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Feature/integrate tsam no multiple timegrid storage #1058

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Feature/integrate tsam no multiple timegrid storage #1058

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c9a101d
flexibility for storages with no inter_storage_content
MaxHiDLR Feb 28, 2024
afa4a56
added description of multiple_tsam_timegrid to storage
MaxHiDLR Feb 28, 2024
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107 changes: 71 additions & 36 deletions src/oemof/solph/components/_generic_storage.py
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Original file line number Diff line number Diff line change
Expand Up @@ -120,7 +120,9 @@ class GenericStorage(Node):
Determine the lifetime of an outflow; only applicable for multi-period
models which can invest in storage capacity and have an
invest_relation_output_capacity defined

multiple_tsam_timegrid : boolean
Relevant in tsam mode.
If true, inter and intra storage content is considers.
Notes
-----
The following sets, variables, constraints and objective parts are created
Expand Down Expand Up @@ -186,6 +188,7 @@ def __init__(
lifetime_inflow=None,
lifetime_outflow=None,
custom_attributes=None,
multiple_tsam_timegrid=True,
):
if inputs is None:
inputs = {}
Expand Down Expand Up @@ -243,7 +246,7 @@ def __init__(
self.invest_relation_output_capacity = invest_relation_output_capacity
self.lifetime_inflow = lifetime_inflow
self.lifetime_outflow = lifetime_outflow

self.multiple_tsam_timegrid = multiple_tsam_timegrid
# Check number of flows.
self._check_number_of_flows()
# Check for infeasible parameter combinations
Expand Down Expand Up @@ -505,7 +508,17 @@ def _storage_content_bound_rule(block, n, t):
n.nominal_storage_capacity * n.max_storage_level[t],
)
return bounds

def _storage_content_bound_intra_rule(block, n, p, k, g):
"""
Rule definition for bounds of storage_content variable of
storage n in timestep t.
"""
t = m.get_timestep_from_tsam_timestep(p, k, g)
bounds = (
n.nominal_storage_capacity * n.min_storage_level[t],
n.nominal_storage_capacity * n.max_storage_level[t],
)
return bounds
if not m.TSAM_MODE:
self.storage_content = Var(
self.STORAGES, m.TIMEPOINTS, bounds=_storage_content_bound_rule
Expand All @@ -520,23 +533,37 @@ def _storage_content_bound_rule(block, n, t):
)
self.storage_content[n, 0].fix()
else:
self.storage_content_inter = Var(
self.STORAGES, m.CLUSTERS_OFFSET, within=NonNegativeReals
)
self.storage_content_intra = Var(
self.STORAGES, m.TIMEINDEX_TYPICAL_CLUSTER_OFFSET
)
for n in group:
if n.multiple_tsam_timegrid:
self.storage_content_inter = Var(
self.STORAGES, m.CLUSTERS_OFFSET, within=NonNegativeReals
)
self.storage_content_intra = Var(
self.STORAGES, m.TIMEINDEX_TYPICAL_CLUSTER_OFFSET
)
else:
self.storage_content_intra = Var(
self.STORAGES, m.TIMEINDEX_TYPICAL_CLUSTER_OFFSET, bounds=_storage_content_bound_intra_rule
)
# set the initial intra storage content
# first timestep in intra storage is always zero
for n in group:
for p, k in m.TYPICAL_CLUSTERS:
self.storage_content_intra[n, p, k, 0] = 0
self.storage_content_intra[n, p, k, 0].fix()
if n.initial_storage_level is not None:
self.storage_content_inter[n, 0] = (
n.initial_storage_level * n.nominal_storage_capacity
)
self.storage_content_inter[n, 0].fix()
if n.multiple_tsam_timegrid:
self.storage_content_intra[n, p, k, 0] = 0
self.storage_content_intra[n, p, k, 0].fix()
else:
if n.initial_storage_level is not None:
self.storage_content_intra[n, p, k, 0] = n.initial_storage_level * \
n.nominal_storage_capacity
self.storage_content_intra[n, p, k, 0].fix()
if n.initial_storage_level is not None and n.multiple_tsam_timegrid:
self.storage_content_inter[n, 0] = (
n.initial_storage_level * n.nominal_storage_capacity
)
self.storage_content_inter[n, 0].fix()


