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.
The project requires Python 3.9 or newer. Currently there are no official packages or images published.
Following sections describe how to locally start the EOS server on http://localhost:8503.
Install dependencies in virtual environment:
python -m venv .venv
.venv/bin/pip install -r requirements.txtFinally, start EOS fastapi server:
.venv/bin/fastapi run --port 8503 src/akkudoktoreos/server/fastapi_server.pydocker compose up --buildThis project uses the EOS.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.
EOS_DIR contains an existing config.json file, the application will use this configuration file.EOS.config.json file does not exist in the specified directory, the default.config.json file will be copied to the directory as EOS.config.json.If the configuration keys in the EOS.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.
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 API documentation for detailed information: EOS OpenAPI Spec