Skip to main content

A meta-package including core, heatpump, tespy, reno, sites and ecommunity

Project description

BATEM Tutorial

Welcome to the BATEM tutorial. This guide will help you learn about different aspects of energy management through hands-on exercises using Python and Jupyter notebooks.

Overview

This tutorial consists of:

  • Interactive Jupyter notebooks (named notebookx_XXX.ipynb)
  • Lecture slides (named slidesx_XXX.pdf)

Getting Started

Access the MyBinder project to start the tutorial.

Depending on your internet connection, you may have to wait a few minutes to start the tutorial.

Important:

  • If you are unable to access the MyBinder environment, you can download the project files and run the notebooks locally.
  • To do this, you need to go through the following steps:

Local Installation Guide

  1. Install Python

    • Download Python from python.org
    • Choose the latest Python 3.x version
    • During installation, make sure to check "Add Python to PATH"
    • Verify installation by opening a terminal and typing (PowerShell in Windows, Terminal in macOS/Linux):
      python --version
      
  2. Install Visual Studio Code

    • Download VS Code from code.visualstudio.com
    • Install VS Code following the default installation steps
    • Open VS Code and install the following extensions:
      • "Python" by Microsoft
      • "Jupyter" by Microsoft
  3. Set up the Python Environment

    • Open a terminal in VS Code (Terminal -> New Terminal)
    • Create a new virtual environment:
      python -m venv venv
      
    • Activate the virtual environment:
      • On Windows:
        .\venv\Scripts\activate
        
      • On macOS/Linux:
        source venv/bin/activate
        
    • Install required packages:
      pip install -r requirements.txt
      
  4. Run the Notebooks

    • Open the project folder in VS Code
    • Open any .ipynb file
    • Select the Python interpreter (venv) when prompted
    • Follow the notebook

Working with MyBinder

The MyBinder window should look like this:

There are three main instruments to work with:

  • The project files, accesible from the left panel (Project Structure)
  • The command bar, at the top of the window (Command Bar)
  • The working area, in the middle of the window (Working window)

Following the tutorial

We recommend to follow the tutorial in the following order:

  • Go thorugh the slides for a subject first (slidesXX_XXX.md)
  • Open the corresponding notebook (notebookXX_XXX.ipynb)
    • Solve the exercises in the notebook by writing your replies in a separate document with the references to the questions and exercises.
    • You can check the slides to get the information you need to solve the exercises
  • After finishing the exercises on a notebook, upload the responses to the course platform.

Working with Notebooks

To open any notebook, double-click the corsponding .ipynb file.

Notebook Basics

Notebooks contain two types of cells, as described bellow:

  1. Text Cells (for reading and writing):

    • Double-click to edit
    • Press 'Shift+Enter' to execute the cell and display the text
    • Press 'Ctrl+S' to save the notebook
  2. Code Cells (for running Python):

    • Click the Run (▶️) button to run the cell
    • Alternatively, use the "Restart and run all" (▶️▶️) button in the top menu to run all the cells in the notebook

Notebooks in VS Code

If you are using VS Code and work with the notebooks locally on your machine, your notebook looks like this:

To run a cell, you can either:

  • Click the Run (▶️) button
  • Use the 'Shift+Enter' shortcut

To run all the cells in the notebook, you can either:

  • Click the "Restart" button in the top menu
  • Click the Run All button in the top menu

Working with Plots

The interactive plots typically show evolution of parmaeters (such as power consumption) over time:

  • View Specific Legend Item (for example an appliance): Double-click items in the legend
  • Zoom In: Click and drag a rectangle on the plot
  • Zoom Out: Click "Autoscale" in the top-right corner of the plot
  • View Details: Hover over lines to see line-specific information

For example, hovering over a line in the power consumption plot will show the weather temperature in function of the time.

Evaluation

You will be evaluated based on the answers you provide to the questions and exercises in the notebooks.

We strongly recommend you to put your answers on a separate document (word, pdf, txt, etc.) and provide clear references to the question numbers.

After you have your document ready, you can upload it to the course platform.

Example:

In the notebook: Section I. Sun Question 1. Calculated solar radiations vs measurements Section I., Question 1: (your answer here)

In the separate document: Section I., Question 1: (your answer here)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

batem-0.1.11.tar.gz (450.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

batem-0.1.11-py3-none-any.whl (621.8 kB view details)

Uploaded Python 3

File details

Details for the file batem-0.1.11.tar.gz.

File metadata

  • Download URL: batem-0.1.11.tar.gz
  • Upload date:
  • Size: 450.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.9

File hashes

Hashes for batem-0.1.11.tar.gz
Algorithm Hash digest
SHA256 60b71944da62c9ce10d2e5c2774d821ce3f3a69f3d1faac28ffd552c91416155
MD5 2fa62f743be7f2b8f89cbf4d3e17b072
BLAKE2b-256 a064c2005a631a84dfff4610583437da81fb1c11713596ba2f91524e685f7ad8

See more details on using hashes here.

File details

Details for the file batem-0.1.11-py3-none-any.whl.

File metadata

  • Download URL: batem-0.1.11-py3-none-any.whl
  • Upload date:
  • Size: 621.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.9

File hashes

Hashes for batem-0.1.11-py3-none-any.whl
Algorithm Hash digest
SHA256 2db4c12538b7d6bedbe1bb8f8953cd41594a861c01235fa257e435a62e35b8ec
MD5 cdf37db22300404eee5fb572f5f7b945
BLAKE2b-256 c7fda1f68bfd4cd3795bb2fb15e0933dbe60935d732e0000db4ddb0d65e0af37

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page