postreise.analyze package

Subpackages

• postreise.analyze.generation package
  • Subpackages
    • postreise.analyze.generation.tests package
      • Submodules
      • postreise.analyze.generation.tests.test_binding module
      • postreise.analyze.generation.tests.test_capacity module
      • postreise.analyze.generation.tests.test_costs module
      • postreise.analyze.generation.tests.test_curtailment module
      • postreise.analyze.generation.tests.test_emissions module
      • postreise.analyze.generation.tests.test_summarize module
      • Module contents
  • Submodules
  • postreise.analyze.generation.binding module
    • pmax_constraints()
    • pmin_constraints()
    • ramp_constraints()
  • postreise.analyze.generation.capacity module
    • calculate_NLDC()
    • calculate_net_load_peak()
    • get_capacity_by_resources()
    • get_capacity_factor_time_series()
    • get_storage_capacity()
    • sum_capacity_by_type_zone()
  • postreise.analyze.generation.costs module
    • calculate_costs()
  • postreise.analyze.generation.curtailment module
    • calculate_curtailment_percentage_by_resources()
    • calculate_curtailment_time_series()
    • calculate_curtailment_time_series_by_areas()
    • calculate_curtailment_time_series_by_areas_and_resources()
    • calculate_curtailment_time_series_by_resources()
    • calculate_curtailment_time_series_by_resources_and_areas()
    • get_curtailment_time_series()
    • summarize_curtailment_by_bus()
    • summarize_curtailment_by_location()
  • postreise.analyze.generation.emissions module
    • carbon_diff()
    • generate_emissions_stats()
    • summarize_emissions_by_bus()
  • postreise.analyze.generation.summarize module
    • get_generation_time_series_by_resources()
    • get_storage_time_series()
    • sum_generation_by_state()
    • sum_generation_by_type_zone()
    • summarize_hist_gen()
  • Module contents
• postreise.analyze.tests package
  • Submodules
  • postreise.analyze.tests.test_demand module
    • test_get_demand_time_series()
    • test_get_net_demand_time_series()
  • postreise.analyze.tests.test_time module
    • test_change_time_zone()
    • test_change_time_zone_argument_type()
    • test_change_time_zone_argument_value()
    • test_daily_resampling_incomplete_and_time_shift_mean()
    • test_daily_resampling_incomplete_and_time_shift_sum()
    • test_daily_resampling_incomplete_mean()
    • test_daily_resampling_incomplete_sum()
    • test_daily_resampling_mean()
    • test_daily_resampling_sum()
    • test_daily_resampling_time_shift_mean()
    • test_daily_resampling_time_shift_sum()
    • test_is_24_hour_format()
    • test_is_dst()
    • test_monthly_resampling_incomplete_and_time_shift_mean()
    • test_monthly_resampling_incomplete_and_time_shift_sum()
    • test_monthly_resampling_incomplete_mean()
    • test_monthly_resampling_incomplete_sum()
    • test_monthly_resampling_mean()
    • test_monthly_resampling_sum()
    • test_monthly_resampling_time_shift_mean()
    • test_monthly_resampling_time_shift_sum()
    • test_resampling_argument_value()
    • test_slicing()
    • test_slicing_argument_value()
    • test_weekly_resampling_incomplete_and_time_shift_mean()
    • test_weekly_resampling_incomplete_and_time_shift_sum()
    • test_weekly_resampling_incomplete_mean()
    • test_weekly_resampling_incomplete_sum()
    • test_weekly_resampling_mean()
    • test_weekly_resampling_sum()
    • test_weekly_resampling_time_shift_mean()
    • test_weekly_resampling_time_shift_sum()
  • Module contents
• postreise.analyze.transmission package
  • Subpackages
    • postreise.analyze.transmission.tests package
      • Submodules
      • postreise.analyze.transmission.tests.test_congestion_surplus module
      • postreise.analyze.transmission.tests.test_utilization module
      • Module contents
  • Submodules
  • postreise.analyze.transmission.congestion module
    • calculate_congestion_surplus()
  • postreise.analyze.transmission.utilization module
    • generate_cong_stats()
    • get_utilization()
  • Module contents

