Fix lead time when consequential

Fix inter year in fuels.py
Version bump

docs/consequential.rst

@@ -51,12 +51,14 @@ Range time
 
 Integer. Years. To measure the trend around the point where the additional
 capital will be installed, a range of n years before and after the point
-is taken as the time interval.
+is taken as the time interval. Note that if set to a value other than 0,
+the duration argument must be set to 0.
 
 Duration
 ^^^^^^^^
 
 Integer. Years. Duration over which the change in demand should be measured.
+Note that if set to a value other than 0, the range time argument must be set to 0.
 
 Foresight
 ^^^^^^^^^

premise/__init__.py

@@ -1,5 +1,5 @@
 __all__ = ("NewDatabase", "clear_cache", "get_regions_definition")
-__version__ = (1, 6, 1)
+__version__ = (1, 6, 2)
 
 from pathlib import Path
 

premise/data/consequential/blacklist.yaml

@@ -5,43 +5,19 @@
 # if it is present, the activity is replaced by the activity
 # specified in the `replacement` field.
 ---
-- name: electricity production, at co-generation power plant/hard coal, oxy, pipeline 200km, storage 1000m
+- name: electricity production, at co-generation hard coal-fired power plant, post, pipeline 200km, storage 1000m
   reference product: electricity, high voltage
   unit: kilowatt hour
-- name: electricity production, at co-generation power plant/hard coal, oxy, pipeline 400km, storage 3000m
-  reference product: electricity, high voltage
-  unit: kilowatt hour
-- name: electricity production, at co-generation power plant/hard coal, post, pipeline 200km, storage 1000m
-  reference product: electricity, high voltage
-  unit: kilowatt hour
-- name: electricity production, at co-generation power plant/hard coal, post, pipeline 400km, storage 1000m
-  reference product: electricity, high voltage
-  unit: kilowatt hour
-- name: electricity production, at co-generation power plant/hard coal, post, pipeline 400km, storage 3000m
-  reference product: electricity, high voltage
-  unit: kilowatt hour
-- name: electricity production, at co-generation power plant/hard coal, pre, pipeline 200km, storage 1000m
-  reference product: electricity, high voltage
-  unit: kilowatt hour
-- name: electricity production, at co-generation power plant/hard coal, pre, pipeline 400km, storage 3000m
-  reference product: electricity, high voltage
-  unit: kilowatt hour
-- name: electricity production, at co-generation power plant/wood, post, pipeline 200km, storage 1000m
-  reference product: electricity, high voltage
-  unit: kilowatt hour
-- name: electricity production, at co-generation power plant/wood, post, pipeline 400km, storage 3000m
-  reference product: electricity, high voltage
-  unit: kilowatt hour
-- name: electricity production, at co-generation power plant/natural gas, post, pipeline 200km, storage 1000m
-  reference product: electricity, high voltage
-  unit: kilowatt hour
-- name: electricity production, at co-generation power plant/natural gas, pre, pipeline 200km, storage 1000m
+
+- name: electricity production, at co-generation wood-fired power plant, post, pipeline 200km, storage 1000m
   reference product: electricity, high voltage
   unit: kilowatt hour
-- name: electricity production, at co-generation power plant/oil, post, pipeline 200km, storage 1000m
+
+- name: electricity production, at co-generation natural gas-fired power plant, post, pipeline 200km, storage 1000m
   reference product: electricity, high voltage
   unit: kilowatt hour
-- name: electricity production, at co-generation power plant/oil, pre, pipeline 200km, storage 1000m
+
+- name: electricity production, at co-generation oil-fired power plant, post, pipeline 200km, storage 1000m
   reference product: electricity, high voltage
   unit: kilowatt hour
 
@@ -117,6 +93,24 @@
       reference product: heat, central or small-scale, other than natural gas
       location: CH
 
+- name: heat and power co-generation, hard coal
+  reference product: electricity, high voltage
+  unit: kilowatt hour
+  location: DE
+  replacement:
+    name: electricity production, hard coal
+    reference product: electricity, high voltage
+    location: DE
+
+- name: heat and power co-generation, oil
+  reference product: electricity, high voltage
+  unit: kilowatt hour
+  location: DE
+  replacement:
+    name: electricity production, oil
+    reference product: electricity, high voltage
+    location: DE
+
 - name: air separation, cryogenic
   reference product: nitrogen, liquid
   unit: kilogram

