Merge branch 'master' into adding_solar_tracking_single_axis

config/config.default.yaml

@@ -785,11 +785,23 @@ solving:
     # io_api: "direct"  # Increases performance but only supported for the highs and gurobi solvers
     # options that go into the optimize function
     track_iterations: false
-    min_iterations: 4
-    max_iterations: 6
+    min_iterations: 2
+    max_iterations: 3
     transmission_losses: 2
     linearized_unit_commitment: true
     horizon: 365
+    post_discretization:
+      enable: false
+      line_unit_size: 1700
+      line_threshold: 0.3
+      link_unit_size:
+        DC: 2000
+        H2 pipeline: 1200
+        gas pipeline: 1500
+      link_threshold:
+        DC: 0.3
+        H2 pipeline: 0.3
+        gas pipeline: 0.3
 
   constraints:
     CCL: false

doc/configtables/solving.csv

@@ -14,6 +14,14 @@ options,,,
 -- transmission_losses,int,[0-9],"Add piecewise linear approximation of transmission losses based on n tangents. Defaults to 0, which means losses are ignored."
 -- linearized_unit_commitment,bool,"{'true','false'}",Whether to optimise using the linearized unit commitment formulation.
 -- horizon,--,int,Number of snapshots to consider in each iteration. Defaults to 100.
+-- post_discretization,,,
+-- -- enable,bool,"{'true','false'}",Switch to enable post-discretization of the network. Disabled by default.
+-- -- line_unit_size,MW,float,Discrete unit size of lines in MW.
+-- -- line_threshold,,float,The threshold relative to the discrete line unit size beyond which to round up to the next unit.
+-- -- link_unit_size,MW,float,Discrete unit size of links in MW by carrier (given in dictionary style).
+-- -- -- {carrier},,,
+-- -- link_threshold,,float,The threshold relative to the discrete link unit size beyond which to round up to the next unit by carrier (given in dictionary style).
+-- -- -- {carrier},,,
 constraints ,,,
 -- CCL,bool,"{'true','false'}",Add minimum and maximum levels of generator nominal capacity per carrier for individual countries. These can be specified in the file linked at ``electricity: agg_p_nom_limits`` in the configuration. File defaults to ``data/agg_p_nom_minmax.csv``.
 -- EQ,bool/string,"{'false',`n(c| )``; i.e. ``0.5``-``0.7c``}",Require each country or node to on average produce a minimal share of its total consumption itself. Example: ``EQ0.5c`` demands each country to produce on average at least 50% of its consumption; ``EQ0.5`` demands each node to produce on average at least 50% of its consumption.

doc/release_notes.rst

@@ -46,6 +46,11 @@ Upcoming Release
 
 * Allow dictionary for the config aviation_demand_factor.
 
+* Add option to post-discretize line and link capacities based on unit sizes and
+  rounding thresholds specified in the configuration under ``solving: options:
+  post_discretization:`` when iterative solving is enables (``solving: optiosn:
+  skip_iterations: false``). This option is disabled by default.
+
 * Group existing capacities to the earlier grouping_year for consistency with optimized capacities.
 
 * Update data bundle:

envs/environment.yaml

@@ -11,7 +11,7 @@ dependencies:
 - pip
 
 - atlite>=0.2.9
-- pypsa>=0.26.1
+- pypsa>=0.28
 - linopy
 - dask
 

scripts/solve_network.py

@@ -1007,9 +1007,12 @@ def solve_network(n, config, solving, **kwargs):
     elif skip_iterations:
         status, condition = n.optimize(**kwargs)
     else:
-        kwargs["track_iterations"] = (cf_solving.get("track_iterations", False),)
-        kwargs["min_iterations"] = (cf_solving.get("min_iterations", 4),)
-        kwargs["max_iterations"] = (cf_solving.get("max_iterations", 6),)
+        kwargs["track_iterations"] = cf_solving["track_iterations"]
+        kwargs["min_iterations"] = cf_solving["min_iterations"]
+        kwargs["max_iterations"] = cf_solving["max_iterations"]
+        if cf_solving["post_discretization"].pop("enable"):
+            logger.info("Add post-discretization parameters.")
+            kwargs.update(cf_solving["post_discretization"])
         status, condition = n.optimize.optimize_transmission_expansion_iteratively(
             **kwargs
         )