This project provides a comprehensive solution for simulating and optimizing an energy system based on renewable energy sources. With a focus on photovoltaic (PV) systems, battery storage (batteries), load management (consumer requirements), heat pumps, electric vehicles, and consideration of electricity price data, this system enables forecasting and optimization of energy flow and costs over a specified period.
See CONTRIBUTING.md.
Good installation guide: https://meintechblog.de/2024/09/05/andreas-schmitz-joerg-installiert-mein-energieoptimierungssystem/
The project requires Python 3.10 or newer.
This project uses a config.json
file to manage configuration settings.
A default configuration file default.config.json
is provided. This file contains all the necessary configuration keys with their default values.
Users can specify a custom configuration directory by setting the environment variable EOS_DIR
.
- If the directory specified by
EOS_DIR
contains an existingconfig.json
file, the application will use this configuration file. - If the
config.json
file does not exist in the specified directory, thedefault.config.json
file will be copied to the directory asconfig.json
.
If the configuration keys in the config.json
file are missing or different from those in default.config.json
, they will be automatically updated to match the default settings, ensuring that all required keys are present.
On Linux (Ubuntu/Debian):
sudo apt install make
On MacOS (requires Homebrew):
brew install make
The server can be started with make run
. A full overview of the main shortcuts is given by make help
.
All necessary dependencies can be installed via pip
. Clone the repository and install the required packages with:
git clone https://github.com/Akkudoktor-EOS/EOS
cd EOS
Next, create a virtual environment. This serves to store the Python dependencies, which we will install later using pip
:
python -m venv .venv
Finally, install the Python dependencies for EOS:
.venv/bin/pip install -r requirements.txt
To always use the Python version from the virtual environment, you should activate it before working in EOS:
source .venv/bin/activate
To use the system and start the server, run fastapi_server.py
in the previously activated virtual environment:
fastapi run src/akkudoktoreos/server/fastapi_server.py
To run the system with Docker:
docker compose up --build
This project uses various classes to simulate and optimize the components of an energy system. Each class represents a specific aspect of the system, as described below:
-
PVAkku
: Simulates a battery storage system, including capacity, state of charge, and now charge and discharge losses. -
PVForecast
: Provides forecast data for photovoltaic generation, based on weather data and historical generation data. -
Load
: Models the load requirements of a household or business, enabling the prediction of future energy demand. -
Heatpump
: Simulates a heat pump, including its energy consumption and efficiency under various operating conditions. -
Strompreis
: Provides information on electricity prices, enabling optimization of energy consumption and generation based on tariff information. -
EMS
: The Energy Management System (EMS) coordinates the interaction between the various components, performs optimization, and simulates the operation of the entire energy system.
These classes work together to enable a detailed simulation and optimization of the energy system. For each class, specific parameters and settings can be adjusted to test different scenarios and strategies.
Each class is designed to be easily customized and extended to integrate additional functions or improvements. For example, new methods can be added for more accurate modeling of PV system or battery behavior. Developers are invited to modify and extend the system according to their needs.
See the Swagger documentation for detailed information: EOS OpenAPI Spec