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Add allocation training model #1958

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Dec 3, 2024
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Add allocation training model #1958

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24 changes: 20 additions & 4 deletions core/src/allocation_optim.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -717,11 +717,9 @@ function save_allocation_flows!(
priority::Int32,
optimization_type::OptimizationType.T,
)::Nothing
(; flow, problem, subnetwork_id) = allocation_model
(; flow, subnetwork_id, sources) = allocation_model
(; allocation, graph) = p
(; record_flow) = allocation
F_basin_in = problem[:F_basin_in]
F_basin_out = problem[:F_basin_out]

edges_allocation = keys(flow.data)

Expand Down Expand Up @@ -776,7 +774,7 @@ function save_allocation_flows!(
for node_id in graph[].node_ids[subnetwork_id]
if node_id.type == NodeType.Basin &&
has_external_demand(graph, node_id, :level_demand)[1]
flow_rate = JuMP.value(F_basin_out[node_id]) - JuMP.value(F_basin_in[node_id])
flow_rate = sources[(node_id, node_id)].basin_flow_rate
push!(record_flow.time, t)
push!(record_flow.edge_id, 0)
push!(record_flow.from_node_type, string(NodeType.Basin))
Expand Down Expand Up @@ -894,6 +892,15 @@ function optimize_per_source!(
)::Nothing
(; problem, sources, subnetwork_id, flow) = allocation_model
(; priorities) = allocation
F_basin_in = problem[:F_basin_in]
F_basin_out = problem[:F_basin_out]

# Start the cumulative basin flow rates at 0
for source in values(sources)
if source.type == AllocationSourceType.basin
source.basin_flow_rate = 0.0
end
end

priority = priorities[priority_idx]

Expand Down Expand Up @@ -940,6 +947,15 @@ function optimize_per_source!(
end
end

# Add to the basin cumulative flow rate
for (edge, source) in sources
if source.type == AllocationSourceType.basin
node_id = edge[1]
source.basin_flow_rate +=
JuMP.value(F_basin_out[node_id]) - JuMP.value(F_basin_in[node_id])
end
end

# Adjust allocated flow to basins
increase_allocateds!(p.basin, problem)
end
Expand Down
3 changes: 3 additions & 0 deletions core/src/parameter.jl
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Expand Up @@ -136,12 +136,15 @@ edge: The outflow edge of the source
type: The type of source (edge, basin, main_to_sub, user_return, buffer)
capacity: The initial capacity of the source as determined by the physical layer
capacity_reduced: The capacity adjusted by passed optimizations
basin_flow_rate: The total outflow rate of a basin when optimized over all sources for one priority.
Ignored when the source is not a basin.
"""
@kwdef mutable struct AllocationSource
const edge::Tuple{NodeID, NodeID}
const type::AllocationSourceType.T
capacity::Float64 = 0.0
capacity_reduced::Float64 = 0.0
basin_flow_rate::Float64 = 0.0
end

function Base.show(io::IO, source::AllocationSource)
Expand Down
2 changes: 2 additions & 0 deletions python/ribasim_testmodels/ribasim_testmodels/__init__.py
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Expand Up @@ -7,6 +7,7 @@
import ribasim_testmodels
from ribasim_testmodels.allocation import (
allocation_example_model,
allocation_training_model,
fair_distribution_model,
flow_demand_model,
level_demand_model,
Expand Down Expand Up @@ -63,6 +64,7 @@
from ribasim_testmodels.two_basin import two_basin_model

__all__ = [
"allocation_training_model",
"allocation_example_model",
"backwater_model",
"basic_arrow_model",
Expand Down
178 changes: 178 additions & 0 deletions python/ribasim_testmodels/ribasim_testmodels/allocation.py
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Expand Up @@ -980,3 +980,181 @@ def fair_distribution_model():
model.edge.add(model.user_demand[9], model.basin[5])

return model


def allocation_training_model():
model = Model(
starttime="2022-01-01",
endtime="2023-01-01",
crs="EPSG:4326",
allocation=Allocation(use_allocation=True),
)

flow_boundary_times = pd.date_range(start="2022-01-01", end="2023-01-01", freq="MS")

