EMHASS: Energy Management for Home Assistant

Welcome to the documentation of EMHASS. With this package written in Python, you will be able to implement a real Energy Management System for your household. This software was designed to be easily configurable and with a fast integration with Home Assistant: https://www.home-assistant.io/

To get started go ahead and look at the installation procedure and usage instructions below.

Contents:

• Intro / Quick start
  • Introduction
  • What is Energy Management for Home Assistant (EMHASS)?
  • Configuration and Installation
  • Installation Methods
  • Usage
  • Home Assistant Automation
  • The publish-data specificities
  • Passing your own data
  • A naive Model Predictive Controller
  • A machine learning forecaster
  • Development
  • Troubleshooting
  • License
• EMHASS & EMHASS-Add-on differences
  • Legacy Parameter definitions
  • Passing in secret parameters
• An EMS based on Linear Programming
  • Motivation
  • Linear programming
  • Household EMS with LP
  • The EMHASS optimizations
  • References
• The forecast module
  • PV power production forecast
  • Load power forecast
  • Load cost forecast
  • PV production selling price forecast
  • Passing your own forecast data
  • Now/current values in forecasts
  • References
• The machine learning forecaster
  • A basic model fit
  • The predict method
  • The tuning method with Bayesian hyperparameter optimization
  • How does this work?
  • Going further?
• The machine learning regressor
  • A basic model fit
  • The predict method
  • Storing CSV files
• Deferrable load thermal model
  • The thermal model
  • Implementing the model
• Example configurations
  • First test system: a simple system with no PV and two deferrable loads
  • A second test system: a 5kW PV installation and two deferrable loads
  • A third test system: a 5kW PV installation, a 5kWh battery and two deferrable loads
  • Configuration example to pass data at runtime
  • Some real forecast data
• Configuration file
  • Retrieve HASS data configuration
  • Optimization configuration parameters
  • System configuration parameters
• API Reference
  • emhass.command_line module
  • emhass.forecast module
  • emhass.machine_learning_forecaster module
  • emhass.optimization module
  • emhass.retrieve_hass module
  • emhass.utils module
• EMHASS Development
  • Step 1 - Fork
  • Step 2 - Develop
  • Step 3 - Pull request

Indices and tables

• Index

• Module Index

• Search Page