diff --git a/component/adapter.py b/component/adapter.py
index 50d9ed2ac578d611828f5ace486443ab827cb0b5..11d3127678baa5c18721cbfac73fce354ad009e2 100644
--- a/component/adapter.py
+++ b/component/adapter.py
@@ -60,19 +60,24 @@ class AssetAdapter(AbstractComponent):
)
return match_kind and match_commodity
- def operational_base_variable_names(self):
+ def non_state_base_variable_names(self):
return [
(self.name + ".input_1", VariableKind.INDEXED),
(self.name + ".output_1", VariableKind.INDEXED),
]
- def _build_operational_model(self, d_block, o_block):
+ def add_non_state_variables(self, o_block):
input = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".input_1", input)
output = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".output_1", output)
+ def add_non_state_model(self, d_block, o_block):
+ input = o_block.component_dict[self.name + ".input_1"]
+
+ output = o_block.component_dict[self.name + ".output_1"]
+
asset_block = o_block.blocks[self.asset._name]
into_member = resample_variable(
@@ -124,19 +129,24 @@ class MemberAdapter(AbstractComponent):
)
return match_kind and match_commodity
- def operational_base_variable_names(self):
+ def non_state_base_variable_names(self):
return [
(self.name + ".input_1", VariableKind.INDEXED),
(self.name + ".output_1", VariableKind.INDEXED),
]
- def _build_operational_model(self, d_block, o_block):
+ def add_non_state_variables(self, o_block):
input = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".input_1", input)
output = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".output_1", output)
+ def add_non_state_model(self, d_block, o_block):
+ input = o_block.component_dict[self.name + ".input_1"]
+
+ output = o_block.component_dict[self.name + ".output_1"]
+
member_result = self.member._results[self.member._last_result_key]
into_member = (
diff --git a/component/core.py b/component/core.py
index d16b80209c71ea05661822d7f07f19442b896f70..fc5b366238ed494c2fb483c2ae65639f42a7b270 100644
--- a/component/core.py
+++ b/component/core.py
@@ -237,10 +237,13 @@ class AbstractComponent:
else:
return [(self.name + ".capacity", VariableKind.UNINDEXED)]
- def operational_base_variable_names(self):
- pass
+ def non_state_base_variable_names(self):
+ return []
+
+ def state_base_variable_names(self):
+ return []
- def build_design_model(self, d_block):
+ def add_design_variables(self, d_block):
if self.capacity is not None:
if isinstance(self.capacity, tuple):
d_block.add(self.name + ".capacity", pyo.Var(bounds=self.capacity))
@@ -251,17 +254,19 @@ class AbstractComponent:
else:
raise ValueError(f"Invalid capacity {self.capacity}!")
- # currently no additional model logic that is part of the desing part
+ def add_non_state_variables(self, o_block):
+ pass
- def build_operational_model(self, d_block, o_block):
- self._build_operational_model(d_block, o_block)
+ def add_state_variables(self, s_block):
+ pass
- self._add_additional_model_logic(d_block, o_block)
+ def add_non_state_model(self, d_block, o_block):
+ pass
- def _build_operational_model(self, d_block, o_block):
+ def add_state_model(self, d_block, o_block, s_block):
pass
- def _add_additional_model_logic(self, d_block, o_block):
+ def add_additional_model_logic(self, d_block, o_block):
for logic_name, logic in self.additional_model_logic.items():
if logic["type"] == "RampPenalty":
var_name = logic["variable"]
@@ -426,19 +431,23 @@ class BaseBusBar(AbstractComponent):
pattern_commodity=commodity,
)
- def operational_base_variable_names(self):
+ def non_state_base_variable_names(self):
return [
(self.name + ".input_1", VariableKind.INDEXED),
(self.name + ".output_1", VariableKind.INDEXED),
]
- def _build_operational_model(self, d_block, o_block):
+ def add_non_state_variables(self, o_block):
input = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".input_1", input)
output = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".output_1", output)
+ def add_non_state_model(self, d_block, o_block):
+ input = o_block.component_dict[self.name + ".input_1"]
+ output = o_block.component_dict[self.name + ".output_1"]