premise/data/consequential/leadtimes.yaml

@@ -17,20 +17,26 @@ Gas CC: 3
 Gas CC CCS: 3
 Gas CHP: 3
 Gas CHP CCS: 3
+Gas ST: 3
 Oil ST: 3
 Oil CC CCS: 3
 Oil CC: 3
 Oil CHP CCS: 3
 Oil CHP: 3
+Foil ST: 3
 Geothermal: 3
 Hydro: 4
 Hydrogen: 3
 Nuclear: 7
+Nuclear_EPR: 7
+Nuclear_SMR: 7
 Solar CSP: 3
+Solar CSP autonomous: 3
 Solar PV Centralized: 2
 Solar PV Residential: 2
 Wind Onshore: 2
 Wind Offshore: 3
+Wave: 3
 diesel: 3
 gasoline: 3
 diesel, synthetic, from wood: 3
@@ -65,3 +71,11 @@ hydrogen, biomass, with CCS: 3
 hydrogen, coal: 3
 hydrogen, nat. gas: 3
 hydrogen, nat. gas, with CCS: 3
+hydrogen, coal, with CCS: 3
+hydrogen, solar: 3
+cement, dry feed rotary kiln: 10
+steel - primary: 10
+steel - secondary: 10
+daccs_sorbent: 3
+biomass - residual: 3
+biomass crops - purpose grown: 3

premise/data/consequential/lifetimes.yaml

@@ -17,6 +17,7 @@ Gas CC: 35
 Gas CC CCS: 35
 Gas CHP: 35
 Gas CHP CCS: 35
+Gas ST: 35
 Oil ST: 25
 Oil CC CCS: 25
 Oil CC: 25
@@ -26,11 +27,16 @@ Geothermal: 30
 Hydro: 130
 Hydrogen: 35
 Nuclear: 40
+Nuclear_EPR: 40
+Nuclear_SMR: 40
+Foil ST: 25
 Solar CSP: 30
+Solar CSP autonomous: 30
 Solar PV Centralized: 30
 Solar PV Residential: 30
 Wind Onshore: 25
 Wind Offshore: 25
+Wave: 25
 diesel: 35
 gasoline: 35
 diesel, synthetic, from wood: 35
@@ -64,4 +70,12 @@ hydrogen, biomass: 35
 hydrogen, biomass, with CCS: 35
 hydrogen, coal: 35
 hydrogen, nat. gas: 35
-hydrogen, nat. gas, with CCS: 35
+hydrogen, nat. gas, with CCS: 35
+hydrogen, coal, with CCS: 35
+hydrogen, solar: 35
+cement, dry feed rotary kiln: 40
+steel - primary: 40
+steel - secondary: 40
+daccs_sorbent: 20
+biomass - residual: 35
+biomass crops - purpose grown: 35

premise/data_collection.py

@@ -411,7 +411,9 @@ def __init__(
         )
 
         self.electricity_markets = self.__fetch_market_data(
-            data=data, input_vars=electricity_prod_vars
+            data=data,
+            input_vars=electricity_prod_vars,
+            system_model=self.system_model,
         )
 
         self.petrol_markets = self.__fetch_market_data(
@@ -421,6 +423,7 @@ def __init__(
                 for k, v in fuel_prod_vars.items()
                 if any(x in k for x in ["gasoline", "ethanol", "methanol"])
             },
+            system_model=self.system_model,
         )
         if self.petrol_markets is not None:
             # divide the volume of "gasoline" by 2
@@ -442,6 +445,7 @@ def __init__(
                     ]
                 )
             },
+            system_model=self.system_model,
         )
         if self.diesel_markets is not None:
             # divide the volume of "gasoline" by 2
@@ -458,6 +462,7 @@ def __init__(
                 for k, v in fuel_prod_vars.items()
                 if any(x in k for x in ["biogas", "methane", "natural gas"])
             },
+            system_model=self.system_model,
         )
 
         self.hydrogen_markets = self.__fetch_market_data(
@@ -472,17 +477,18 @@ def __init__(
                     ]
                 )
             },
+            system_model=self.system_model,
         )
 
         self.cement_markets = self.__fetch_market_data(
-            data=data, input_vars=cement_prod_vars
+            data=data, input_vars=cement_prod_vars, system_model="cutoff"
         )
         self.steel_markets = self.__fetch_market_data(
-            data=data, input_vars=steel_prod_vars
+            data=data, input_vars=steel_prod_vars, system_model="cutoff"
         )
-        self.dac_markets = self.__fetch_market_data(data=data, input_vars=dac_prod_vars)
+        self.dac_markets = self.__fetch_market_data(data=data, input_vars=dac_prod_vars, system_model="cutoff")
         self.biomass_markets = self.__fetch_market_data(
-            data=data, input_vars=biomass_prod_vars
+            data=data, input_vars=biomass_prod_vars, system_model="cutoff"
         )
 
         self.carbon_capture_rate = self.__get_carbon_capture_rate(
@@ -496,6 +502,7 @@ def __init__(
             data=data,
             input_vars=other_vars,
             normalize=False,
+            system_model = "cutoff"
         )
 
         self.electricity_efficiencies = self.get_iam_efficiencies(
@@ -707,7 +714,7 @@ def __get_iam_data(
         return array
 
     def __fetch_market_data(
-        self, data: xr.DataArray, input_vars: dict, normalize: bool = True
+        self, data: xr.DataArray, input_vars: dict, system_model: str, normalize: bool = True,
     ) -> [xr.DataArray, None]:
         """
         This method retrieves the market share for each technology,
@@ -742,7 +749,7 @@ def __fetch_market_data(
             rev_input_vars[v] for v in market_data.variables.values
         ]
 
