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Merged
FelixCAAuer merged 15 commits into from
Jul 25, 2025
Merged

Long-Duration Storage and RoR implementation #7

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300db6a
Sort TableDefinitions and changelog alphabetically
FelixCAAuer Jul 24, 2025
d4622d3
Sort tests alphabetically
FelixCAAuer Jul 24, 2025
b606018
Add Power_Storage to TableDefinitions
FelixCAAuer Jul 24, 2025
a75a8d5
Remove RoR (RoR is moved to VRES, long-duration to storage)
FelixCAAuer Jul 24, 2025
52ab509
Add Power_Inflows to TableDefinitions
FelixCAAuer Jul 24, 2025
9a2c480
Sort functions in ExcelReader and -Writer alphabetically
FelixCAAuer Jul 24, 2025
a9fdebf
Remove unused do_not_convert_values from ExcelReader
FelixCAAuer Jul 24, 2025
76fbc3b
Update list of files in ExcelWriter (when called as main)
FelixCAAuer Jul 24, 2025
ad9e946
Add Power_Inflows to changelog, move Power_Network to alphabetical pos.
FelixCAAuer Jul 24, 2025
40fa005
Add switch to fail on wrong version when reading Excel files
FelixCAAuer Jul 24, 2025
31e8e89
Fix wrong file selection for Inflows & Storage, fix scaling for Inflows
FelixCAAuer Jul 24, 2025
64944b2
Improve read-in handling for Power_Inflows and Power_VRES_Profiles
FelixCAAuer Jul 24, 2025
402a1d0
Add safety check for Power_Storage
FelixCAAuer Jul 24, 2025
58d8907
Add check to only include existing or investable generators
FelixCAAuer Jul 25, 2025
da53886
Fix typo in warning message (found by Copilot)
FelixCAAuer Jul 25, 2025
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94 changes: 20 additions & 74 deletions CaseStudy.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import copy
import os
import warnings
from typing import Optional, Self

Expand All @@ -20,7 +21,6 @@ def __init__(self,
power_businfo_file: str = "Power_BusInfo.xlsx", dPower_BusInfo: pd.DataFrame = None,
power_network_file: str = "Power_Network.xlsx", dPower_Network: pd.DataFrame = None,
power_thermalgen_file: str = "Power_ThermalGen.xlsx", dPower_ThermalGen: pd.DataFrame = None,
power_ror_file: str = "Power_RoR.xlsx", dPower_RoR: pd.DataFrame = None,
power_vres_file: str = "Power_VRES.xlsx", dPower_VRES: pd.DataFrame = None,
power_demand_file: str = "Power_Demand.xlsx", dPower_Demand: pd.DataFrame = None,
power_inflows_file: str = "Power_Inflows.xlsx", dPower_Inflows: pd.DataFrame = None,
Expand Down Expand Up @@ -98,19 +98,6 @@ def __init__(self,
self.power_thermalgen_file = power_thermalgen_file
self.dPower_ThermalGen = ExcelReader.get_dPower_ThermalGen(self.data_folder + self.power_thermalgen_file)

if self.dPower_Parameters["pEnableRoR"]:
if dPower_RoR is not None:
self.dPower_RoR = dPower_RoR
else:
self.power_ror_file = power_ror_file
self.dPower_RoR = self.get_dPower_RoR()

if dPower_Inflows is not None:
self.dPower_Inflows = dPower_Inflows
else:
self.power_inflows_file = power_inflows_file
self.dPower_Inflows = self.get_dPower_Inflows()

if self.dPower_Parameters["pEnableVRES"]:
if dPower_VRES is not None:
self.dPower_VRES = dPower_VRES
Expand All @@ -120,7 +107,7 @@ def __init__(self,

if dPower_VRESProfiles is not None:
self.dPower_VRESProfiles = dPower_VRESProfiles
else:
elif os.path.isfile(self.data_folder + power_vresprofiles_file):
self.power_vresprofiles_file = power_vresprofiles_file
self.dPower_VRESProfiles = ExcelReader.get_dPower_VRESProfiles(self.data_folder + self.power_vresprofiles_file)

Expand All @@ -129,7 +116,14 @@ def __init__(self,
self.dPower_Storage = dPower_Storage
else:
self.power_storage_file = power_storage_file
self.dPower_Storage = self.get_dPower_Storage()
self.dPower_Storage = ExcelReader.get_dPower_Storage(self.data_folder + self.power_storage_file)

if self.dPower_Parameters["pEnableVRES"] or self.dPower_Parameters["pEnableStorage"]:
if dPower_Inflows is not None:
self.dPower_Inflows = dPower_Inflows
elif os.path.isfile(self.data_folder + power_inflows_file):
self.power_inflows_file = power_inflows_file
self.dPower_Inflows = ExcelReader.get_dPower_Inflows(self.data_folder + self.power_inflows_file)

if self.dPower_Parameters["pEnablePowerImportExport"]:
if dPower_ImpExpHubs is not None:
Expand Down Expand Up @@ -169,8 +163,7 @@ def scale_CaseStudy(self):
if self.dPower_Parameters["pEnableThermalGen"]:
self.scale_dPower_ThermalGen()

