Sienna-Platform · daniel-thom · Jul 29, 2026 · Jul 30, 2026
diff --git a/Project.toml b/Project.toml
@@ -6,6 +6,7 @@ authors = ["Sienna-Platform"]
 [deps]
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
+InfraStore = "6aee0376-896a-4a59-96ff-12f221c99746"
 InfrastructureOptimizationModels = "bed98974-b02a-5e2f-9ee0-a103f5c45069"
 InfrastructureSystems = "2cd47ed4-ca9b-11e9-27f2-ab636a7671f1"
 InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
@@ -25,10 +26,11 @@ TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
 PowerFlows = "94fada2c-fd9a-4e89-8d82-81405f5cb4f6"
 
 [sources]
-InfrastructureSystems = {rev = "IS4", url = "https://github.com/Sienna-Platform/InfrastructureSystems.jl"}
-PowerSystems = {rev = "psy6", url = "https://github.com/Sienna-Platform/PowerSystems.jl"}
-InfrastructureOptimizationModels = {rev = "main", url = "https://github.com/Sienna-Platform/InfrastructureOptimizationModels.jl"}
+InfraStore = {path = "../../infrastore/julia/InfraStore.jl"}
+InfrastructureOptimizationModels = {path = "../InfrastructureOptimizationModels.jl"}
+InfrastructureSystems = {path = "../IS3.jl"}
 PowerNetworkMatrices = {rev = "psy6", url = "https://github.com/Sienna-Platform/PowerNetworkMatrices.jl"}
+PowerSystems = {rev = "feat/rust-time-series-store", url = "https://github.com/Sienna-Platform/PowerSystems.jl"}
 
 [extensions]
 PowerFlowsExt = "PowerFlows"
@@ -39,9 +41,9 @@ DocStringExtensions = "~0.8, ~0.9"
 InfrastructureSystems = "3"
 InteractiveUtils = "1.11.0"
 JuMP = "^1.28"
-PowerSystems = "^5.10"
 PowerFlows = "0.21, 0.22"
 PowerNetworkMatrices = "^0.24"
+PowerSystems = "^5.10"
 PrettyTables = "3"
 ProgressMeter = "1.11.0"
 TimerOutputs = "~0.5"

diff --git a/src/common_models/add_parameters.jl b/src/common_models/add_parameters.jl
@@ -162,35 +162,43 @@ function _add_time_series_parameters!(
     device_names = String[]
     devices_with_time_series = D[]
     initial_values = Dict{String, AbstractArray}()
-    # device name -> ts_uuid cache so the second loop below doesn't re-query IS.
-    device_ts_uuids = Dict{String, String}()
+    # device name -> data hash cache so the second loop below doesn't re-query IS.
+    device_ts_hashes = Dict{String, String}()
     model_interval = get_interval(get_settings(container))
     is_ts_interval = _to_is_interval(model_interval)
     model_resolution = get_resolution(get_settings(container))
     is_ts_resolution = _to_is_resolution(model_resolution)
 
     @debug "adding" T D ts_name ts_type _group = IOM.LOG_GROUP_OPTIMIZATION_CONTAINER
 
+    # One catalog query resolves the content hash of every device's stored array.
+    # Devices whose time series share an array share a hash, so the parameter rows
+    # dedupe on it (the role the per-array time series UUID used to play).
+    ts_hashes_by_id = IS.get_time_series_hashes(
+        devices,
+        ts_type,
+        ts_name;
+        resolution = is_ts_resolution,
+        interval = is_ts_interval,
+    )
     for device::D in devices
         if !PSY.has_time_series(device, ts_type, ts_name)
             @debug "Time series $(ts_type):$(ts_name) for $D, $(PSY.get_name(device)) not found. Skipping parameter addition for this device."
             continue
         end
         device_name = PSY.get_name(device)
+        ts_hash = get(ts_hashes_by_id, IS.get_id(device), nothing)
+        if ts_hash === nothing
+            error(
+                "Time series $(ts_type):$(ts_name) for $D, $device_name does not " *
+                "match resolution=$model_resolution interval=$model_interval.",
+            )
+        end
         push!(device_names, device_name)
         push!(devices_with_time_series, device)
-        ts_uuid = string(
-            IS.get_time_series_uuid(
-                ts_type,
-                device,
-                ts_name;
-                resolution = is_ts_resolution,
-                interval = is_ts_interval,
-            ),
-        )
-        device_ts_uuids[device_name] = ts_uuid
-        if !(ts_uuid in keys(initial_values))
-            initial_values[ts_uuid] =
+        device_ts_hashes[device_name] = ts_hash
+        if !(ts_hash in keys(initial_values))
+            initial_values[ts_hash] =
                 IOM.get_time_series_initial_values!(
                     container,
                     ts_type,
@@ -199,7 +207,7 @@ function _add_time_series_parameters!(
                     interval = model_interval,
                     resolution = model_resolution,
                 )
-            _check_branch_rating_ts(initial_values[ts_uuid], param, device, model)
+            _check_branch_rating_ts(initial_values[ts_hash], param, device, model)
         end
     end
 
