📈 Turkey 2024 Electricity Prediction Using Ridge Regression, Random Forest, and XGBoost

(Turkey, From 2016–2023 electricity consumption data to predict 2024 consumption)

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📌 Objective

Build a forecasting model for Turkey’s total electricity load (MWh) in 2024 using classical, interpretable machine-learning algorithms.

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🧾 Data Overview

• Source: EPİAŞ – Enerji Piyasaları İşletme A.Ş.
• File: bileşik_tüketim.csv
• Time Range: 01.01.2016 to 31.12.2024
• Granularity: Hourly electricity consumption data

📁 Files in This Project

• electricity_forecasting_notebook_with_report.ipynb — Main notebook
• elec_daily_preprocessed.csv — Preprocessed daily data
• bileşik_tüketim.csv — Raw hourly consumption dataset

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🔧 Future Work

• Incorporate weather data (temperature, humidity, etc.)
• Try time series-specific models (e.g., ARIMA, Prophet)
• Deploy as an API or web app for public electricity prediction

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👤 Author

Egehan Vardar
Email: egehanvardar@gmail.com