antupy 0.6.0

Toolkit for energy engineering

antupy

antupy (from the mapuzugun word "antü" (sun)[^1]) is an open-source python library to support the development of (solar thermal) energy research projects. It is a toolkit of classes and methods to help simulate energy conversion and energy storage systems, under uncertain timeseries constraints (weather, market, human behaviour, etc.).

An object-oriented software, it is structured in three main interdependent layers:

• Core layer: A unit management system providing three classes to represent physical quantities with automatic unit tracking and conversion. Var for scalars, Array for vectors/timeseries, and Frame for tabular data with per-column units.
• Utilities layer: A set of modules built on top of the core layer: props (thermophysical properties), htc (heat transfer correlations), solar (sun position and radiation calculations), and loc (geographical location management).
• Simulation layer: Framework for building and analyzing energy systems using Model, Plant, and Parametric classes to support energy system simulation development (Weather, Market).

So far, some research projects that have used antupy:

• bdr_csp: A repository for csp simulations.
• tm_solarshift: A repository for domestic electric water heating systems (specifically for the Australian market).

Documentation

The full documentation is available here.

Brief Introduction

antupy works in its core with a unit management module units, which include the class Unit to represent units that are compatible with the SI unit system. From this, three type of variables are introduced:

1. The Var class to manage single variables, with the structure (value:float, unit:str).
2. The Array class for 1D data structures in the form of (array:np.ndarray, unit:str).
3. The Frame class for 2D data structures in the form of (frame:pd.DataFrame, units:list[str]). Where the string unit (or units) has to follow a couple of simple rules to represent properly physical units. All three classes support arithmetic operations with automatic unit conversion and dimensional checking, ensuring dimensional consistency throughout calculations.

Core Concepts

Plant - System Integration Container

The Plant class is the main simulation container where you define components as class attributes and implement the run_simulation() method. Components can be dataclasses representing physical equipment with run_model() methods, TimeSeriesGenerators for weather/market data, or other model objects. The Plant orchestrates the simulation workflow and stores results in the out dictionary.

Example workflow:

1. Define components as class attributes (collectors, tanks, heat exchangers, etc.)
2. Implement run_simulation() to define the simulation logic
3. Access results through the out attribute

Parametric - Sensitivity Analysis

The Parametric class enables parametric studies by running multiple simulations while systematically varying input parameters. It accepts a base Plant or Simulation instance and a dictionary of parameter ranges (as Array objects), runs all parameter combinations, and returns results as a Frame with units preserved. Supports detailed result saving and incremental CSV export for long-running studies.

TimeSeriesGenerator (TSG)

Protocol for generating time-dependent boundary conditions. Current implementations include:

• Weather: TMY (Typical Meteorological Year), historical weather, Monte Carlo weather generation, and constant-day modes
• Market: Electricity price data for Australia (MarketAU) and Chile (MarketCL)

TSGs provide the get_data() method to retrieve timeseries data with proper unit tracking.

Examples

Quick Start - Core Classes

from antupy import Var, Array, Frame
import numpy as np

# Scalar with units
mass = Var(5.0, "kg")
power = Var(100, "kW")
time = Var(1, "day")

# Automatic unit conversion and arithmetic
energy = (power * time).su("kWh")  # 2400 [kWh]
energy = (power * time).su("kW")   # Throws an error
print(f"Energy: {energy}")

# Arrays and Frames with units
temps = Array([20, 25, 30], "degC")

# Frames with per-column units
data = {"power": [10., 20., 40.], "area": [20., 35., 50.]}
df = Frame(data=data, units={"power": "MW", "area": "m2"})

Thermophysical Properties

from antupy import Var
from antupy.props import Water

# Calculate energy stored in a water tank
temp_max = Var(60, "degC")
temp_mains = Var(20, "degC")
vol_tank = Var(300, "L")
fluid = Water()

# Get temperature-dependent properties
temp_avg = (temp_max + temp_mains) / 2
cp = fluid.cp(temp_avg)   # Specific heat [J/kg-K]
rho = fluid.rho(temp_avg)  # Density [kg/m3]

# Calculate stored energy
q_stg = vol_tank * rho * cp * (temp_max - temp_mains)
print(f"Energy stored: {q_stg.su('kWh'):.1f}")  # Output in kWh

For complete examples including Plant simulations and Parametric studies, see the documentation.

Data

[^1]: mapuzugun is the language of the Mapuche people, the main indigineous group in Chile. antü (antv) means sun, but it also represents one of the main pijan (spirits) in the Mapuche mythology. Here the word is used in its first literal meaning. The name was chosen because the first version of this software was written in Temuco, at the historic Mapuche heartland.