Accommodate FunctionData move to InfrastructureSystems

NREL-Sienna · Feb 22, 2024 · 09447d5 · 09447d5
1 parent cac43e0
commit 09447d5
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Showing 2 changed files with 57 additions and 18 deletions.
diff --git a/src/library/psitest_library.jl b/src/library/psitest_library.jl
@@ -211,7 +211,7 @@ function build_c_sys5_re(; kwargs...)
             )
         end
         for (ix, serv) in enumerate(PSY.get_components(PSY.ReserveDemandCurve, c_sys5_re))
-            forecast_data = SortedDict{Dates.DateTime, Vector{IS.PWL}}()
+            forecast_data = SortedDict{Dates.DateTime, Vector{PiecewiseLinearPointData}}()
             for t in 1:2
                 ini_time = TimeSeries.timestamp(ORDC_cost_ts[t])[1]
                 forecast_data[ini_time] = TimeSeries.values(ORDC_cost_ts[t])
@@ -467,7 +467,7 @@ function build_c_sys5_hyd(; kwargs...)
             )
         end
         for (ix, serv) in enumerate(PSY.get_components(PSY.ReserveDemandCurve, c_sys5_hyd))
-            forecast_data = SortedDict{Dates.DateTime, Vector{IS.PWL}}()
+            forecast_data = SortedDict{Dates.DateTime, Vector{PiecewiseLinearPointData}}()
             for t in 1:2
                 ini_time = TimeSeries.timestamp(ORDC_cost_ts[t])[1]
                 forecast_data[ini_time] = TimeSeries.values(ORDC_cost_ts[t])
@@ -636,7 +636,7 @@ function build_c_sys5_hyd_ems(; kwargs...)
             )
         end
         for (ix, serv) in enumerate(PSY.get_components(PSY.ReserveDemandCurve, c_sys5_hyd))
-            forecast_data = SortedDict{Dates.DateTime, Vector{IS.PWL}}()
+            forecast_data = SortedDict{Dates.DateTime, Vector{PiecewiseLinearPointData}}()
             for t in 1:2
                 ini_time = TimeSeries.timestamp(ORDC_cost_ts[t])[1]
                 forecast_data[ini_time] = TimeSeries.values(ORDC_cost_ts[t])
@@ -750,7 +750,7 @@ function build_c_sys5_bat(; kwargs...)
             )
         end
         for (ix, serv) in enumerate(PSY.get_components(PSY.ReserveDemandCurve, c_sys5_bat))
-            forecast_data = SortedDict{Dates.DateTime, Vector{IS.PWL}}()
+            forecast_data = SortedDict{Dates.DateTime, Vector{PiecewiseLinearPointData}}()
             for t in 1:2
                 ini_time = TimeSeries.timestamp(ORDC_cost_ts[t])[1]
                 forecast_data[ini_time] = TimeSeries.values(ORDC_cost_ts[t])
@@ -841,7 +841,7 @@ function build_c_sys5_il(; kwargs...)
             )
         end
         for (ix, serv) in enumerate(PSY.get_components(PSY.ReserveDemandCurve, c_sys5_il))
-            forecast_data = SortedDict{Dates.DateTime, Vector{IS.PWL}}()
+            forecast_data = SortedDict{Dates.DateTime, Vector{PiecewiseLinearPointData}}()
             for t in 1:2
                 ini_time = TimeSeries.timestamp(ORDC_cost_ts[t])[1]
                 forecast_data[ini_time] = TimeSeries.values(ORDC_cost_ts[t])
@@ -1179,7 +1179,7 @@ function build_c_sys5_uc(; kwargs...)
         end
 
         for (ix, serv) in enumerate(PSY.get_components(PSY.ReserveDemandCurve, c_sys5_uc))
-            forecast_data = SortedDict{Dates.DateTime, Vector{IS.PWL}}()
+            forecast_data = SortedDict{Dates.DateTime, Vector{PiecewiseLinearPointData}}()
             for t in 1:2
                 ini_time = timestamp(ORDC_cost_ts[t])[1]
                 forecast_data[ini_time] = TimeSeries.values(ORDC_cost_ts[t])
@@ -1291,7 +1291,7 @@ function build_c_sys5_uc_non_spin(; kwargs...)
         end
 
         for (ix, serv) in enumerate(PSY.get_components(PSY.ReserveDemandCurve, c_sys5_uc))
-            forecast_data = SortedDict{Dates.DateTime, Vector{IS.PWL}}()
+            forecast_data = SortedDict{Dates.DateTime, Vector{PiecewiseLinearPointData}}()
             for t in 1:2
                 ini_time = timestamp(ORDC_cost_ts[t])[1]
                 forecast_data[ini_time] = TimeSeries.values(ORDC_cost_ts[t])
@@ -1431,7 +1431,7 @@ function build_c_sys5_uc_re(; kwargs...)
         end
 
