Resource data

Resource data#

Common Resource Datasets and Considerations#

Both wind and solar resource data can be obtained from resource models that use the OpenMeteo Archive API or resource models that use the resource models available in the NLR Developer Network.

Resource models that use the NLR Developer Network require an API key (which can be obtained for free from here). Resource models that use the OpenMeteo Archive API do not require an API key.

Another key difference is that the NLR resource datasets are constrained to specific geographic regions, meaning you have to choose the resource model that corresponds to your site location. OpenMeteo resource data is available globally, for all onshore sites.

Note

OpenMeteo data can be downloaded directly from the web instead of using the models in H2I. If OpenMeteo resource data is downloaded directly from the web and in the local timezone of the site, the data is downloaded with a UTC offset in daylight time whereas data downloaded with the H2I resource models will use a UTC offset in standard time. Resource data downloaded from the NLR Developer developer network in local time also use a UTC offset in standard time.

Setting resource data for a technology#

There are two ways to supply resource data to a technology:

  1. Set resource for a technology data using set_val()

  2. Create a custom resource model for the technology

Resource data specified using set_val()#

Resource data for a technology can be set using the set_val() command. In the Run of River Example, the technology named river needs a resource input called discharge. An example of this is shown below:

import pandas as pd
from h2integrate import H2IntegrateModel
# Create an H2I model
h2i = H2IntegrateModel("07_run_of_river.yaml")

# Suppose we load the resource data from a csv file
resource_df = pd.read_csv("river_resource_data.csv")

# Setup the h2i model
h2i.setup()

# Set the resource data for the river
h2i.set_val("river.discharge", val=resource_df["discharge"].values, units="m**3/s")

# Run the model
h2i.run()

Custom resource models#

The benefit of using a custom resource model is that the resource data can be made to vary for different inputs, which can be beneficial if running a design sweep or optimization where the resource location (specified by a latitude and longitude) is a design variable.

A general resource model can be defined similarly to a custom technology model. A custom resource model should be defined in the plant configuration file within a site section under sites.

Note

Note that all custom resource models must have inputs of latitude and longitude. The outputs of your custom resource model should match the expected input to whatever model its connected to.

Below shows an example, similar to the Run of River Example of how to define a custom resource model within the plant_config.yaml file:

sites:
  site:
    latitude: 32.34
    longitude: -98.27
    resources:
      river_resource:
        resource_model: CustomRiverResource
        resource_model_location: river_resource/river_resource_model.py
        resource_parameters:
          filename: river_data.csv

resource_to_tech_connections:
  # connect the river resource to the run-of-river hydro technology
  - [site.river_resource, river, discharge]

The output discharge from the custom river_resource model is an input to the technology river. The custom resource model is a class named CustomRiverResource and the filepath for the CustomRiverResource is specified as the resource_model_location.