+
def rule(m, t):
return output[t] == input[t]
@@ -502,15 +511,22 @@ class BaseComponent(AbstractComponent):
pattern_commodity=commodity,
)
- def operational_base_variable_names(self):
+ def non_state_base_variable_names(self):
return self.operational_variables
- def _build_operational_model(self, d_block, o_block):
- capacity = d_block.component_dict[self.name + ".capacity"]
-
+ def add_non_state_variables(self, o_block):
dep_var_1 = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + "." + self.indep_var_1, dep_var_1)
+ if self.indep_var_2 is not None:
+ dep_var_2 = pyo.Var(o_block.T, bounds=(0, None))
+ o_block.add(self.name + "." + self.indep_var_2, dep_var_2)
+
+ def add_non_state_model(self, d_block, o_block):
+ capacity = d_block.component_dict[self.name + ".capacity"]
+
+ dep_var_1 = o_block.component_dict[self.name + "." + self.indep_var_1]
+
def rule(m, t):
return dep_var_1[t] <= capacity
@@ -520,8 +536,7 @@ class BaseComponent(AbstractComponent):
)
if self.indep_var_2 is not None:
- dep_var_2 = pyo.Var(o_block.T, bounds=(0, None))
- o_block.add(self.name + "." + self.indep_var_2, dep_var_2)
+ dep_var_2 = o_block.component_dict[self.name + "." + self.indep_var_2]
def rule(m, t):
return dep_var_2[t] <= capacity
@@ -631,13 +646,16 @@ class BaseConsumption(AbstractComponent):
pattern_commodity=commodity,
)
- def operational_base_variable_names(self):
+ def non_state_base_variable_names(self):
return [(self.name + ".input_1", VariableKind.INDEXED)]
- def _build_operational_model(self, d_block, o_block):
+ def add_non_state_variables(self, o_block):
input = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".input_1", input)
+ def add_non_state_model(self, d_block, o_block):
+ input = o_block.component_dict[self.name + ".input_1"]
+
consumption = self.consumption.resample(o_block.dynamic).values
def rule(m, t):
@@ -673,13 +691,16 @@ class BaseGeneration(AbstractComponent):
pattern_commodity=commodity,
)
- def operational_base_variable_names(self):
+ def non_state_base_variable_names(self):
return [(self.name + ".output_1", VariableKind.INDEXED)]
- def _build_operational_model(self, d_block, o_block):
+ def add_non_state_variables(self, o_block):
output = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".output_1", output)
+ def add_non_state_model(self, d_block, o_block):
+ output = o_block.component_dict[self.name + ".output_1"]
+
generation = self.generation.resample(o_block.dynamic).values
def rule(m, t):
@@ -718,19 +739,24 @@ class BaseGrid(AbstractComponent):
pattern_commodity=commodity,
)
- def operational_base_variable_names(self):
+ def non_state_base_variable_names(self):
return [
(self.name + ".input_1", VariableKind.INDEXED),
(self.name + ".output_1", VariableKind.INDEXED),
]
- def _build_operational_model(self, d_block, o_block):
+ def add_non_state_variables(self, o_block):
input = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".input_1", input)
output = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".output_1", output)
+ def add_non_state_model(self, d_block, o_block):
+ input = o_block.component_dict[self.name + ".input_1"]
+
+ output = o_block.component_dict[self.name + ".output_1"]
+
if self.capacity is not None:
capacity = d_block.component_dict[self.name + ".capacity"]
@@ -831,25 +857,33 @@ class BaseStorage(AbstractComponent):
pattern_commodity=commodity,
)
- def operational_base_variable_names(self):
+ def state_base_variable_names(self):
return [
(self.name + ".input_1", VariableKind.INDEXED),
(self.name + ".output_1", VariableKind.INDEXED),
- (self.name + ".energy", VariableKind.EXTENDED_INDEXED),
]
- def _build_operational_model(self, d_block, o_block):
- capacity = d_block.component_dict[self.name + ".capacity"]
-
- energy = pyo.Var(o_block.T_prime, bounds=(0, None))
- o_block.add(self.name + ".energy", energy)
+ def state_base_variable_names(self):
+ return [
+ (self.name + ".energy", VariableKind.EXTENDED_INDEXED),
+ ]
+ def add_non_state_variables(self, o_block):
input = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".input_1", input)