@@ -227,7 +235,7 @@ function _add_time_series_parameters!(
     jump_model = get_jump_model(container)
     param_instance = T()
     parent_param = IOM.get_parameter_array_data(param_container)
-    for (i, (ts_uuid, raw_ts_vals)) in enumerate(initial_values)
+    for (i, (ts_hash, raw_ts_vals)) in enumerate(initial_values)
         ts_vals = IOM.unwrap_for_param.((param_instance,), raw_ts_vals, (additional_axes,))
         @assert all(_size_wrapper.(ts_vals) .== (length.(additional_axes),))
 
@@ -244,7 +252,7 @@ function _add_time_series_parameters!(
         IOM.add_component_name!(
             IOM.get_attributes(param_container),
             device_name,
-            device_ts_uuids[device_name],
+            device_ts_hashes[device_name],
         )
     end
     return
@@ -280,7 +288,7 @@ function _add_time_series_parameters!(
     ts_name = _get_time_series_name(T, first(devices), model)
     model_interval = get_interval(get_settings(container))
     ts_interval = model_interval
-    device_name_axis, ts_uuid_axis =
+    device_name_axis, ts_hash_axis =
         get_branch_argument_parameter_axes(
             net_reduction_data,
             devices,
@@ -292,17 +300,17 @@ function _add_time_series_parameters!(
         @info "No devices with time series $ts_name found for $D devices. Skipping parameter addition."
         return
     end
-    # name -> ts_uuid cache built from the axis pair so the per-branch loop below
-    # doesn't re-query IS.get_time_series_uuid for each branch.
-    branch_ts_uuids = Dict{String, String}(zip(device_name_axis, ts_uuid_axis))
+    # name -> data hash cache built from the axis pair so the per-branch loop below
+    # doesn't re-query the store catalog for each branch.
+    branch_ts_hashes = Dict{String, String}(zip(device_name_axis, ts_hash_axis))
     additional_axes = ()
     param_container = add_param_container!(
         container,
         T,
         D,
         ts_type,
         ts_name,
-        ts_uuid_axis,
+        ts_hash_axis,
         device_name_axis,
         additional_axes,
         time_steps,
@@ -312,10 +320,10 @@ function _add_time_series_parameters!(
     jump_model = get_jump_model(container)
     parent_param = IOM.get_parameter_array_data(param_container)
     parent_mult = IOM.get_multiplier_array_data(param_container)
-    # The param array's first axis is `ts_uuid_axis` (UUID-keyed) while the multiplier
-    # array's first axis is `device_name_axis` (name-keyed); we need two separate row
-    # lookups so parallel branches sharing a UUID still write their multiplier to the
-    # correct (per-branch-name) row.
+    # The param array's first axis is `ts_hash_axis` (content-hash-keyed) while the
+    # multiplier array's first axis is `device_name_axis` (name-keyed); we need two
+    # separate row lookups so parallel branches sharing an array still write their
+    # multiplier to the correct (per-branch-name) row.
     param_lookup = get_parameter_array(param_container).lookup[1]
     mult_lookup = get_multiplier_array(param_container).lookup[1]
     for (name, (arc, reduction)) in PNM.get_name_to_arc_map(net_reduction_data, D)
@@ -325,8 +333,8 @@ function _add_time_series_parameters!(
         if device_with_time_series === nothing
             continue
         end
-        ts_uuid = branch_ts_uuids[name]
-        i_param = param_lookup[ts_uuid]
+        ts_hash = branch_ts_hashes[name]
+        i_param = param_lookup[ts_hash]
         i_mult = mult_lookup[name]
 