# Flow boundaries
main = model.flow_boundary.add(
Node(1, Point(0.0, 0.0), subnetwork_id=1, name="Main"),
[
flow_boundary.Time(
time=flow_boundary_times,
flow_rate=[
47.3,
156.7,
77.6,
47.8,
26.6,
23.1,
18.6,
15.6,
23.1,
35.6,
24.4,
20.0,
29.4,
],
)
],
)

minor = model.flow_boundary.add(
Node(2, Point(-3.0, 0.0), subnetwork_id=1, name="Minor"),
[
flow_boundary.Time(
time=flow_boundary_times,
flow_rate=[
0.2,
28.3,
16.0,
11.2,
8.5,
9.6,
9.2,
7.9,
7.5,
7.2,
7.4,
10.0,
8.3,
],
)
],
)

level = model.level_demand.add(
Node(11, Point(1, 1), subnetwork_id=1, name="test"),
[
level_demand.Static(
min_level=[2],
max_level=5,
priority=1,
)
],
)

# Confluence
conf = model.basin.add(
Node(3, Point(-1.5, -1), subnetwork_id=1, name="confluence"),
[
basin.Profile(area=[672000, 5600000], level=[0, 6]),
basin.State(level=[4]),
],
)

tbr_conf = model.tabulated_rating_curve.add(
Node(4, Point(-1.5, -1.5), subnetwork_id=1, name="tbr_conf"),
[
tabulated_rating_curve.Static(
level=[0.0, 2, 5],
flow_rate=[0.0, 50, 200],
)
],
)

# Irrigation
irr = model.user_demand.add(
Node(6, Point(-1.5, 0.5), subnetwork_id=1, name="irrigation"),
[
user_demand.Time(
demand=[0.0, 0.0, 10, 12, 12, 0.0],
return_factor=0,
min_level=0,
priority=3,
time=[
"2022-01-01",
"2022-03-31",
"2022-04-01",
"2022-07-01",
"2022-09-30",
"2022-10-01",
],
)
],
)

# Reservoir
reservoir = model.basin.add(
Node(7, Point(-0.75, -0.5), subnetwork_id=1, name="reservoir"),
[
basin.Profile(area=[20000000, 32300000], level=[0, 7]),
basin.State(level=[3.5]),
],
)

rsv_weir = model.tabulated_rating_curve.add(
Node(8, Point(-1.125, -0.75), subnetwork_id=1, name="rsv_weir"),
[
tabulated_rating_curve.Static(
level=[0.0, 1.5, 5],
flow_rate=[0.0, 45, 200],
)
],
)

# Public water use
city = model.user_demand.add(
Node(9, Point(-0.75, -1), subnetwork_id=1, name="city"),
[
user_demand.Time(
# Total demand in m³/s
demand=[2.0, 2.3, 2.3, 2.4, 3, 3, 4, 3, 2.5, 2.2, 2.0, 2.0],
return_factor=0.4,
min_level=0,
priority=2,
time=pd.date_range(start="2022-01-01", periods=12, freq="MS"),
)
],
)

# Industry
industry = model.user_demand.add(
Node(10, Point(0, -1.5), subnetwork_id=1, name="industry"),
[
user_demand.Time(
# Total demand in m³/s
demand=[4, 4, 4.5, 5, 5, 6, 7.5, 8, 5, 4, 3, 2.0],
return_factor=0.5,
min_level=0,
priority=1,
time=pd.date_range(start="2022-01-01", periods=12, freq="MS"),
)
],
)

sea = model.terminal.add(Node(5, Point(-1.5, -3.0), subnetwork_id=1, name="sea"))

model.edge.add(main, reservoir, name="main")
model.edge.add(minor, conf, name="minor")
model.edge.add(reservoir, irr, name="irr supplied")
model.edge.add(irr, conf, name="irr drain")
model.edge.add(reservoir, city, name="city supplied")
model.edge.add(city, conf, name="city returnflow")
model.edge.add(reservoir, rsv_weir, name="rsv2weir")
model.edge.add(rsv_weir, conf, name="weir2conf")
model.edge.add(conf, tbr_conf, name="conf2tbr")
model.edge.add(level, reservoir)
model.edge.add(reservoir, industry, name="industry supplied")
model.edge.add(industry, conf, name="ind2conf")
model.edge.add(tbr_conf, sea, name="sea")

return model
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