---
title: TBATS Model for Energy Consumption Prediction
description: >-
  This model predicts energy consumption based on meteorological data and
  historical usage.
license: gpl
---

# TBATS Model for Energy Consumption Prediction

## Description
This TBATS model predicts energy consumption over a 48-hour period based on historical energy usage from 2021 to 2023. It utilizes time series data from a transformer station to forecast future energy demands.

## Model Details
**Model Type:** TBATS (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)  
**Data Period:** 2021-2023  
**Variables Used:**
- `Lastgang`: Energy consumption data

## Features
The model splits the data into training and testing sets, with the last 192 data points (equivalent to 48 hours at 15-minute intervals) designated as the test dataset. The dataset includes preprocessed features such as interpolated and aggregated energy consumption data (`Lastgang`).

## Installation and Execution
To run this model, you need Python along with the following libraries:
- `pandas`
- `tbats`
- `numpy`
- `matplotlib`
- `scikit-learn`

### Steps to Execute the Model:
1. **Install Required Packages**

2. **Load your Data**

3. **Preprocess the data according to the specifications**

4. **Run the Script**