Example of steady temperature with 1t solver, all models and all parameters

In [1]:

import numpy as np
import matplotlib.pyplot as plt

from thermohl.solver.entities import VariableType
from thermohl.solver.entities import ModelType
from thermohl.solver.entities import HeatEquationType
from thermohl.solver.entities import PowerType

from thermohl import solver

import numpy as np import matplotlib.pyplot as plt from thermohl.solver.entities import VariableType from thermohl.solver.entities import ModelType from thermohl.solver.entities import HeatEquationType from thermohl.solver.entities import PowerType from thermohl import solver

In [2]:

# time array in hours
hour = np.linspace(0, 24, 241)[:-1]
minute = np.linspace(0, 24 * 60, 241)[:-1].astype(int)

# time array in hours hour = np.linspace(0, 24, 241)[:-1] minute = np.linspace(0, 24 * 60, 241)[:-1].astype(int)

We can modify the values of the parameters' dictionnary if we don't want to use the default values. Missing or None values in the input dictionary are replaced with a default value, available using solver.default_values()

In [3]:

# input dict, with varying transit, ambient temperature and wind speed
parameters = {
    # position
    "latitude": 45.2,
    "longitude": 0.0,
    "altitude": 543.0,
    "cable_azimuth": 21.0,
    "datetime_utc": np.array([np.datetime64(f"2026-06-20T{minute // 60:02d}:{minute % 60:02d}:00") for minute in minute]),
    
    # weather
    "ambient_temperature": 10.0 + 7.5 * (1 + np.sin(np.pi * (hour - 7.0) / 12.0)),
    "wind_speed": np.piecewise(hour, [hour <= 6.0, hour > 6.0, hour > 12.0, hour >= 18.0], [1.0, 2.0, 1.0, 3.0]),
    "wind_azimuth": 69,
    "albedo": 0.21,
    "turbidity": 0.5,
    
    # transit
    "transit": np.piecewise(hour, [hour < 12.0, hour >= 12.0], [300.0, 600.0]),
    
    # conductor
    "core_diameter": 0.0,
    "outer_diameter": 3.0e-02,
    "core_area": 0.0,
    "outer_area": 5.69e-04,
    "roughness_ratio": 6.30e-02,
    "solar_absorptivity": 0.9,
    "emissivity": 0.8,
    "linear_resistance_dc_20c": 5.84e-05,
    "magnetic_coeff": 1.02,
    "magnetic_coeff_per_a": 0.01,
    "temperature_coeff_linear": 4.0e-03,
    "temperature_coeff_quadratic": 8.0e-07,
    "linear_resistance_temp_high": 6.7744e-05,
    "linear_resistance_temp_low": 5.84e-05,
    "temp_high": 60.0,
    "temp_low": 20.0,
}

# input dict, with varying transit, ambient temperature and wind speed parameters = { # position "latitude": 45.2, "longitude": 0.0, "altitude": 543.0, "cable_azimuth": 21.0, "datetime_utc": np.array([np.datetime64(f"2026-06-20T{minute // 60:02d}:{minute % 60:02d}:00") for minute in minute]), # weather "ambient_temperature": 10.0 + 7.5 * (1 + np.sin(np.pi * (hour - 7.0) / 12.0)), "wind_speed": np.piecewise(hour, [hour <= 6.0, hour > 6.0, hour > 12.0, hour >= 18.0], [1.0, 2.0, 1.0, 3.0]), "wind_azimuth": 69, "albedo": 0.21, "turbidity": 0.5, # transit "transit": np.piecewise(hour, [hour < 12.0, hour >= 12.0], [300.0, 600.0]), # conductor "core_diameter": 0.0, "outer_diameter": 3.0e-02, "core_area": 0.0, "outer_area": 5.69e-04, "roughness_ratio": 6.30e-02, "solar_absorptivity": 0.9, "emissivity": 0.8, "linear_resistance_dc_20c": 5.84e-05, "magnetic_coeff": 1.02, "magnetic_coeff_per_a": 0.01, "temperature_coeff_linear": 4.0e-03, "temperature_coeff_quadratic": 8.0e-07, "linear_resistance_temp_high": 6.7744e-05, "linear_resistance_temp_low": 5.84e-05, "temp_high": 60.0, "temp_low": 20.0, }

In [4]:

# compute steady_temperature using 1t heat equation and Rte model
solver_rte = solver.rte(parameters, heat_equation=HeatEquationType.ONE_TEMPERATURE)
steady_temperature = solver_rte.steady_temperature()

# compute steady_temperature using 1t heat equation and Rte model solver_rte = solver.rte(parameters, heat_equation=HeatEquationType.ONE_TEMPERATURE) steady_temperature = solver_rte.steady_temperature()

In [5]:

# Compute steady temperature and power terms using all 4 models,
# using 1t heat equation
models = [
    ModelType.CIGRE,
    ModelType.IEEE,
    ModelType.OLLA,
    ModelType.RTE,
]
solvers = [
    solver._factory(
        parameters, heat_equation=HeatEquationType.ONE_TEMPERATURE, model=model
    )
    for model in models
]
results = [s.steady_temperature(return_power=True) for s in solvers]

# Compute steady temperature and power terms using all 4 models, # using 1t heat equation models = [ ModelType.CIGRE, ModelType.IEEE, ModelType.OLLA, ModelType.RTE, ] solvers = [ solver._factory( parameters, heat_equation=HeatEquationType.ONE_TEMPERATURE, model=model ) for model in models ] results = [s.steady_temperature(return_power=True) for s in solvers]

In [6]:

# plot all
fig, ax = plt.subplots(nrows=2, ncols=4, figsize=(20, 10))
for i, key in enumerate([VariableType.TRANSIT.value, "ambient_temperature", "wind_speed"]):
    ax[0, i].plot(hour, parameters[key])
    ax[0, i].set_title(f"Input {key}")

ax[0, 3].set_title("Conductor temperature")
for i, r in enumerate(results):
    ci = f"C{1 + i}"
    ax[0, 3].plot(hour, r[VariableType.TEMPERATURE.value], c=ci, label=models[i])
    for j, p in enumerate(
        [
            PowerType.JOULE,
            PowerType.SOLAR,
            PowerType.CONVECTION,
            PowerType.RADIATION,
        ]
    ):
        ax[1, j].plot(hour, r[p.value], c=ci, label=models[i])
        ax[1, j].set_title(f"{p.value} (W/m)")

for i in range(ax.shape[0]):
    for j in range(ax.shape[1]):
        ax[i, j].set_xlabel("Time (hour)")
        ax[i, j].grid(True)
ax[-1, -1].legend()
%matplotlib inline

# plot all fig, ax = plt.subplots(nrows=2, ncols=4, figsize=(20, 10)) for i, key in enumerate([VariableType.TRANSIT.value, "ambient_temperature", "wind_speed"]): ax[0, i].plot(hour, parameters[key]) ax[0, i].set_title(f"Input {key}") ax[0, 3].set_title("Conductor temperature") for i, r in enumerate(results): ci = f"C{1 + i}" ax[0, 3].plot(hour, r[VariableType.TEMPERATURE.value], c=ci, label=models[i]) for j, p in enumerate( [ PowerType.JOULE, PowerType.SOLAR, PowerType.CONVECTION, PowerType.RADIATION, ] ): ax[1, j].plot(hour, r[p.value], c=ci, label=models[i]) ax[1, j].set_title(f"{p.value} (W/m)") for i in range(ax.shape[0]): for j in range(ax.shape[1]): ax[i, j].set_xlabel("Time (hour)") ax[i, j].grid(True) ax[-1, -1].legend() %matplotlib inline