# ************* Constraints ***************************

def _storage_inter_minimum_level_rule(block):
Expand Down Expand Up @@ -566,13 +593,15 @@ def _storage_inter_minimum_level_rule(block):
)

if m.TSAM_MODE:
self.storage_inter_minimum_level = Constraint(
self.STORAGES, m.TIMEINDEX_CLUSTER, noruleinit=True
)
for n in self.STORAGES:
if n.multiple_tsam_timegrid:
self.storage_inter_minimum_level = Constraint(
self.STORAGES, m.TIMEINDEX_CLUSTER, noruleinit=True
)

self.storage_inter_minimum_level_build = BuildAction(
rule=_storage_inter_minimum_level_rule
)
self.storage_inter_minimum_level_build = BuildAction(
rule=_storage_inter_minimum_level_rule
)

def _storage_inter_maximum_level_rule(block):
for n in self.STORAGES:
Expand All @@ -598,13 +627,15 @@ def _storage_inter_maximum_level_rule(block):
)

if m.TSAM_MODE:
self.storage_inter_maximum_level = Constraint(
self.STORAGES, m.TIMEINDEX_CLUSTER, noruleinit=True
)
for n in self.STORAGES:
if n.multiple_tsam_timegrid:
self.storage_inter_maximum_level = Constraint(
self.STORAGES, m.TIMEINDEX_CLUSTER, noruleinit=True
)

self.storage_inter_maximum_level_build = BuildAction(
rule=_storage_inter_maximum_level_rule
)
self.storage_inter_maximum_level_build = BuildAction(
rule=_storage_inter_maximum_level_rule
)

def _storage_balance_rule(block, n, p, t):
"""
Expand Down Expand Up @@ -702,11 +733,13 @@ def _inter_storage_balance_rule(block, n, i):
return expr == 0

if m.TSAM_MODE:
self.inter_balance = Constraint(
self.STORAGES,
m.CLUSTERS,
rule=_inter_storage_balance_rule,
)
for n in self.STORAGES:
if n.multiple_tsam_timegrid:
self.inter_balance = Constraint(
self.STORAGES,
m.CLUSTERS,
rule=_inter_storage_balance_rule,
)

def _balanced_storage_rule(block, n):
"""
Expand All @@ -733,9 +766,11 @@ def _balanced_inter_storage_rule(block, n):
self.STORAGES_BALANCED, rule=_balanced_storage_rule
)
else:
self.balanced_cstr = Constraint(
self.STORAGES_BALANCED, rule=_balanced_inter_storage_rule
)
for n in self.STORAGES:
if n.multiple_tsam_timegrid:
self.balanced_cstr = Constraint(
self.STORAGES_BALANCED, rule=_balanced_inter_storage_rule
)

def _power_coupled(block):
"""
Expand Down
49 changes: 27 additions & 22 deletions src/oemof/solph/processing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -566,7 +566,6 @@ def _calculate_soc_from_inter_and_intra_soc(soc, storage, tsa_parameters):
t_offset = 0
for p, tsa_period in enumerate(tsa_parameters):
for i, k in enumerate(tsa_period["order"]):
inter_value = soc["inter"].iloc[i_offset + i]["value"]
# Self-discharge has to be taken into account for calculating
# inter SOC for each timestep in cluster
t0 = t_offset + i * tsa_period["timesteps"]
Expand All @@ -581,32 +580,38 @@ def _calculate_soc_from_inter_and_intra_soc(soc, storage, tsa_parameters):
if is_last_timestep
else tsa_period["timesteps"]
)
inter_series = (
pd.Series(
itertools.accumulate(
(
(1 - storage.loss_rate[t])
** tsa_period["segments"][(k, t - t0)]
if "segments" in tsa_period
else 1 - storage.loss_rate[t]
for t in range(
intra_series = soc["intra"][(p, k)].iloc[0:timesteps]
if storage.multiple_tsam_timegrid:
inter_value = soc["inter"].iloc[i_offset + i]["value"]
inter_series = (
pd.Series(
itertools.accumulate(
(
(1 - storage.loss_rate[t])
** tsa_period["segments"][(k, t - t0)]
if "segments" in tsa_period
else 1 - storage.loss_rate[t]
for t in range(
t0,
t0 + timesteps - 1,
)
),
operator.mul,
initial=1,
),
operator.mul,
initial=1,
)
)
* inter_value
)
soc_frame = pd.DataFrame(
intra_series["value"].values
+ inter_series.values, # Neglect indexes, otherwise none
columns=["value"],
)
else:
soc_frame = pd.DataFrame(
intra_series["value"].values,
columns=["value"],
)
* inter_value
)
intra_series = soc["intra"][(p, k)].iloc[0:timesteps]
soc_frame = pd.DataFrame(
intra_series["value"].values
+ inter_series.values, # Neglect indexes, otherwise none
columns=["value"],
)

# Disaggregate segmentation
if "segments" in tsa_period:
soc_disaggregated = _disaggregate_segmentation(
Expand Down
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