         for (ix, serv) in enumerate(PSY.get_components(PSY.ReserveDemandCurve, c_sys5_uc))
-            forecast_data = SortedDict{Dates.DateTime, Vector{IS.PWL}}()
+            forecast_data = SortedDict{Dates.DateTime, Vector{PiecewiseLinearPointData}}()
             for t in 1:2
                 ini_time = timestamp(ORDC_cost_ts[t])[1]
                 forecast_data[ini_time] = TimeSeries.values(ORDC_cost_ts[t])
@@ -2586,12 +2586,32 @@ function build_pwl_marketbid_sys(; kwargs...)
     DA_load_forecast = Dict{Dates.DateTime, TimeSeries.TimeArray}()
     market_bid_gen1_data = Dict(
         ini_time => [
-            [(589.99, 22.0), (884.99, 33.0), (1210.04, 44.0), (1543.44, 55.0)],
-            [(589.99, 22.0), (884.99, 33.0), (1210.04, 44.0), (1543.44, 55.0)],
+            PiecewiseLinearPointData([
+                (22.0, 589.99),
+                (33.0, 884.99),
+                (44.0, 1210.04),
+                (55.0, 1543.44),
+            ]),
+            PiecewiseLinearPointData([
+                (22.0, 589.99),
+                (33.0, 884.99),
+                (44.0, 1210.04),
+                (55.0, 1543.44),
+            ]),
         ],
         ini_time + Hour(1) => [
-            [(589.99, 22.0), (884.99, 33.0), (1210.04, 44.0), (1543.44, 55.0)],
-            [(589.99, 22.0), (884.99, 33.0), (1210.04, 44.0), (1543.44, 55.0)],
+            PiecewiseLinearPointData([
+                (22.0, 589.99),
+                (33.0, 884.99),
+                (44.0, 1210.04),
+                (55.0, 1543.44),
+            ]),
+            PiecewiseLinearPointData([
+                (22.0, 589.99),
+                (33.0, 884.99),
+                (44.0, 1210.04),
+                (55.0, 1543.44),
+            ]),
         ],
     )
     market_bid_gen1 = PSY.Deterministic(;
@@ -2601,12 +2621,32 @@ function build_pwl_marketbid_sys(; kwargs...)
     )
     market_bid_gen2_data = Dict(
         ini_time => [
-            [(0.0, 5.0), (290.1, 7.33), (582.72, 9.67), (894.1, 12.0)],
-            [(0.0, 5.0), (300.1, 7.33), (600.72, 9.67), (900.1, 12.0)],
+            PiecewiseLinearPointData([
+                (5.0, 0.0),
+                (7.33, 290.1),
+                (9.67, 582.72),
+                (12.0, 894.1),
+            ]),
+            PiecewiseLinearPointData([
+                (5.0, 0.0),
+                (7.33, 300.1),
+                (9.67, 600.72),
+                (12.0, 900.1),
+            ]),
         ],
         ini_time + Hour(1) => [
-            [(0.0, 5.0), (290.1, 7.33), (582.72, 9.67), (894.1, 12.0)],
-            [(0.0, 5.0), (300.1, 7.33), (600.72, 9.67), (900.1, 12.0)],
+            PiecewiseLinearPointData([
+                (5.0, 0.0),
+                (7.33, 290.1),
+                (9.67, 582.72),
+                (12.0, 894.1),
+            ]),
+            PiecewiseLinearPointData([
+                (5.0, 0.0),
+                (7.33, 300.1),
+                (9.67, 600.72),
+                (12.0, 900.1),
+            ]),
         ],
     )
     market_bid_gen2 = PSY.Deterministic(;
@@ -2845,7 +2885,7 @@ function build_c_sys5_bat_ems(; kwargs...)
             add_time_series!(c_sys5_bat, serv, Deterministic("requirement", forecast_data))
         end
         for (ix, serv) in enumerate(get_components(ReserveDemandCurve, c_sys5_bat))
-            forecast_data = SortedDict{Dates.DateTime, Vector{IS.PWL}}()
+            forecast_data = SortedDict{Dates.DateTime, Vector{PiecewiseLinearPointData}}()
             for t in 1:2
                 ini_time = timestamp(ORDC_cost_ts[t])[1]
                 forecast_data[ini_time] = TimeSeries.values(ORDC_cost_ts[t])

diff --git a/test/test_psitestsystems.jl b/test/test_psitestsystems.jl
@@ -38,7 +38,6 @@ end
         @test length(PSY.get_components(PSY.StaticLoad, sys)) >= 2
         @test length(PSY.get_components(PSY.PowerLoad, sys)) >= 1
         @test length(PSY.get_components(PSY.StandardLoad, sys)) >= 1
-        println((PSY.get_components(PSY.StaticLoad, sys)))
     end
     test_c_sys5_all_components()
 end