Submodules

postreise.analyze.demand module

postreise.analyze.demand.get_demand_time_series(scenario, area, area_type=None)

Get time series demand in certain area of a scenario

Parameters:

• scenario (powersimdata.scenario.scenario.Scenario) – scenario instance

• area (str) – one of loadzone, state, state abbreviation, interconnect, ‘all’

• area_type (str) – one of ‘loadzone’, ‘state’, ‘state_abbr’, ‘interconnect’

Returns:

(pandas.Series) – time series of total demand, index: time stamps, column: demand values

postreise.analyze.demand.get_net_demand_time_series(scenario, area, area_type=None)

Get time series net demand in certain area of a scenario

Parameters:

• scenario (powersimdata.scenario.scenario.Scenario) – scenario instance

• area (str) – one of loadzone, state, state abbreviation, interconnect, ‘all’

• area_type (str) – one of ‘loadzone’, ‘state’, ‘state_abbr’, ‘interconnect’

Returns:

(pandas.Series) – time series of total demand, index: time stamps, column: net demand values

postreise.analyze.time module

postreise.analyze.time.change_time_zone(ts, tz)

Convert hourly time series to new time zone. UTC is assumed if no time zone is assigned to the input time series.

Parameters:

• ts (pandas.DataFrame/pands.Series) – time series.

• tz (str) – new time zone.

Returns:

(pandas.DataFrame/pandas.Series) – time series with new time zone.

Raises:

• TypeError – if tz is not a str.

• ValueError – if tz is invalid or the time series has already been resampled.

postreise.analyze.time.is_24_hour_format(time)

Check if the input string is in 24-hour format

Parameters:

time (str) – input string

Returns:

(bool) – the input string is in 24-hour format or not

postreise.analyze.time.is_dst(ts)

Flag Daylight Saving Time (DST) in a time series.

Parameters:

ts (pandas.DataFrame/pands.Series) – time series.

Returns:

(bool) – True if time zone observes DST.

postreise.analyze.time.resample_time_series(ts, freq, agg='sum')

Resample a time series.

Parameters:

• ts (pandas.DataFrame/pandas.Series) – time series to resample.

• freq (str) – frequency. Either ‘D’ (day), ‘W’ (week), ‘M’ (month).

• agg (str) – aggregation method. Either ‘sum’ or ‘mean’.

Returns:

(pandas.DataFrame/pandas.Series) – the resampled time series.

Raises:

ValueError – if freq is not one of ‘D’, ‘W’, ‘M’ or agg is not one of ‘sum’ or ‘mean’ or ts is time zone aware with DST.

Note

When resampling:

• the left side of the bin interval is closed.

• the left bin edge is used to label the interval.

• intervals start at midnight when freq is ‘D’.

• intervals start on Sunday when freq is ‘W’.

• incomplete days, weeks and months are clipped when agg is ‘sum’.

• incomplete days, weeks and months are calculated using available data samples when agg is ‘mean’.

postreise.analyze.time.slice_time_series(ts, start, end, between_time=None, dayofweek=None)

Slice a time series.

Parameters:

• ts (pandas.DataFrame/pandas.Series) – time series to slice.

• start (pandas.Timestamp/numpy.datetime64/datetime.datetime) – start date.

• end (pandas.Timestamp/numpy.datetime64/datetime.datetime) – end date.

• between_time (list) – specify the start hour and end hour of each day inclusively, default to None, which includes every hour of a day. Note that if the end hour is set before the start hour, the complementary hours of a day are picked.

• dayofweek (set) – specify the interest days of week, which is a subset of integers in [0, 6] with 0 being Monday and 6 being Sunday, default to None, which includes every day of a week.

Returns:

(pandas.DataFrame/pandas.Series) – the sliced time series.

Raises:

• TypeError – if between_time is provided but not a list and/or if not all elements of between_time are strings and/or if dayofweek is provided but not a set.

• ValueError – if between_time is provided but does not have exactly two elements and/or if not all elements of between_time are in 24 hour format and/or if dayofweek is provided but not a subset of integers in [0, 6].

Module contents