         has_entry, tracker_container = search_for_reduced_branch_parameter!(
@@ -382,7 +390,7 @@ function _add_time_series_parameters!(
         IOM.add_component_name!(
             IOM.get_attributes(param_container),
             name,
-            ts_uuid,
+            ts_hash,
         )
     end
     return
@@ -418,7 +426,8 @@ function _get_time_series_name(
 )
     op_cost = PSY.get_operation_cost(device)
     IS.@assert_op op_cost isa TS_OFFER_CURVE_COST_TYPES
-    return IS.get_name(IS.get_time_series_key(PSY.get_start_up(op_cost)))
+    # The TS-backed startup field is the time-series key itself.
+    return IS.get_name(PSY.get_start_up(op_cost))
 end
 
 function _get_time_series_name(
@@ -816,21 +825,26 @@ function _add_parameters!(
     name = PSY.get_name(service)
     model_interval = get_interval(get_settings(container))
     ts_interval = model_interval
-    ts_uuid = string(
-        IS.get_time_series_uuid(
-            ts_type,
-            service,
-            ts_name;
-            interval = _to_is_interval(ts_interval),
-        ),
+    ts_hashes = IS.get_time_series_hashes(
+        (service,),
+        ts_type,
+        ts_name;
+        interval = _to_is_interval(ts_interval),
     )
+    ts_hash = get(ts_hashes, IS.get_id(service), nothing)
+    if ts_hash === nothing
+        error(
+            "Time series $(ts_type):$(ts_name) for $U, $name does not match " *
+            "interval=$ts_interval.",
+        )
+    end
     @debug "adding" T U _group = IOM.LOG_GROUP_OPTIMIZATION_CONTAINER
     additional_axes = calc_additional_axes(container, T, [service], model)
     parameter_container = add_param_container!(container, T,
         U,
         ts_type,
         ts_name,
-        [ts_uuid],
+        [ts_hash],
         [name],
         additional_axes,
         time_steps;
@@ -847,7 +861,7 @@ function _add_parameters!(
     for t in time_steps
         IOM._set_parameter_at!(parent_param, jump_model, ts_vector[t], 1, t)
     end
-    IOM.add_component_name!(IOM.get_attributes(parameter_container), name, ts_uuid)
+    IOM.add_component_name!(IOM.get_attributes(parameter_container), name, ts_hash)
     return
 end
 

diff --git a/src/common_models/market_bid_overrides.jl b/src/common_models/market_bid_overrides.jl
@@ -80,8 +80,19 @@ function IOM.validate_occ_component(
     device::PSY.ThermalMultiStart,
 )
     startup = PSY.get_start_up(PSY.get_operation_cost(device))
-    # TupleTimeSeries{PSY.StartUpStages} guarantees NTuple{3, Float64} values at construction
-    startup isa IS.TupleTimeSeries && return
+    # A TS-backed startup is a bare time-series key referencing NTuple{3, Float64}
+    # stages; its element type is checked when the parameter is populated.
+    if startup isa IS.TimeSeriesKey
+        if eltype(typeof(startup)) != NTuple{3, Float64}
+            # TODO: should this be a helper in IOM?
+            throw(
+                ArgumentError(
+                    "Expected element type NTuple{3, Float64} but got $(typeof(startup))",
+                ),
+            )
+        end
+        return
+    end
     _validate_eltype(
         Union{Float64, NTuple{3, Float64}, PSY.StartUpStages},
         device,
@@ -99,7 +110,8 @@ function IOM.validate_occ_component(
     startup = PSY.get_start_up(PSY.get_operation_cost(device))
     apply_maybe_across_time_series(device, startup) do x
         # x may be Float64 (TGC), PSY.StartUpStages (static MBC), or NTuple{3, Float64}
-        # (TupleTimeSeries elements). `values` normalizes both NamedTuple and Tuple.
+        # (elements of a TS-backed startup key). `values` normalizes both NamedTuple
+        # and Tuple.
         if any(!iszero, x isa Number ? (x,) : values(x))
             @warn "Nonzero startup cost detected for renewable generation or storage device $(get_name(device))."
         end