output = pyo.Var(o_block.T, bounds=(0, None))
o_block.add(self.name + ".output_1", output)
+ def add_state_variables(self, s_block):
+ energy = pyo.Var(s_block.T_prime, bounds=(0, None))
+ s_block.add(self.name + ".energy", energy)
+
+ def add_non_state_model(self, d_block, o_block):
+ capacity = d_block.component_dict[self.name + ".capacity"]
+ input = o_block.component_dict[self.name + ".input_1"]
+ output = o_block.component_dict[self.name + ".output_1"]
+
def rule(m, t):
return input[t] * self.input_efficiency <= capacity / self.e2p_in
@@ -864,6 +898,54 @@ class BaseStorage(AbstractComponent):
self.name + ".capacity_output_cons", pyo.Constraint(o_block.T, rule=rule)
)
+ z_bi_flow = pyo.Var(o_block.T, domain=pyo.Binary)
+ o_block.add(self.name + ".z_bi_flow", z_bi_flow)
+
+ if isinstance(self.capacity, (int, float)):
+
+ def rule(m, t):
+ return input[t] <= z_bi_flow[t] * (
+ capacity / (self.e2p_in * self.input_efficiency)
+ )
+
+ o_block.add(
+ self.name + ".bi_flow_cons_1", pyo.Constraint(o_block.T, rule=rule)
+ )
+
+ def rule(m, t):
+ return output[t] <= (1.0 - z_bi_flow[t]) * (
+ (capacity * self.output_efficiency) / self.e2p_out
+ )
+
+ o_block.add(
+ self.name + ".bi_flow_cons_2", pyo.Constraint(o_block.T, rule=rule)
+ )
+ else:
+
+ def rule(m, t):
+ return input[t] <= z_bi_flow[t] * (
+ capacity.ub / (self.e2p_in * self.input_efficiency)
+ )
+
+ o_block.add(
+ self.name + ".bi_flow_cons_1", pyo.Constraint(o_block.T, rule=rule)
+ )
+
+ def rule(m, t):
+ return output[t] <= (1.0 - z_bi_flow[t]) * (
+ (capacity.ub * self.output_efficiency) / self.e2p_out
+ )
+
+ o_block.add(
+ self.name + ".bi_flow_cons_2", pyo.Constraint(o_block.T, rule=rule)
+ )
+
+ def add_state_model(self, d_block, o_block, s_block):
+ capacity = d_block.component_dict[self.name + ".capacity"]
+ energy = s_block.component_dict[self.name + ".energy"]
+ input = o_block.component_dict[self.name + ".input_1"]
+ output = o_block.component_dict[self.name + ".output_1"]
+
def rule(m, t):
return energy[t] <= capacity
@@ -918,45 +1000,3 @@ class BaseStorage(AbstractComponent):
sense = self.final_soe["sense"]
raise ValueError(f"Invalid sense {sense}!")
o_block.add(self.name + ".fix_final_energy", pyo.Constraint(expr=expr))
-
- z_bi_flow = pyo.Var(o_block.T, domain=pyo.Binary)
- o_block.add(self.name + ".z_bi_flow", z_bi_flow)
-
- if isinstance(self.capacity, (int, float)):
-
- def rule(m, t):
- return input[t] <= z_bi_flow[t] * (
- capacity / (self.e2p_in * self.input_efficiency)
- )
-
- o_block.add(
- self.name + ".bi_flow_cons_1", pyo.Constraint(o_block.T, rule=rule)
- )
-
- def rule(m, t):
- return output[t] <= (1.0 - z_bi_flow[t]) * (
- (capacity * self.output_efficiency) / self.e2p_out
- )
-
- o_block.add(
- self.name + ".bi_flow_cons_2", pyo.Constraint(o_block.T, rule=rule)
- )
- else:
-
- def rule(m, t):
- return input[t] <= z_bi_flow[t] * (
- capacity.ub / (self.e2p_in * self.input_efficiency)
- )
-
- o_block.add(
- self.name + ".bi_flow_cons_1", pyo.Constraint(o_block.T, rule=rule)
- )
-
- def rule(m, t):
- return output[t] <= (1.0 - z_bi_flow[t]) * (
- (capacity.ub * self.output_efficiency) / self.e2p_out
- )
-
- o_block.add(
- self.name + ".bi_flow_cons_2", pyo.Constraint(o_block.T, rule=rule)
- )
diff --git a/component/electricity.py b/component/electricity.py
index 933486bebb558a53221372c687fcb58be36536dd..aeaa45c266d38d68e32922bd76dd37aca07eae7b 100644
--- a/component/electricity.py
+++ b/component/electricity.py
@@ -132,7 +132,11 @@ class PVGenerator(BaseComponent):
def _setup_conversions(self, configuration):
self.operational_variables = [(self.name + ".output_1", VariableKind.INDEXED)]
- def _build_operational_model(self, d_block, o_block):
+ def add_non_state_variables(self, o_block):
+ output = pyo.Var(o_block.T, bounds=(0, None))
+ o_block.add(self.name + ".output_1", output)
+
+ def add_non_state_model(self, d_block, o_block):
if hasattr(self, "power_factors"):
power_factor = self.power_factors.resample(o_block.dynamic).values
else:
@@ -145,9 +149,7 @@ class PVGenerator(BaseComponent):
power_factor[power_factor > 1.0] = 1.0
