Use greater than or less than instead of ==

Author: staadecker

.gitignore

@@ -2,9 +2,6 @@
 # Edit at https://www.toptal.com/developers/gitignore?templates=macos,python,venv,data,visualstudiocode,pycharm,jupyternotebooks,dotenv,virtualenv
 
 ### Data ###
-*.csv
-# Don't ignore data in switch_model.csv
-!switch_model/**/*.csv
 *.dat
 *.efx
 *.gbr
@@ -18,8 +15,11 @@
 *.vcf
 *.xml
 *.pickle
+examples/**/temp/**
+examples/**/outputs/*.csv
+examples/**/outputs/*.txt
+examples/**/graphs/*.png
 examples/**/info.txt
-examples/**/*.png
 
 ### dotenv ###
 .env

switch_model/policies/wind_to_solar_ratio.py

@@ -3,17 +3,20 @@
 
 It takes in wind_to_solar_ratio.csv that has the following format
 
-PERIOD,wind_to_solar_ratio
-2020,.
-2030,0.5
-2040,1
-2050,1.5
+PERIOD,wind_to_solar_ratio,wind_to_solar_ratio_const_gt
+2020,.,.
+2030,0.5,0
+2040,1,0
+2050,1.5,1
 
 Here when wind_to_solar_ratio is specified (i.e. not '.') a constraint is activated that enforces that
 
-Online wind capacity = Online solar capacity * wind_to_solar_ratio
+Online wind capacity >=/<= Online solar capacity * wind_to_solar_ratio
 
 for the entire period.
+
+When wind_to_solar_ratio_const_gt is true (1) the constraint is a >= constraint.
+When wind_to_solar_ratio_const_gt is False (0) the constraint is a <= constraint.
 """
 import os
 
@@ -30,51 +33,77 @@ def define_components(mod):
     mod.WindCapacity = Expression(
         mod.PERIODS,
         rule=lambda m, p: sum(
-            m.GenCapacity[g, p] for g in m.VARIABLE_GENS if m.gen_energy_source[g] == _WIND_ENERGY_TYPE
-        )
+            m.GenCapacity[g, p]
+            for g in m.VARIABLE_GENS
+            if m.gen_energy_source[g] == _WIND_ENERGY_TYPE
+        ),
     )
 
     mod.SolarCapacity = Expression(
         mod.PERIODS,
         rule=lambda m, p: sum(
-            m.GenCapacity[g, p] for g in m.VARIABLE_GENS if m.gen_energy_source[g] == _SOLAR_ENERGY_TYPE
-        )
+            m.GenCapacity[g, p]
+            for g in m.VARIABLE_GENS
+            if m.gen_energy_source[g] == _SOLAR_ENERGY_TYPE
+        ),
     )
 
     mod.wind_to_solar_ratio = Param(
         mod.PERIODS,
         default=0,  # 0 means the constraint is inactive
-        within=NonNegativeReals
+        within=NonNegativeReals,
     )
 
+    mod.wind_to_solar_ratio_const_gt = Param(mod.PERIODS, default=True, within=Boolean)
+
     # We use a scaling factor to improve the numerical properties
     # of the model.
     # Learn more by reading the documentation on Numerical Issues.
     # 1e-3 was picked since this value is normally on the order of GW instead of MW
     scaling_factor = 1e-3
+
+    def wind_to_solar_ratio_const_rule(m, p):
+        if m.wind_to_solar_ratio[p] == 0:  # 0 means Constraint is inactive
+            return Constraint.Skip
+
+        lhs = m.WindCapacity[p] * scaling_factor
+        rhs = m.SolarCapacity[p] * m.wind_to_solar_ratio[p] * scaling_factor
+        if m.wind_to_solar_ratio_const_gt[p]:
+            return lhs >= rhs
+        else:
+            return lhs <= rhs
+
     mod.wind_to_solar_ratio_const = Constraint(
-        mod.PERIODS,
-        rule=lambda m, p: Constraint.skip if m.wind_to_solar_ratio == 0 else (
-                m.WindCapacity[p] * scaling_factor == m.SolarCapacity[p] * m.wind_to_solar_ratio[p] * scaling_factor
-        )
+        mod.PERIODS, rule=wind_to_solar_ratio_const_rule
     )
 
 
 def load_inputs(mod, switch_data, inputs_dir):
     switch_data.load_aug(
-        index=mod.PERIODS,
-        filename=os.path.join(inputs_dir, 'wind_to_solar_ratio.csv'),
+        filename=os.path.join(inputs_dir, "wind_to_solar_ratio.csv"),
         auto_select=True,
-        param=(mod.wind_to_solar_ratio,),
-        optional=True
+        param=(mod.wind_to_solar_ratio, mod.wind_to_solar_ratio_const_gt),
+        optional=True,  # We want to allow including this module even if the file isn't there
     )
 
