entise 1.3.0

Key Features

• Multiple time series types including DHW, HVAC, PV, and more in the works.

• Flexible pipeline- and strategy-based architecture for customizable time series generation.

• Support for dependent methods to create related time series.

• Two access patterns: batch processing via TimeSeriesGenerator or direct method imports for individual control.

Requirements

• Python (3.10 or newer)

• Git for version control (optional, only for development)

Installation

EnTiSe can be installed directly from PyPI:

pip install entise

For faster installation, you can use uv:

pip install uv
uv pip install entise

For development or the latest features, you can install directly from the repository:

pip install git+https://github.com/tum-ens/entise.git

Or clone the repository and install in development mode:

git clone https://github.com/tum-ens/need/entise.git
cd entise
pip install -e ".[dev]"

Now you’re ready to use EnTiSe! Check the examples directory for usage examples.

Basic Usage

EnTiSe provides two flexible ways to generate time series data:

from entise import Generator

# Initialize the generator
gen = Generator()

# Add objects (e.g., buildings)
gen.add_objects({
    "id": "building1",
    "hvac": "1R1C",
    "resistance": 2.0,
    "capacitance": 1e5,
    "temp_min": 20.0,
    "temp_max": 24.0,
})

# Prepare input data (e.g., weather)
data = {
    "weather": pd.DataFrame({
        "temp_out": [0.0] * 24,
    }, index=pd.date_range("2025-01-01", periods=24, freq="h"))
}

# Generate time series
summary, df = gen.generate(data)

from entise.methods.pv import PVLib

# Create an instance
pvlib = PVLib()

# Generate time series
result = pvlib.generate(
    latitude=48.1,
    longitude=11.6,
    power=5000,
    weather=weather_df
)

# Access results
summary = result["summary"]
timeseries = result["timeseries"]

Supported or Planned Time Series Types

EnTiSe supports generating time series for the following types:

Integrated:

• Electricity demand

• Domestic Hot Water (DHW)

• Heat pump (COP)

• HVAC (Heating, Ventilation, and Air Conditioning)

• Occupancy data

• Solar Photovoltaic (PV)

• Wind energy

Planned:

• Concentrated Solar Power (CSP) (https://oemof-thermal.readthedocs.io/en/latest/concentrating_solar_power.html)

• Geothermal energy

• Hydroelectric power (https://github.com/IdahoLabResearch/HydroGenerate or https://github.com/9505-PNNL/wmpy_power or https://www.theoj.org/joss-papers/joss.03294/10.21105.joss.03294.pdf)

• Mobility (https://emobpy.readthedocs.io/en/latest/)

• Solar thermal (https://oemof-thermal.readthedocs.io or https://www.theoj.org/joss-papers/joss.03294/10.21105.joss.03294.pdf)

• Tidal energy

• Wave energy

Coding Standards

This repository follows consistent coding styles. Refer to CONTRIBUTING.md for detailed standards.

Changelog

The changelog is maintained in the CHANGELOG.md file. It lists all changes made to the repository. Follow instructions there to document any updates.