haakonwebb/NEPP

NEPP - Norwegian Electricity Price Predictor, is a prediction model using machine learning and statistical data to predict future prices of the electricity in Norway's 5 regions.

NEPP - Norwegian Electricity Price Predictor

NEPP (Norwegian Electricity Price Predictor) is a machine learning-based prediction model that forecasts future electricity prices in Norway's five regions using statistical data and advanced analytics.

Table of Contents

• Project Structure
• Installation
• Usage
• License
• Declaration

Project Structure

Here's a brief overview of the project's file structure:

Portfolio_Elec_Model/
│
├── data/
│ ├── raw/ # Raw data storage
│ └── processed/ # Processed data
│ ├── cleaned/ # Cleaned data
│ ├── normalized/ # Normalized data
│ └── preprocessed/ # Preprocessed data
│
├── src/
│ ├── init.py # Initialization script
│ ├── config.py # Configuration settings
│ ├── data_cleaner.py # Data cleaning script
│ ├── data_fetcher.py # Data fetching script
│ ├── data_loader.py # Data loading script
│ ├── data_normalizer.py # Data normalization script
│ ├── data_preprocessor.py# Data preprocessing script
│ ├── data_processing_tracker.py # Data processing tracking
│ ├── main.py # Main script for running the project
│ ├── model.py # Model definition
│ ├── visualize_and_predict.py # Visualization and Prediction script
│ ├── train.py # Model training script
│ └── utils.py # Utility functions
│
├── outputs/
│ ├── models/ # Model storage
│ └── figures/ # Generated figures and plots
│
├── tests/
│ └── test_data_preprocessor.py # Data processing tests
│
├── .env # Environment variables
├── .gitignore # Git ignore file
├── LICENSE # License details
├── README.md # Project overview (this file)
└── requirements.txt # Project dependencies

Installation

To set up the NEPP project on your local machine, follow these steps:

1. Clone the Repository:

git clone https://github.com/haakonwebb/NEPP.git
cd Portfolio_Elec_Model

2. Create and Activate a Virtual Environment (Optional but Recommended):

python -m venv venv
source venv/bin/activate # For Windows use venv\Scripts\activate

3. Install Dependencies:

pip install -r requirements.txt

Or run init.py

4. Environment Variables:

• Create your .env file.

touch .env

• Add enviroment variable ot the '.env' file.

ENTSOE_API_KEY=your_entsoe_api_key_here

• Applying for an API key can be done by following this doucment: Entsoe API Token Management

Usage

To run the NEPP project, follow these steps:

1. Initialize the Project:

• Run python src/__init__.py to create the necessary folder structure and install dependencies.

2. Data Fetching and Processing:

• Execute the data fetching, preprocessing, cleaning, and normalization scripts.

3. Model Training:

• Run the training script with the necessary parameters.

4. Prediction and Analysis:

• Use the main script or model scripts to perform predictions and analyses.
• A prediction for the next 24 hours should look something like this (note that this is a prototype and the prediction is not functioning correctly)

License

This project is licensed under the GNU GPLv3. See the LICENSE file for more details.

Declaration

• Most of the code is produced by GPT-4.
• Resource used for theory: A Machine Learning Approach for future electricity price prediction