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# Open-Loop Storage Controllers Demonstrations

```{code-cell} ipython3
from pathlib import Path
from matplotlib import pyplot as plt
from h2integrate.core.h2integrate_model import H2IntegrateModel
```

## Hydrogen Dispatch

The following example is an expanded form of `examples/14_wind_hydrogen_dispatch`.

Here, we're highlighting the dispatch controller setup from
`examples/14_wind_hydrogen_dispatch/inputs/tech_config.yaml`. Please note some sections are removed
simply to highlight the controller sections

```{literalinclude} ../../examples/14_wind_hydrogen_dispatch/inputs/tech_config.yaml
:language: yaml
:lineno-start: 54
:linenos: true
:lines: 54,59-61,67-74
```

Using the primary configuration, we can create, run, and postprocess an H2Integrate model.

```{code-cell} ipython3
# Create an H2Integrate model
model = H2IntegrateModel(Path("../../examples/14_wind_hydrogen_dispatch/inputs/h2i_wind_to_h2_storage.yaml"))

# Run the model
model.run()
model.post_process()
```

Now, we can visualize the demand profiles over time.

```{code-cell} ipython3
fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(8, 6), layout="tight")

start_hour = 0
end_hour = 200
total_time_steps = model.prob.get_val("h2_storage.hydrogen_soc").size
demand_profile = [
    model.technology_config["technologies"]["h2_storage"]["model_inputs"]["control_parameters"][
        "demand_profile"
    ]
    * 1e-3
] * total_time_steps
xvals = list(range(start_hour, end_hour))

ax1.plot(
    xvals,
    model.prob.get_val("h2_storage.hydrogen_soc", units="percent")[start_hour:end_hour],
    label="SOC",
)
ax2.plot(
    xvals,
    model.prob.get_val("h2_storage.hydrogen_in", units="t/h")[start_hour:end_hour],
    linestyle="-",
    label="H$_2$ Produced (kg)",
)
ax2.plot(
    xvals,
    model.prob.get_val("h2_storage.hydrogen_unused_commodity", units="t/h")[start_hour:end_hour],
    linestyle=":",
    label="H$_2$ Unused (kg)",
)
ax2.plot(
    xvals,
    model.prob.get_val("h2_storage.hydrogen_unmet_demand", units="t/h")[start_hour:end_hour],
    linestyle=":",
    label="H$_2$ Unmet Demand (kg)",
)
ax2.plot(
    xvals,
    model.prob.get_val("h2_storage.hydrogen_out", units="t/h")[start_hour:end_hour],
    linestyle="-",
    label="H$_2$ Delivered (kg)",
)
ax2.plot(
    xvals,
    demand_profile[start_hour:end_hour],
    linestyle="--",
    label="H$_2$ Demand (kg)",
)

ax1.set_ylabel("SOC (%)")
ax1.grid()
ax1.set_axisbelow(True)
ax1.set_xlim(0, 200)
ax1.set_ylim(0, 50)

ax2.set_ylabel("H$_2$ Hourly (t)")
ax2.set_xlabel("Timestep (hr)")
ax2.grid()
ax2.set_axisbelow(True)
ax2.set_ylim(0, 20)
ax2.set_yticks(range(0, 21, 2))

plt.legend(ncol=3)
fig.show()
```