-        if self.system_model == "consequential":
+        if system_model == "consequential":
             market_data = consequential_method(
                 market_data, self.year, self.system_model_args
             )

premise/electricity.py

@@ -1506,6 +1506,8 @@ def create_biomass_markets(self) -> None:
                         0,
                         1,
                     )
+                elif self.system_model == "consequential" and biomass_type == "biomass - residual":
+                    share = 0
                 else:
                     share = 0
 

premise/fuels.py

@@ -2195,8 +2195,8 @@ def generate_regional_fuel_market(
 
         if (
             self.iam_fuel_markets.sel(
-                region=region, variables=prod_vars, year=self.year
-            ).sum(dim=["variables"])
+                region=region, variables=prod_vars
+            ).interp(year=self.year).sum(dim=["variables"])
             == 0
         ):
             print("No fuel market for", dataset["name"], "in", region)

premise/marginal_mixes.py

@@ -48,7 +48,15 @@ def get_leadtime(list_tech: Tuple) -> np.ndarray:
     with open(IAM_LEADTIMES, "r", encoding="utf-8") as stream:
         dict_ = yaml.safe_load(stream)
 
-    dict_ = {k: v for k, v in dict_.items() if k in list(list_tech)}
+    # check that all technologies have a lead-time
+    if not all([k in dict_.keys() for k in list_tech]):
+        raise ValueError(
+            f"Not all technologies have a lead-time. "
+            f"Missing technologies: {set(list_tech) - set(dict_.keys())}"
+        )
+    dict_ = {k: dict_[k] for k in list(list_tech)}
+
+
     return np.array(list(dict_.values()), dtype=float)
 
 
@@ -203,12 +211,12 @@ def consequential_method(data: xr.DataArray, year: int, args: dict) -> xr.DataAr
             },
             (False, False, False, True): {
                 "start": year,
-                "end": year + leadtime,
+                "end": year + fetch_avg_leadtime(leadtime, shares),
                 "start_avg": year,
                 "end_avg": year + fetch_avg_lifetime(lifetime=leadtime, shares=shares),
             },
             (False, False, True, True): {
-                "start": year - leadtime,
+                "start": year - fetch_avg_leadtime(leadtime, shares),
                 "end": year,
                 "start_avg": year
                 - fetch_avg_lifetime(lifetime=leadtime, shares=shares),
@@ -227,8 +235,8 @@ def consequential_method(data: xr.DataArray, year: int, args: dict) -> xr.DataAr
                 "end_avg": year + range_time,
             },
             (True, False, False, True): {
-                "start": year + leadtime - range_time,
-                "end": year + leadtime + range_time,
+                "start": year + fetch_avg_leadtime(leadtime, shares) - range_time,
+                "end": year + fetch_avg_leadtime(leadtime, shares) + range_time,
                 "start_avg": year + fetch_avg_leadtime(leadtime, shares) - range_time,
                 "end_avg": year + fetch_avg_leadtime(leadtime, shares) + range_time,
             },
@@ -251,8 +259,8 @@ def consequential_method(data: xr.DataArray, year: int, args: dict) -> xr.DataAr
                 "end_avg": year + duration,
             },
             (False, True, False, True): {
-                "start": year + leadtime,
-                "end": year + leadtime + duration,
+                "start": year + fetch_avg_leadtime(leadtime, shares),
+                "end": year + fetch_avg_leadtime(leadtime, shares) + duration,
                 "start_avg": year + fetch_avg_leadtime(leadtime, shares),
                 "end_avg": year + fetch_avg_leadtime(leadtime, shares) + duration,
             },
@@ -281,8 +289,9 @@ def consequential_method(data: xr.DataArray, year: int, args: dict) -> xr.DataAr
 
         except KeyError:
             print(
-                "The combination of range_time, duration, foresight, and lead_time "
-                "is not possible. Please check your input."
+                f"The combination of range_time, duration, foresight, and lead_time {range_time, duration, foresight, lead_time} "
+                "is not possible. Please check your input. Specifically, if `range_time` is non-null, `duration` must be null, "
+                "and vice versa."
             )
             continue
 

setup.py

@@ -32,7 +32,7 @@ def package_files(directory):
 
 setup(
     name="premise",
-    version="1.6.1",
+    version="1.6.2",
     python_requires=">=3.9,<3.11",
     packages=packages,
     author="Romain Sacchi <[email protected]>, Alois Dirnaichner <[email protected]>, Chris Mutel "