smif.convert.interval module¶
Handles conversion between the set of time intervals used in the SosModel
There are three main classes, which are currently rather intertwined.
Interval
represents an individual definition of a period
within a year.
This is specified using the ISO8601 period syntax and exposes
methods which use the isodate library to parse this into an internal hourly
representation of the period.
TimeIntervalRegister
holds the definitions of time-interval sets
specified for the sector models at the SosModel
level.
This class exposes one public method,
add_interval_set()
which allows the SosModel
to add an interval definition from a model configuration to the register.
Quantities¶
Quantities are associated with a duration, period or interval. For example 120 GWh of electricity generated during each week of February.:
Week 1: 120 GW
Week 2: 120 GW
Week 3: 120 GW
Week 4: 120 GW
Other examples of quantities:
- greenhouse gas emissions
- demands for infrastructure services
- materials use
- counts of cars past a junction
- costs of investments, operation and maintenance
Upscale: Divide¶
To convert to a higher temporal resolution, the values need to be apportioned across the new time scale. In the above example, the 120 GWh of electricity would be divided over the days of February to produce a daily time series of generation. For example:
1st Feb: 17 GWh
2nd Feb: 17 GWh
3rd Feb: 17 GWh
...
Downscale: Sum¶
To resample weekly values to a lower temporal resolution, the values would need to be accumulated. A monthly total would be:
Feb: 480 GWh
Remapping¶
Remapping quantities, as is required in the conversion from energy demand (hourly values over a year) to energy supply (hourly values for one week for each of four seasons) requires additional averaging operations. The quantities are averaged over the many-to-one relationship of hours to time-slices, so that the seasonal-hourly timeslices in the model approximate the hourly profiles found across the particular seasons in the year. For example:
hour 1: 20 GWh
hour 2: 15 GWh
hour 3: 10 GWh
...
hour 8592: 16 GWh
hour 8593: 12 GWh
hour 8594: 21 GWh
...
hour 8760: 43 GWh
To:
season 1 hour 1: 20+16+.../4 GWh # Denominator number hours in sample
season 1 hour 2: 15+12+.../4 GWh
season 1 hour 3: 10+21+.../4 GWh
...
Prices¶
Unlike quantities, prices are associated with a point in time. For example a spot price of £870/GWh. An average price can be associated with a duration, but even then, we are just assigning a price to any point in time within a range of times.
Upscale: Fill¶
Given a timeseries of monthly spot prices, converting these to a daily price can be done by a fill operation. E.g. copying the monthly price to each day.
From:
Feb: £870/GWh
To:
1st Feb: £870/GWh
2nd Feb: £870/GWh
...
Downscale: Average¶
On the other hand, going down scale, such as from daily prices to a monthly price requires use of an averaging function. From:
1st Feb: £870/GWh
2nd Feb: £870/GWh
...
To:
Feb: £870/GWh
Development Notes¶
- We could use
numpy.convolve()
to compare time intervals as hourly arrays before adding them to the set of intervals
Summary¶
Data:
BASE_YEAR |
int([x]) -> integer int(x, base=10) -> integer |
Interval |
A time interval |
IntervalAdaptor |
Convert intervals, assuming uniform distributions where necessary |
IntervalSet |
A collection of intervals |
Reference¶
-
class
smif.convert.interval.
IntervalAdaptor
(name)[source]¶ Bases:
smif.convert.adaptor.Adaptor
Convert intervals, assuming uniform distributions where necessary
-
generate_coefficients
(from_spec, to_spec) → <MagicMock id='139764765378688'>[source]¶ Generate conversion coefficients for interval dimensions
Assumes that the Coordinates elements contain an ‘interval’ key whose value corresponds to
Interval
data, that is a {‘name’: interval_id, ‘interval’: list of interval extents}.For example, intervals covering each hour of a period
{ 'name': 'first_hour', 'interval': [('PT0H', 'PT1H')] } { 'name': ''second_hour', 'interval': [('PT1H', 'PT2H')] } ...
Or intervals corresponding to repeating hours for each day of a period
{ 'name': midnight', 'interval': [ ('PT0H', 'PT1H'), ('PT24H', 'PT25H'), ('PT48H', 'PT49H'), ... ] }, { 'name': ''one_am', 'interval': [ ('PT1H', 'PT2H'), ('PT25H', 'PT26H'), ('PT49H', 'PT50H'), ... ] } ...
-
-
class
smif.convert.interval.
Interval
(name, list_of_intervals, base_year=2010)[source]¶ Bases:
object
A time interval
Parameters: - id (str) – The unique name of the Interval
- list_of_intervals (str) – A list of tuples of valid ISO8601 duration definition string denoting the time elapsed from the beginning of the year to the (beginning, end) of the interval
- base_year (int, default=2010) – The reference year used for conversion to a datetime tuple
Example
>>> a = Interval('id', ('PT0H', 'PT1H')) >>> a.interval = ('PT1H', 'PT2H') >>> repr(a) "Interval('id', [('PT0H', 'PT1H'), ('PT1H', 'PT2H')], base_year=2010)" >>> str(a) "Interval 'id' starts at hour 0 and ends at hour 1"
-
start
¶ The start hour of the interval(s)
Returns: A list of integers, representing the hour from the beginning of the year associated with the start of each of the intervals Return type: list
-
end
¶ The end hour of the interval(s)
Returns: An integer or list of integers, representing the hour from the beginning of the year associated with the end of each of the intervals Return type: int or list
-
interval
¶ The list of intervals
Setter appends a tuple or list of intervals to the list of intervals
-
baseyear
¶ The reference year
-
bounds
¶ Return a list of tuples of the intervals in terms of hours
Returns: A list of tuples of the start and end hours of the year of the interval Return type: list
-
to_hourly_array
()[source]¶ Converts a list of intervals to a boolean array of hours
Returns: A boolean array Return type: numpy.ndarray
-
class
smif.convert.interval.
IntervalSet
(name, data, base_year=2010)[source]¶ Bases:
smif.convert.register.ResolutionSet
A collection of intervals
Parameters: -
static
get_bounds
(entry)[source]¶ Implement this helper method to return bounds from an entry in the register
Parameters: entry – An entry from a ResolutionSet Returns: The bounds of the entry Return type: bounds
-
get_proportion
(from_index, to_interval)[source]¶ Find proportion of interval address by from_index in to_interval
Parameters: Returns: Return type:
-
intersection
(to_entry)[source]¶ Return the destination intervals that intersect with to_entry
to_entry : Interval
Returns: A list of Intervals that intersect with bounds Return type: list Notes
Look at the columns of the intersection array and identify overlapping intervals
-
static