diff --git a/src/common_models/market_bid_plumbing.jl b/src/common_models/market_bid_plumbing.jl
@@ -617,8 +617,8 @@ IOM.transform_single_time_series!(
     interval::Dates.Period;
     kwargs...,
 ) = PSY.transform_single_time_series!(sys, horizon, interval; kwargs...)
-# sys.data.internal UUID, not sys's wrapper UUID — IOM uses this as a filename identifier.
-IOM.get_system_uuid(sys::PSY.System) = IS.get_uuid(sys.data.internal)
+# The system's own UUID (`System.metadata.uuid`) — IOM uses this as a filename identifier.
+IOM.get_system_uuid(sys::PSY.System) = PSY.get_uuid(sys)
 # PSY.get_components restricts T <: PSY.Component; IOM passes IS.InfrastructureSystemsComponent.
 # Bridge directly to IS.get_components to preserve the looser typing.
 IOM.get_subsystem_components(

diff --git a/src/network_models/network_reductions.jl b/src/network_models/network_reductions.jl
@@ -219,30 +219,35 @@ function get_branch_argument_parameter_axes(
 ) where {T <: IS.InfrastructureSystemsComponent, V <: IS.TimeSeriesData}
     is_interval = IOM._to_is_interval(interval)
     name_axis = Vector{String}()
-    ts_uuid_axis = Vector{String}()
+    ts_hash_axis = Vector{String}()
     arc_map = get(PNM.get_name_to_arc_maps(net_reduction_data), T, nothing)
-    isnothing(arc_map) && return name_axis, ts_uuid_axis
+    isnothing(arc_map) && return name_axis, ts_hash_axis
+    devices_with_time_series = IS.InfrastructureSystemsComponent[]
     for (name, (arc, reduction)) in arc_map
         reduction_entry =
             PNM.get_all_branch_maps_by_type(net_reduction_data)[reduction][T][arc]
         device_with_time_series =
             get_branch_with_time_series(reduction_entry, V, ts_name)
         if !isnothing(device_with_time_series)
             push!(name_axis, name)
-            push!(
-                ts_uuid_axis,
-                string(
-                    IS.get_time_series_uuid(
-                        V,
-                        device_with_time_series,
-                        ts_name;
-                        interval = is_interval,
-                    ),
-                ),
+            push!(devices_with_time_series, device_with_time_series)
+        end
+    end
+    # One catalog query resolves the content hash of every branch's stored array;
+    # branches sharing an array share a hash, which is what keys the parameter rows.
+    hashes = IS.get_time_series_hashes(devices_with_time_series, V, ts_name;
+        interval = is_interval)
+    for (name, device) in zip(name_axis, devices_with_time_series)
+        ts_hash = get(hashes, IS.get_id(device), nothing)
+        if ts_hash === nothing
+            error(
+                "Time series $V:$ts_name for branch $name does not match " *
+                "interval=$interval.",
             )
         end
+        push!(ts_hash_axis, ts_hash)
     end
-    return name_axis, ts_uuid_axis
+    return name_axis, ts_hash_axis
 end
 
