AndreasandClaude Opus 4.8 67cf6f7d8a feat(optimization): schedule any number of flexible consumers
Replace the single hourly "dishwasher" home appliance with a list of
flexible consumers (home_appliances). Each consumer defines its load
either as an explicit power profile (energy-preservingly resampled onto
the optimization slot grid, incl. 15-min and non-integer interval ratios)
or the flat consumption_wh/duration_h fallback, and runs ONCE or DAILY
within its time windows and the optimization horizon.

- ConsumerScheduleMode + shared load-definition validation (XOR of
  profile/fallback, reject negative/NaN/inf, unique device_id)
- ApplianceGeneLayout: variable appliance gene block (index into
  allowed_start_slots), ONCE/DAILY calendar-day based, no snapping
- per-device output: result.home_appliance_energy_wh, appliance_starts
  (absolute local times), per-device solution columns and DDBC RUN/OFF
  instructions on state transitions only
- deprecate dishwasher/washingstart/Home_appliance_wh_per_hour with
  backward-compatible mapping and explicit conflict rejection
- max_home_appliances is now an upper bound only; no demo appliance and
  no on/off behaviour
- docs, openapi.json, CHANGELOG and optimize_result_2* fixtures updated;
  new tests/test_homeappliance.py covers the mandatory test matrix

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-15 14:19:46 +02:00
2025-01-24 20:08:48 +01:00
2025-04-07 22:23:35 +02:00
2024-05-03 10:43:31 +02:00
2024-11-15 22:27:25 +01:00
2026-06-18 08:29:26 +02:00

AkkudoktorEOS AkkudoktorEOS

Build optimized energy management plans for your home automation

AkkudoktorEOS is a comprehensive solution for simulating and optimizing energy systems based on renewable sources. Optimize your photovoltaic systems, battery storage, load management, and electric vehicles while considering real-time electricity pricing.

Why use AkkudoktorEOS?

AkkudoktorEOS can be used to build energy management plans that are optimized for your specific setup of PV system, battery, electric vehicle, household load and electricity pricing. It can be integrated into home automation systems such as NodeRED, Home Assistant, EVCC.

🏘️ Community

We are an open-source community-driven project and we love to hear from you. Here are some ways to get involved:

What do people build with AkkudoktorEOS

The community uses AkkudoktorEOS to minimize grid energy consumption and to maximize the revenue from grid energy feed in with their home automation system.

Why not use AkkudoktorEOS?

AkkudoktorEOS does not control your home automation assets. It must be integrated into a home automation system. If you do not use a home automation system or you feel uncomfortable with the configuration effort needed for the integration you should better use other solutions.

Quick Start

Run EOS with Docker (access dashboard at http://localhost:8504):

docker run -d \
  --name akkudoktoreos \
  -p 8503:8503 \
  -p 8504:8504 \
  -e OPENBLAS_NUM_THREADS=1 \
  -e OMP_NUM_THREADS=1 \
  -e MKL_NUM_THREADS=1 \
  -e EOS_SERVER__HOST=0.0.0.0 \
  -e EOS_SERVER__EOSDASH_HOST=0.0.0.0 \
  -e EOS_SERVER__EOSDASH_PORT=8504 \
  --ulimit nproc=65535:65535 \
  --ulimit nofile=65535:65535 \
  --security-opt seccomp=unconfined \
  akkudoktor/eos:latest

System Requirements

  • Python: 3.11 or higher
  • Architecture: amd64, aarch64 (armv8)
  • OS: Linux, Windows, macOS

Note

: Other architectures (armv6, armv7) require manual compilation of dependencies with Rust and GCC.

Installation

Home Assistant add-on

Supports aarch64 Architecture Supports amd64 Architecture

To install the Akkudoktor-EOS add-on in Home Assistant:

Open your Home Assistant instance and show the add add-on repository dialog with a specific repository URL pre-filled.

  1. Add the repository URL:

    In Home Assistant, go to:

    Settings → Add-ons → Add-on Store → ⋮ (top-right menu) → Repositories
    

    and enter the URL of this Git repository:

    https://github.com/Akkudoktor-EOS/EOS
    
  2. Install the add-on:

    After adding the repository, the add-on will appear in the Add-on Store. Click Install.

  3. Start the add-on:

    Once installed, click Start in the add-on panel.

  4. Access the dashboard:

    Click Open Web UI in the add-on panel.

  5. Configure EOS (optional): In the dashboard, go to:

    Config
    
docker pull akkudoktor/eos:latest
docker compose up -d

Access the API at http://localhost:8503 (docs at http://localhost:8503/docs)

From Source

git clone https://github.com/Akkudoktor-EOS/EOS.git
cd EOS

Linux:

python -m venv .venv
.venv/bin/pip install -r requirements.txt
.venv/bin/pip install -e .
.venv/bin/python -m akkudoktoreos.server.eos

Windows:

python -m venv .venv
.venv\Scripts\pip install -r requirements.txt
.venv\Scripts\pip install -e .
.venv\Scripts\python -m akkudoktoreos.server.eos

Configuration

EOS uses EOS.config.json for configuration. If the file doesn't exist, a default configuration is created automatically.

Custom Configuration Directory

export EOS_DIR=/path/to/your/config

Configuration Methods

  1. EOSdash (Recommended) - Web interface at http://localhost:8504
  2. Manual - Edit EOS.config.json directly
  3. API - Use the Server API

See the documentation for all configuration options.

Port Configuration

Default ports: 8503 (API), 8504 (Dashboard)

If running on shared systems (e.g., Synology NAS), these ports may conflict with system services. Reconfigure port mappings as needed:

docker run -p 8505:8503 -p 8506:8504 ...

API Documentation

Interactive API docs available at:

  • Swagger UI: http://localhost:8503/docs
  • OpenAPI Spec: View Online

Resources

Contributing

We welcome contributions! See CONTRIBUTING for guidelines.

Contributors

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

S
Description
This repository features an Energy Optimization System (EOS) that optimizes energy distribution, usage for batteries, heat pumps& household devices. It includes predictive models for electricity prices (planned), load forecasting& dynamic optimization to maximize energy efficiency & minimize costs. Founder Dr. Andreas Schmitz (YouTube @akkudoktor)
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