power_factor[power_factor < 0.0] = 0.0
- output = pyo.Var(o_block.T, bounds=(0, None))
- o_block.add(self.name + ".output_1", output)
-
+ output = o_block.component_dict[self.name + ".output_1"]
capacity = d_block.component_dict[self.name + ".capacity"]
def rule(m, t):
diff --git a/component/heat.py b/component/heat.py
index 68cec38ce80b1b1470748c84b80dd6c8123af53a..66609a0fa4aace5d20ef9df979d9a11e6b456ef2 100644
--- a/component/heat.py
+++ b/component/heat.py
@@ -122,15 +122,17 @@ class SolarThermalCollector(BaseComponent):
def _setup_conversions(self, configuration):
self.operational_variables = [(self.name + ".output_1", VariableKind.INDEXED)]
- def _build_operational_model_new(self, d_block, o_block):
+ def add_non_state_variables(self, o_block):
+ output = pyo.Var(o_block.T, bounds=(0, None))
+ o_block.add(self.name + ".output_1", output)
+
+ def add_non_state_model(self, d_block, o_block):
irradiance = self.irradiance.resample(o_block.dynamic).values
power_factor = irradiance * 0.001 # <--- Yi: your code here
power_factor[power_factor > 1.0] = 1.0
power_factor[power_factor < 0.0] = 1.0
- output = pyo.Var(o_block.T, bounds=(0, None))
- o_block.add(self.name + ".output_1", output)
-
+ output = o_block.component_dict[self.name + ".output_1"]
capacity = d_block.component_dict[self.name + ".capacity"]
def rule(m, t):
diff --git a/topology.py b/topology.py
index d19298c3e3ba8e606c38a1d3f02186424993cdf4..cfb0478ab89dbdf6961d60ad7d056843a81c5f02 100644
--- a/topology.py
+++ b/topology.py
@@ -294,8 +294,8 @@ class Topology:
if isinstance(architecture, TrivialArchitecture):
design_objectives = self.fill_design_block(block, objectives)
- operational_objectives = self.fill_operational_block(
- block, block, objectives
+ operational_objectives = self.fill_operational_blocks(
+ block, block, block, objectives
)
w = (365.0 * 24.0) / (np.sum(block.dynamic.step_lengths()) / 3600.0)
@@ -324,7 +324,9 @@ class Topology:
period_blocks.append(period_block)
operational_objectives.append(
- self.fill_operational_block(block, period_block, objectives)
+ self.fill_operational_blocks(
+ block, period_block, period_block, objectives
+ )
)
w = (365.0 * 24.0) / (np.sum(block.dynamic.step_lengths()) / 3600.0)
@@ -359,7 +361,7 @@ class Topology:
def fill_design_block(self, d_block, objectives):
for component in self._components:
- self._components[component].build_design_model(d_block)
+ self._components[component].add_design_variables(d_block)
for logic_name, logic in self._additional_model_logic.items():
if logic["type"] == "EqualCapacity":
@@ -393,9 +395,13 @@ class Topology:
return design_objectives
- def fill_operational_block(self, d_block, o_block, objectives):
+ def fill_operational_blocks(self, d_block, o_block, s_block, objectives):
for component in self._components:
- self._components[component].build_operational_model(d_block, o_block)
+ self._components[component].add_non_state_variables(o_block)
+ self._components[component].add_state_variables(s_block)
+ self._components[component].add_non_state_model(d_block, o_block)
+ self._components[component].add_state_model(d_block, o_block, s_block)
+ self._components[component].add_additional_model_logic(d_block, o_block)
for flow in self._flows:
o_block.add(flow, pyo.Var(o_block.T, bounds=(0, None)))
@@ -535,7 +541,10 @@ class Topology:
self._components[component].design_base_variable_names()
)
base_variable_names.extend(
- self._components[component].operational_base_variable_names()
+ self._components[component].non_state_base_variable_names()
+ )
+ base_variable_names.extend(
+ self._components[component].state_base_variable_names()
)
for flow in self._flows:
@@ -559,7 +568,10 @@ class Topology:
operational_base_variable_names = []
for component in self._components:
operational_base_variable_names.extend(
- self._components[component].operational_base_variable_names()
+ self._components[component].non_state_base_variable_names()
+ )
+ operational_base_variable_names.extend(
+ self._components[component].state_base_variable_names()
)
for flow in self._flows: