This project analyzes the capital expenditure (CAPEX) and profitability of European offshore wind farms. It provides a data processing pipeline, a predictive model for CAPEX / MW, a farms similarity analysis engine, and an interactive web-based UI for visualizing the results.
- Data Preprocessing: Cleans, enriches, and prepares raw data for analysis.
- Profitability Calculation: Calculates key financial metrics for wind farm projects.
- Predictive Modeling: Trains a model to predict CAPEX / MW for new projects.
- Similarity Analysis: Determines the similarity between farms.
- Interactive Dashboard: A Streamlit-based user interface to explore the data and model predictions.
- Profitability Map: Visualizes the profitability of wind farms on a map of Europe.
- Similarity Table: Summarizes the farms that are most similar to the one proposed.
Install Python 3.12.0 and the required dependencies:
pip install -r src2/requirements.txtTo run the full pipeline, execute the main.py script:
py -m src2.mainThis will launch the Streamlit application in your web browser.
Data Preprocessing and Profitability Calculation stages run only if there are no cleaned_european_offshore_wind_capex.csv and calculated_offshore_wind_data.csv files in /data folder.
It prevents overwriting the existing data and allows to save time when you want to quickly test changes in the UI or model. If you want to re-run the preprocessing or calculations, simply delete the corresponding files from the /data folder.
The project's configuration is managed in the src2/config.py file. This file contains constants for data paths, model parameters, and other settings.