 
 def post_solve(m, outdir):
-    df = pd.DataFrame({
-                          "WindCapacity (GW)": value(m.WindCapacity[p]) / 1000,
-                          "SolarCapacity (GW)": value(m.SolarCapacity[p]) / 1000,
-                          "ComputedRatio": value(m.WindCapacity[p] / m.SolarCapacity[p]),
-                          "ExpectedRatio": value(m.wind_to_solar_ratio[p])
-                      } for p in m.PERIODS if m.wind_to_solar_ratio[p] != 0)
-    write_table(m, output_file=os.path.join(outdir, "wind_to_solar_ratio.csv"), df=df, index=False)
+    df = pd.DataFrame(
+        {
+            "WindCapacity (GW)": value(m.WindCapacity[p]) / 1000,
+            "SolarCapacity (GW)": value(m.SolarCapacity[p]) / 1000,
+            "ComputedRatio": value(m.WindCapacity[p] / m.SolarCapacity[p])
+            if value(m.SolarCapacity[p]) != 0
+            else ".",
+            "ExpectedRatio": value(m.wind_to_solar_ratio[p])
+            if m.wind_to_solar_ratio[p] != 0
+            else ".",
+        }
+        for p in m.PERIODS
+    )
+    write_table(
+        m,
+        output_file=os.path.join(outdir, "wind_to_solar_ratio.csv"),
+        df=df,
+        index=False,
+    )

switch_model/utilities/__init__.py

@@ -636,14 +636,21 @@ def load_aug(
         switch_data.load(**kwds)
         return
 
+    # Use our custom DataManager to allow 'inf' in csvs.
+    if extension == ".csv":
+        kwds["using"] = "switch_csv"
+
     # copy the optional_params to avoid side-effects when the list is altered below
     optional_params = list(optional_params)
     # Parse header and first row
     with open(path) as infile:
         headers_line = infile.readline()
         second_line = infile.readline()
-    file_is_empty = headers_line == ""
-    file_has_no_data_rows = second_line == ""
+
+    # Skip if the file is empty.
+    if optional and headers_line == "":
+        return
+
     suffix = path.split(".")[-1]
     if suffix in {"tab", "tsv"}:
         separator = "\t"
@@ -653,9 +660,7 @@ def load_aug(
         raise InputError(f"Unrecognized file type for input file {path}")
     # TODO: parse this more formally, e.g. using csv module
     headers = headers_line.strip().split(separator)
-    # Skip if the file is empty.
-    if optional and file_is_empty:
-        return
+
     # Try to get a list of parameters. If param was given as a
     # singleton or a tuple, make it into a list that can be edited.
     params = []
@@ -740,14 +745,11 @@ def load_aug(
             del kwds["select"][i]
             del kwds["param"][p_i]
 
-    if optional and file_has_no_data_rows:
-        # Skip the file.  Note that we are only doing this after having
+    if optional and second_line == "":
+        # Skip the file if it has no data.  Note that we are only doing this after having
         # validated the file's column headings.
         return
 
-    # Use our custom DataManager to allow 'inf' in csvs.
-    if kwds["filename"][-4:] == ".csv":
-        kwds["using"] = "switch_csv"
     # All done with cleaning optional bits. Pass the updated arguments
     # into the DataPortal.load() function.
     switch_data.load(**kwds)

switch_model/wecc/get_inputs.py

@@ -12,6 +12,7 @@
 import argparse
 import os
 import shutil
+import warnings
 from typing import Iterable, List
 
 # Switch packages
@@ -69,6 +70,8 @@ def write_csv(data: Iterable[List], fname, headers: List[str], log=True):
     "switch_model.policies.carbon_policies",
     "switch_model.policies.rps_unbundled",
     # "switch_model.reporting.basic_exports_wecc",
+    # Always include since by default it does nothing except output useful data
+    "switch_model.policies.wind_to_solar_ratio",
 ]
 
 
@@ -901,14 +904,31 @@ def query_db(full_config, skip_cf):
 
 
 def write_wind_to_solar_ratio(wind_to_solar_ratio):
+    # TODO ideally we'd have a table where we can specify the wind_to_solar_ratios per period.
+    #   At the moment only the wind_to_solar_ratio is specified and which doesn't allow different values per period
     if wind_to_solar_ratio is None:
         return
 
-    print("wind_to_solar_ratio.csv")
+    print("wind_to_solar_ratio.csv...")
     df = pd.read_csv("periods.csv")[["INVESTMENT_PERIOD"]]
     df["wind_to_solar_ratio"] = wind_to_solar_ratio
+
+    # wind_to_solar_ratio.csv requires a column called wind_to_solar_ratio_const_gt that is True (1) or False (0)
+    # This column specifies whether the constraint is a greater than constraint or a less than constraint.
+    # In our case we want it to be a greater than constraint if we're trying to force wind-to-solar ratio above its default
+    # and we want it to be a less than constraint if we're trying to force the ratio below its default.
+    # Here the default is the ratio if we didn't have the constraint.
+    cutoff_ratio = 0.28
+    warnings.warn(
+        "To determine the sign of the wind-to-solar ratio constraint we have "
+        f"assumed that without the constraint, the wind-to-solar ratio is {cutoff_ratio}. "
+        f"This value was accurate for Martin's LDES runs however it may not be accurate for you. "
+        f"You should update this value in get_inputs or manually specify whether you want a greater than "
+        f"or a less than constraint."
+    )
+    df["wind_to_solar_ratio_const_gt"] = 1 if wind_to_solar_ratio > cutoff_ratio else 0
+
     df.to_csv("wind_to_solar_ratio.csv", index=False)
-    modules.append("switch_model.policies.wind_to_solar_ratio")
 
 
 def ca_policies(db_cursor, ca_policies_scenario_id, study_timeframe_id):