electrolyzer/examples/example_05_controller/example_05_controller_options.py at main · NatLabRockies/electrolyzer · GitHub

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import pprint
from pathlib import Path

import numpy as np
import matplotlib.pyplot as plt

from electrolyzer.simulation.bert import run_electrolyzer
from electrolyzer.tools.validation import load_modeling_yaml


# Generate a power signal to illustrate Supervisor behavior

dt = 1

p1 = np.zeros(15 * 60)  # 15 minute buffer
p2 = np.ones(15 * 60)  # step up 30 minutes
p3 = np.zeros(15 * 60)  # step down 30 minutes
p4 = np.linspace(0, 1, 30 * 60)  # ramp up 1 hour
p5 = np.linspace(1, 0, 30 * 60)  # ramp down 1 hour

t_sin = np.logspace(0, np.log10(2 * 3600), 2 * 3600) - 1
t_sin = np.linspace(0, 2 * 3600, 2 * 3600)
p6 = 0.5 * (np.sin(t_sin / 600 - np.pi / 2) + 1)  # sine wave 2 hours


ws = np.load(
    Path.cwd()
    / "examples"
    / "example_05_controller"
    / "FC_wind"
    / "FC_August_1sec_1day.npy"
)[0 : 4 * 3600]


ws = ws / max(ws)
p7 = ws  # wind 4 hours

plant_rating = 5e6  # 5 MW H2 plant

power = plant_rating * np.concatenate([p1, p2, p3, p4, p5, p6, p7])

plt.plot(power * 1e-6)
plt.xlabel("Time (sec)")
plt.ylabel("Power (MW)")


def plot_results(result_df):
    # Collect H2 production rate timeseries from results
    stack_rates = result_df[[col for col in result_df.columns if "_kg_rate" in col]]

    fig_H2, ax_H2 = plt.subplots(6, 1, figsize=(10, 5), sharex=True)
    colors = ["C0", "C1", "C2", "C3", "C4"]

    ax_H2[0].plot(power * 1e-6, color="k", label="power (MW)")
    ax_H2[0].legend(loc="lower right")
    for i, stack in enumerate(stack_rates.columns):
        ax_H2[i + 1].plot(stack_rates[stack], color=colors[i], label=stack)
        ax_H2[i + 1].legend(loc="lower right")
    fig_H2.subplots_adjust(hspace=0)

    # Collect degradation timeseries from results
    deg = result_df[[col for col in result_df.columns if "deg" in col]]

    fig_deg, ax_deg = plt.subplots(6, 1, figsize=(10, 5), sharex=True)
    colors = ["C0", "C1", "C2", "C3", "C4"]

    ax_deg[0].plot(power * 1e-6, color="k", label="power (MW)")
    ax_deg[0].legend(loc="lower right")
    for i, stack in enumerate(deg.columns):
        ax_deg[i + 1].plot(deg[stack], color=colors[i], label=stack)
        ax_deg[i + 1].legend(loc="lower right")
    fig_deg.subplots_adjust(hspace=0)


fname_input_modeling = str(
    Path.cwd() / "examples" / "example_05_controller" / "modeling_options.yaml"
)
modeling_input = load_modeling_yaml(fname_input_modeling)
pprint.pprint(modeling_input)

modeling_input["electrolyzer"]["controller"]["control_type"] = "PowerSharingRotation"

elec_sys, result_df = run_electrolyzer(modeling_input, power)
plot_results(result_df)

modeling_input["electrolyzer"]["controller"]["control_type"] = "SequentialRotation"

elec_sys, result_df = run_electrolyzer(modeling_input, power)
plot_results(result_df)

modeling_input["electrolyzer"]["controller"]["control_type"] = "DecisionControl"
modeling_input["electrolyzer"]["controller"]["policy"] = {
    "eager_on": True,
    "eager_off": False,
    "sequential": True,
    "even_dist": True,
    "baseline": False,
}

elec_sys, result_df = run_electrolyzer(modeling_input, power)
plot_results(result_df)

modeling_input["electrolyzer"]["controller"]["control_type"] = "DecisionControl"
modeling_input["electrolyzer"]["controller"]["policy"] = {
    "eager_on": False,
    "eager_off": True,
    "sequential": False,
    "even_dist": False,
    "baseline": False,
}

elec_sys, result_df = run_electrolyzer(modeling_input, power)
plot_results(result_df)

modeling_input["electrolyzer"]["controller"]["control_type"] = "DecisionControl"
modeling_input["electrolyzer"]["controller"]["policy"] = {
    "eager_on": False,
    "eager_off": False,
    "sequential": True,
    "even_dist": False,
    "baseline": False,
}

elec_sys, result_df = run_electrolyzer(modeling_input, power)
plot_results(result_df)

plt.show()