Time Series¶

Infrastructure systems supports time series data expressed as a one-dimensional array of floats using the class SingleTimeSeries. Users must provide a variable_name that is typically the field of a component being modeled. For example, if the user has a time array associated with the active power of a generator, they would assign variable_name = "active_power".

Here is an example of how to create an instance of SingleTimeSeries:

    import random
    time_series = SingleTimeSeries.from_array(
        data=[random.random() for x in range(24)],
        variable_name="active_power",
        initial_time=datetime(year=2030, month=1, day=1),
        resolution=timedelta(hours=1),
    )

Users can attach their own attributes to each time array. For example, there might be different profiles for different scenarios or model years.

    time_series = SingleTimeSeries.from_array(
        data=[random.random() for x in range(24)],
        variable_name="active_power",
        initial_time=datetime(year=2030, month=1, day=1),
        resolution=timedelta(hours=1),
        scenario="high",
        model_year="2035",
    )

Resolution¶

Infrastructure systems support two types of objects for passing the resolution: :class:datetime.timedelta and :class:dateutil.relativedelta.relativedelta. These types allow users to define durations with varying levels of granularity and semantic meaning. While timedelta is best suited for precise, fixed-length intervals (e.g., seconds, minutes, hours, days), relativedelta is more appropriate for calendar-aware durations such as months or years, which do not have a fixed number of days.

Internally, all durations, regardless of whether they are specified using timedelta or relativedelta, are normalized and serialized into a strict ISO 8601 format. This provides a consistent and standardized representation of durations across the system, ensuring compatibility and simplifying transport, storage, and validation. For example, a timedelta of 1 month will be converted to the ISO format string P1M and a timedelta of 1 hour will be converted to P0DT1H.

Behaviors¶

Users can customize time series behavior with these flags passed to the System constructor:

time_series_in_memory: The System stores each array of data in an Arrow file by default. This is a binary file that enables efficient storage and row access. Set this flag to store the data in memory instead.
time_series_read_only: The default behavior allows users to add and remove time series data. Set this flag to disable mutation. That can be useful if you are de-serializing a system, won’t be changing it, and want to avoid copying the data.
time_series_directory: The System stores time series data on the computer’s tmp filesystem by default. This filesystem may be of limited size. If your data will exceed that limit, such as what is likely to happen on an HPC compute node, set this parameter to an alternate location (such as /tmp/scratch on NREL’s HPC systems).

Refer to the Time Series API for more information.