EMHASS (Energy Management for Home Assistant) is an MIT-licensed Python module for residential households that optimizes home energy use around electricity prices, solar panel generation, and battery storage, and that interfaces with Home Assistant.

What it is

EMHASS is an optimization tool designed for residential households, written in Python and released under the MIT License, with copyright held by David Hernandez Torres for the 2021–2026 period. It applies a Linear Programming approach to decide how energy should be used across a home, taking electricity prices, power generation from solar panels, and energy storage from batteries as its inputs. The project is published as a Python module, documented at emhass.readthedocs.io, and carries 679 stars, 165 forks, and 50 open issues.

The concrete problem it solves is scheduling. Rather than switching appliances and charging cycles by hand or by fixed rule, EMHASS produces an optimized daily schedule for a household's devices, allowing energy consumption to be shifted toward cheaper or cleaner moments. It replaces the manual or ad-hoc logic a Home Assistant user would otherwise write to decide when a battery charges, when a load runs, and how solar production is spent. Its topics place it squarely in home-automation and energy management, with linear-programming, optimization, and model-predictive-control named as the methods involved.

Key capabilities

• Linear Programming based optimization of home energy usage, per the package description and the linear-programming topic.
• Optimization over electricity prices, solar panel power generation, and battery energy storage as stated inputs.
• Model-predictive-control approach, named in the project topics.
• Generation of an optimized daily schedule for controllable devices in the home.
• Interfacing with Home Assistant, with dedicated guides for Home Assistant automations (docs/automations.md).
• High degree of configurability, described in the README as making integration with Home Assistant and other smart home systems easy.
• Suitability for households with solar panels, with energy storage, or with only a controllable load.
• MIT License, permitting use, copy, modification, merge, publication, distribution, sublicensing, and sale.

Who uses it and how

• Residential households with solar panels, where generation forecasts and prices shape the daily plan.
• Households with battery storage, where charging and discharging are scheduled rather than fixed.
• Households with only a controllable load, which the README explicitly names as a supported case.
• Home Assistant users who wire the optimization output into automations using the project's Home Assistant automations guide.
• Developers and contributors, since pull requests are accepted and development instructions live in docs/develop.md.

Getting started

The README directs new users to the Quick Start guide at docs/quick_start.md, with installation methods documented in docs/installation_methods.md. The README excerpt does not embed an exact package name, Docker image, or compose file; the installation methods page in the documentation is the authoritative source.

How it compares

No paid products are listed as being replaced by this project, and no comparable tools are named in the facts. On the evidence available, it stands alone in this registry.

When to use it — and when not to

It fits users already running Home Assistant or another smart home system who want optimization rather than hand-written scheduling rules for solar, batteries, and controllable loads. It does not fit users who want a hosted service, or who are unwilling to install and configure a Python module and read through separate installation and usage guides before anything runs. Honest limitations: the README excerpt is brief and carries no inline install command, and the project carries 50 open issues, so expect to work from the documentation site rather than the repository front page.