimskie") and select the start and end dates for your analysis.

3. **Fetch Data**:

    - Click "Fetch Data" to retrieve the wind data and automatically calculate the energy generated by the wind turbine.

4. **View Results**:

    - The daily wind data is visualized on an interactive graph.

    - Performance metrics such as total energy generated, max wind speed, average wind speed, and minimum speed are displayed in the analysis section.

## Dependencies

- `streamlit`: Web app framework for data science.

- `pandas`: Data analysis and manipulation tool.

- `numpy`: Numerical computing package.

- `requests`: HTTP library for Python.

- `geopy`: Geocoding library to convert addresses into latitude and longitude.

- `plotly`: Interactive graphing library.

- `xlsxwriter`: Saving data to Excel sheet.

## API

This application uses the [Open-Meteo API](https://open-meteo.com/) to fetch historical wind data.