if self.dPower_Parameters["pEnableRoR"]:
self.scale_dPower_RoR()
if self.dPower_Inflows is not None:
self.scale_dPower_Inflows()

if self.dPower_Parameters["pEnableVRES"]:
Expand Down Expand Up @@ -209,7 +202,6 @@ def scale_dPower_Demand(self):
self.dPower_Demand["value"] *= self.power_scaling_factor

def scale_dPower_ThermalGen(self):
self.dPower_ThermalGen = self.dPower_ThermalGen[self.dPower_ThermalGen["excl"].isnull()] # Only keep rows that are not excluded (i.e., have no value in the "Excl." column)
self.dPower_ThermalGen = self.dPower_ThermalGen[(self.dPower_ThermalGen["ExisUnits"] > 0) | (self.dPower_ThermalGen["EnableInvest"] > 0)] # Filter out all generators that are not existing and not investable

self.dPower_ThermalGen['EFOR'] = self.dPower_ThermalGen['EFOR'].fillna(0) # Fill NaN values with 0 for EFOR
Expand Down Expand Up @@ -243,17 +235,11 @@ def scale_dPower_ThermalGen(self):
self.dPower_ThermalGen['Qmin'] = self.dPower_ThermalGen['Qmin'].fillna(0) * self.reactive_power_scaling_factor
self.dPower_ThermalGen['Qmax'] = self.dPower_ThermalGen['Qmax'].fillna(0) * self.reactive_power_scaling_factor

def scale_dPower_RoR(self):
self.dPower_RoR['InvestCostEUR'] = self.dPower_RoR['MaxProd'] * self.power_scaling_factor * (self.dPower_RoR['InvestCostPerMW'] + self.dPower_RoR['InvestCostPerMWh'] * self.dPower_RoR['Ene2PowRatio']) * (self.cost_scaling_factor / self.power_scaling_factor)
self.dPower_RoR['MaxProd'] *= self.power_scaling_factor

self.dPower_RoR['Qmin'] = self.dPower_RoR['Qmin'].fillna(0) * self.reactive_power_scaling_factor
self.dPower_RoR['Qmax'] = self.dPower_RoR['Qmax'].fillna(0) * self.reactive_power_scaling_factor

def scale_dPower_Inflows(self):
self.dPower_Inflows["Inflow"] *= self.power_scaling_factor
self.dPower_Inflows["value"] *= self.power_scaling_factor

def scale_dPower_VRES(self):
self.dPower_VRES = self.dPower_VRES[(self.dPower_VRES["ExisUnits"] > 0) | ((self.dPower_VRES["EnableInvest"] > 0) & (self.dPower_VRES["MaxInvest"] > 0))] # Filter out all generators that are not existing and not investable
if "MinProd" not in self.dPower_VRES.columns:
self.dPower_VRES['MinProd'] = 0

Expand All @@ -265,6 +251,7 @@ def scale_dPower_VRES(self):
self.dPower_VRES['Qmax'] = self.dPower_VRES['Qmax'].fillna(0) * self.reactive_power_scaling_factor

def scale_dPower_Storage(self):
self.dPower_Storage = self.dPower_Storage[(self.dPower_Storage["ExisUnits"] > 0) | ((self.dPower_Storage["EnableInvest"] > 0) & (self.dPower_Storage["MaxInvest"] > 0))] # Filter out all generators that are not existing and not investable
self.dPower_Storage['IniReserve'] = self.dPower_Storage['IniReserve'].fillna(0)
self.dPower_Storage['MinReserve'] = self.dPower_Storage['MinReserve'].fillna(0)
self.dPower_Storage['MinProd'] = self.dPower_Storage["MinProd"].fillna(0)
Expand All @@ -276,6 +263,10 @@ def scale_dPower_Storage(self):
self.dPower_Storage['Qmin'] = self.dPower_Storage['Qmin'].fillna(0) * self.reactive_power_scaling_factor
self.dPower_Storage['Qmax'] = self.dPower_Storage['Qmax'].fillna(0) * self.reactive_power_scaling_factor

# Check if any DisEffic or ChEffic is nan, if so, raise an error
if self.dPower_Storage['DisEffic'].isna().any() or self.dPower_Storage['ChEffic'].isna().any():
raise ValueError("DisEffic and ChEffic in 'Power_Storage.xlsx' must not contain NaN values. Please check the data.")

def scale_dPower_ImpExpHubs(self):
self.dPower_ImpExpHubs["Pmax Import"] *= self.power_scaling_factor
self.dPower_ImpExpHubs["Pmax Export"] *= self.power_scaling_factor
Expand All @@ -302,7 +293,7 @@ def get_dPower_Parameters(self):
dPower_Parameters = dPower_Parameters.dropna(how="all")
dPower_Parameters = dPower_Parameters.set_index('General')

self.yesNo_to_bool(dPower_Parameters, ['pEnableChDisPower', 'pFixStInterResToIniReserve', 'pEnableSoftLineLoadLimits', 'pEnableThermalGen', 'pEnableRoR', 'pEnableVRES', 'pEnableStorage', 'pEnablePowerImportExport', 'pEnableSOCP'])
self.yesNo_to_bool(dPower_Parameters, ['pEnableChDisPower', 'pFixStInterResToIniReserve', 'pEnableSoftLineLoadLimits', 'pEnableThermalGen', 'pEnableVRES', 'pEnableStorage', 'pEnablePowerImportExport', 'pEnableSOCP'])