 function get_branch_argument_variable_axis(

diff --git a/test/Project.toml b/test/Project.toml
@@ -6,6 +6,7 @@ DataFramesMeta = "1313f7d8-7da2-5740-9ea0-a2ca25f37964"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"
+InfraStore = "6aee0376-896a-4a59-96ff-12f221c99746"
 InfrastructureOptimizationModels = "bed98974-b02a-5e2f-9ee0-a103f5c45069"
 InfrastructureSystems = "2cd47ed4-ca9b-11e9-27f2-ab636a7671f1"
 Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
@@ -37,14 +38,19 @@ TimeSeries = "9e3dc215-6440-5c97-bce1-76c03772f85e"
 TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
 UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 
+# InfraStore is not registered yet, so it cannot resolve from a registry. Pkg
+# only honors the [sources] section of the root project, so this environment
+# needs its own entry (and InfraStore must be a direct dependency for the source
+# to apply). Drop the dep + entry once InfraStore is registered.
 [sources]
-InfrastructureOptimizationModels = {rev = "main", url = "https://github.com/Sienna-Platform/InfrastructureOptimizationModels.jl"}
-InfrastructureSystems = {rev = "IS4", url = "https://github.com/Sienna-Platform/InfrastructureSystems.jl"}
-PowerSystems = {rev = "psy6", url = "https://github.com/Sienna-Platform/PowerSystems.jl"}
 # psy6: disabled pending transformer refactor
 # PowerFlows = {rev = "psy6", url = "https://github.com/Sienna-Platform/PowerFlows.jl"}
+InfraStore = {path = "../../../infrastore/julia/InfraStore.jl"}
+InfrastructureSystems = {path = "../../IS3.jl"}
+PowerSystems = {url = "https://github.com/Sienna-Platform/PowerSystems.jl", rev = "feat/rust-time-series-store"}
+InfrastructureOptimizationModels = {path = "../../InfrastructureOptimizationModels.jl"}
 PowerNetworkMatrices = {rev = "psy6", url = "https://github.com/Sienna-Platform/PowerNetworkMatrices.jl"}
-PowerSystemCaseBuilder = {rev = "psy6", url = "https://github.com/Sienna-Platform/PowerSystemCaseBuilder.jl"}
+PowerSystemCaseBuilder = {rev = "feat/rust-time-series-store", url = "https://github.com/Sienna-Platform/PowerSystemCaseBuilder.jl"}
 
 [compat]
 HiGHS = "1"

diff --git a/test/test_mbc_parameter_population.jl b/test/test_mbc_parameter_population.jl
@@ -75,7 +75,7 @@ function _build_mbtsc_thermal_system(;
 
     new_cost = PSY.MarketBidTimeSeriesCost(;
         no_load_cost = PSY.TimeSeriesLinearCurve(nl_key),
-        start_up = IS.TupleTimeSeries{PSY.StartUpStages}(su_key),
+        start_up = su_key,
         shut_down = PSY.TimeSeriesLinearCurve(sd_key),
         incremental_offer_curves = PSY.make_market_bid_ts_curve(pwl_incr_key, ii_incr_key),
         decremental_offer_curves = PSY.make_market_bid_ts_curve(pwl_decr_key, ii_decr_key),
@@ -97,7 +97,7 @@ function _pp_build_container(sys::PSY.System, time_steps::UnitRange{Int})
     return container
 end
 
-@testset "StartupCostParameter populated from TupleTimeSeries" begin
+@testset "StartupCostParameter populated from tuple-valued time series" begin
     # Drift by 10 per hour so each timestep is distinct: (100,150,200), (110,160,210), ...
     sys, gen = _build_mbtsc_thermal_system(;
         name = _PP_THERMAL_NAME,

diff --git a/test/test_utils/add_market_bid_cost.jl b/test/test_utils/add_market_bid_cost.jl
@@ -189,7 +189,7 @@ function extend_mbc!(
 
         new_cost = MarketBidTimeSeriesCost(;
             no_load_cost = TimeSeriesLinearCurve(nl_key),
-            start_up = IS.TupleTimeSeries{PSY.StartUpStages}(su_key),
+            start_up = su_key,
             shut_down = TimeSeriesLinearCurve(sd_key),
             incremental_offer_curves = ts_curves["incremental"],
             decremental_offer_curves = ts_curves["decremental"],

diff --git a/test/test_utils/mbc_math_helpers.jl b/test/test_utils/mbc_math_helpers.jl
@@ -403,7 +403,7 @@ function stub_ts_market_bid_cost(;
 )
     return PSY.MarketBidTimeSeriesCost(;
         no_load_cost = PSY.TimeSeriesLinearCurve(_stub_forecast_key("no_load")),
-        start_up = IS.TupleTimeSeries{PSY.StartUpStages}(_stub_forecast_key("start_up")),
+        start_up = _stub_forecast_key("start_up"),
         shut_down = PSY.TimeSeriesLinearCurve(_stub_forecast_key("shut_down")),
         incremental_offer_curves = stub_ts_offer_curve(;
             curve_name = "variable_cost incremental",