SpinePeriods.jl

A package to run the optimisation-based representative period models described in this working paper.

Compatibility

Fill in once testing has been setup.

Installation

using Pkg
pkg"registry add https://github.com/Spine-tools/SpineJuliaRegistry"
pkg"add SpinePeriods"

Usage

Assuming you have a working SpineOpt database:

1. Load the SpineOpt periods template from src/representative_periods_template.json into your SpineOpt database.

2. Setup your model object; specify model_start and model_end as well as roll_forward - which determines the candidate periods for the model. In short, whatever SpineOpt would see as optimization windows, SpinePeriods sees as candidate periods.

3. Create a representative_period object (only one representative_period object is needed; if you create two or more, only one of them will be used and you wouldn't know which one.)

4. Specify the value of the representative_period_method parameter for your representative_period object, which determines the method for the representative periods model. Two values are possible:

   • representative_periods simply selects representative periods.
   • representative_periods_ordering also orders representative periods throughout the optimisation horizon so that long term storage arbitrage can be modeled (see this section of the SpineOpt documentation).

   The two methods are described in this working paper where they are referred to as ORDF and ORDO respectively.

5. Specify the value of the representative_periods and representative_blocks parameters for your representative_period object:

   • representative_periods is the number of representative periods to be selected (and ordered).
   • representative_blocks is the discretisation level of the duration curves used for the representative_periods_ordering method, i.e. not relevant for the representative_periods method. Higher leads to more accuracy; lower reduces problem size and speeds up computation.

6. Specify the value of the for_rolling Boolean parameter for your representative_period object, which determines whether or not the output of SpinePeriods should be a SpineOpt DB ready to run a rolling horizon optimization on the selected representative periods (as if they were successive).

7. Create unit__representative_period, node__representative_period and unit__node__representative_period relationships between your representative_period object, and the units and nodes that you want to include in the representative periods model. The relationships you create determine the parameter values used to select (and order) representative periods according to the table below.

   relationship	parameter
   unit__representative_period	unit_availability_factor for the unit
   node__representative_period	demand for the node
   unit__node__representative_period	unit_capacity for both the unit__from_node and unit__to_node

8. Optionally specify representative_period_weight for the above relationships. This determines the weight SpinePeriods will assign to the corresponding parameter value in the optimisation model. It defaults to 1.

9. You're ready to go! From Julia:

   using SpinePeriods
   db_url_in = "sqlite:///<path_to_your_input_database>"
   db_url_out = "sqlite:///<path_to_your_output_database>"
   json_out = "<path_to_your_output_file>.json" 
   run_spine_periods(
       db_url_in,
       db_url_out, # replace this with `json_out` to write results to a JSON file
       with_optimizer=optimizer_with_attributes(
           HiGHS.Optimizer, "output_flag" => true, "mip_rel_gap" => 0.01, "time_limit" => 600.0        
       )
   )

10. Let SpinePeriods cook. The output database will be a copy of the input with a few additions/modifications depending on the value of the for_rolling parameter:

    • If for rolling is false:

      • One temporal_block object for each selected representative period will be created. These temporal_blocks will also be associated to each unit and node included in your representative periods model (according to step 6 above) via units_on__temporal_block and node__temporal_block, respectively.
      • The value of roll_forward will be set to null.
      • For each temporal_block originally associated to any units and nodes included your representative periods model (as per step 6 above), if the value of block_end is a duration then it will be adjusted to reflect the fact that the model won't be rolling anymore.
      • Finally, if you selected the representative_periods_ordering method, then for each temporal_block originally associated to any units and nodes included in your representative periods model (as per step 6 above), the value of the representative_periods_mapping parameter will be set to a map that SpineOpt will like.

    • If for rolling is true:

      • The value of model_start for your model object will be set to the start of the first representative period selected.
      • The value of roll_forward will be set to an array of duration values, thus allowing SpineOpt to roll over the selected representative periods.
      • Finally, if you selected the representative_periods_ordering method, then the value of the representative_windows_mapping parameter for your model object will be set to a map from window start to representative window start.

    In either case, the database will be ready to be used by SpineOpt.

Troubleshooting and known issues

• Selecting and ordering periods of lengths smaller than days (e.g. hours) could make Julia crash. This should not be the case when only selecting periods.
• Similarly, selecting (and ordering) from several years could lead to Julia crashing if the optimisation problem becomes too large.

Reporting Issues and Contributing

See CONTRIBUTING.md

License

SpinePeriods is licensed under GNU Lesser General Public License version 3.0 or later.