# Transform to make it easier to access values
dPower_Parameters = dPower_Parameters.drop(dPower_Parameters.columns[1:], axis=1) # Drop all columns but "Value" (rest is just for information in the Excel)
Expand All @@ -322,34 +313,6 @@ def yesNo_to_bool(df: pd.DataFrame, columns_to_be_changed: list[str]):
raise ValueError(f"Value for {column} must be either 'Yes' or 'No'.")
return df

def get_dPower_RoR(self):
dPower_RoR = self.read_generator_data(self.data_folder + self.power_ror_file)

# If column 'scenario' is not present, add it
if 'scenario' not in dPower_RoR.columns:
dPower_RoR['scenario'] = 'ScenarioA' # TODO: Fill this dynamically, once the Excel file is updated
return dPower_RoR

def get_dPower_Storage(self):
dPower_Storage = self.read_generator_data(self.data_folder + self.power_storage_file)

# If column 'scenario' is not present, add it
if 'scenario' not in dPower_Storage.columns:
dPower_Storage['scenario'] = 'ScenarioA' # TODO: Fill this dynamically, once the Excel file is updated
return dPower_Storage

def get_dPower_Inflows(self):
dPower_Inflows = pd.read_excel(self.data_folder + self.power_inflows_file, skiprows=[0, 1, 3, 4, 5])
dPower_Inflows = dPower_Inflows.drop(dPower_Inflows.columns[0], axis=1)
dPower_Inflows = dPower_Inflows.rename(columns={dPower_Inflows.columns[0]: "rp", dPower_Inflows.columns[1]: "g"})
dPower_Inflows = dPower_Inflows.melt(id_vars=['rp', 'g'], var_name='k', value_name='Inflow')
dPower_Inflows = dPower_Inflows.set_index(['rp', 'g', 'k'])

# If column 'scenario' is not present, add it
if 'scenario' not in dPower_Inflows.columns:
dPower_Inflows['scenario'] = 'ScenarioA' # TODO: Fill this dynamically, once the Excel file is updated
return dPower_Inflows

def get_dPower_ImpExpHubs(self):
dPower_ImpExpHubs = pd.read_excel(self.data_folder + self.power_impexphubs_file, skiprows=[0, 1, 3, 4, 5])
dPower_ImpExpHubs = dPower_ImpExpHubs.drop(dPower_ImpExpHubs.columns[0], axis=1)
Expand Down Expand Up @@ -531,12 +494,6 @@ def merge_single_node_buses(self):
row['i'] = new_bus_name
self.dPower_ThermalGen.loc[i] = row

# Adapt dPower_RoR
for i, row in self.dPower_RoR.iterrows():
if row['i'] in connected_buses:
row['i'] = new_bus_name
self.dPower_RoR.loc[i] = row

# Adapt dPower_VRES
for i, row in self.dPower_VRES.iterrows():
if row['i'] in connected_buses:
Expand Down Expand Up @@ -567,16 +524,6 @@ def merge_single_node_buses(self):
self.dPower_VRESProfiles = self.dPower_VRESProfiles.groupby(['rp', 'i', 'k', 'tec']).mean() # TODO: Aggregate using more complex method (capacity * productionCapacity * ... * / Total Production Capacity)
self.dPower_VRESProfiles.sort_index(inplace=True)

# Function to read generator data
@staticmethod
def read_generator_data(file_path):
d_generator = pd.read_excel(file_path, skiprows=[0, 1, 3, 4, 5])
d_generator = d_generator.drop(d_generator.columns[0], axis=1)
d_generator = d_generator[(d_generator["ExisUnits"] > 0) | (d_generator["EnableInvest"] > 0)] # Filter out all generators that are not existing and not investable
d_generator = d_generator.rename(columns={d_generator.columns[0]: "g", d_generator.columns[1]: "tec", d_generator.columns[2]: "i"})
d_generator = d_generator.set_index('g')
return d_generator

# Create transition matrix from Hindex
def get_rpTransitionMatrices(self):
rps = sorted(self.dPower_Hindex.index.get_level_values('rp').unique().tolist())
Expand Down Expand Up @@ -689,8 +636,7 @@ def filter_scenario(self, scenario_name) -> Self:

if hasattr(caseStudy, "dPower_ThermalGen"):
caseStudy._filter_dataframe("dPower_ThermalGen", scenario_name)
if hasattr(caseStudy, "dPower_RoR") and len(caseStudy.dPower_RoR) > 0:
caseStudy._filter_dataframe("dPower_RoR", scenario_name)
if hasattr(caseStudy, "dPower_Inflows"):
caseStudy._filter_dataframe("dPower_Inflows", scenario_name)
if hasattr(caseStudy, "dPower_VRES"):
caseStudy._filter_dataframe("dPower_VRES", scenario_name)
Expand Down
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