Add timeseries operating reserve outputs

CHANGELOG.md

@@ -23,6 +23,12 @@ Classify the change according to the following categories:
     ### Deprecated
     ### Removed
 
+## v0.33.1
+### Added
+- Add timeseries operating reserve outputs for each tech for off-grid only
+### Changed
+- Change units for total timeseries operating reserves required and provided to kW (from kWh)
+
 ## v0.33.0
 ### Added
 - Functionality to evaluate scenarios with Wind can in the ERP (`backup_reliability`)

src/core/production_factor.jl

@@ -7,12 +7,12 @@ function get_production_factor(pv::PV, latitude::Real, longitude::Real; timefram
         return pv.production_factor_series
     end
 
-    watts, ambient_temp_celcius = call_pvwatts_api(latitude, longitude; tilt=pv.tilt, azimuth=pv.azimuth, module_type=pv.module_type, 
+    watts, ambient_temp_celcius, pv_station_distance_km = call_pvwatts_api(latitude, longitude; tilt=pv.tilt, azimuth=pv.azimuth, module_type=pv.module_type, 
         array_type=pv.array_type, losses=round(pv.losses*100, digits=3), dc_ac_ratio=pv.dc_ac_ratio,
         gcr=pv.gcr, inv_eff=pv.inv_eff*100, timeframe=timeframe, radius=pv.radius,
         time_steps_per_hour=time_steps_per_hour)
 
-    return watts
+    return watts, pv_station_distance_km
 
 end
 

src/core/reopt_inputs.jl

@@ -151,7 +151,7 @@ function REoptInputs(s::AbstractScenario)
 
     time_steps = 1:length(s.electric_load.loads_kw)
     hours_per_time_step = 1 / s.settings.time_steps_per_hour
-    techs, pv_to_location, maxsize_pv_locations, pvlocations, 
+    techs, pv_to_location, maxsize_pv_locations, pvlocations,
         production_factor, max_sizes, min_sizes, existing_sizes, cap_cost_slope, om_cost_per_kw, n_segs_by_tech, 
         seg_min_size, seg_max_size, seg_yint, techs_by_exportbin, export_bins_by_tech, boiler_efficiency,
         tech_renewable_energy_fraction, tech_emissions_factors_CO2, tech_emissions_factors_NOx, tech_emissions_factors_SO2, 
@@ -349,7 +349,7 @@ function setup_tech_inputs(s::AbstractScenario)
         setup_operating_reserve_fraction(s, techs_operating_reserve_req_fraction)
     end
 
-    return techs, pv_to_location, maxsize_pv_locations, pvlocations, 
+    return techs, pv_to_location, maxsize_pv_locations, pvlocations,
     production_factor, max_sizes, min_sizes, existing_sizes, cap_cost_slope, om_cost_per_kw, n_segs_by_tech, 
     seg_min_size, seg_max_size, seg_yint, techs_by_exportbin, export_bins_by_tech, boiler_efficiency,
     tech_renewable_energy_fraction, tech_emissions_factors_CO2, tech_emissions_factors_NOx, tech_emissions_factors_SO2, 
@@ -435,7 +435,7 @@ end
 
 function setup_pv_inputs(s::AbstractScenario, max_sizes, min_sizes,
     existing_sizes, cap_cost_slope, om_cost_per_kw, production_factor,
-    pvlocations, pv_to_location, maxsize_pv_locations, 
+    pvlocations, pv_to_location, maxsize_pv_locations,
     segmented_techs, n_segs_by_tech, seg_min_size, seg_max_size, seg_yint, 
     techs_by_exportbin, techs)
 
@@ -444,7 +444,7 @@ function setup_pv_inputs(s::AbstractScenario, max_sizes, min_sizes,
     roof_max_kw, land_max_kw = 1.0e5, 1.0e5
 
     for pv in s.pvs        
-        production_factor[pv.name, :] = get_production_factor(pv, s.site.latitude, s.site.longitude; 
+        production_factor[pv.name, :], pv_station_distance_km = get_production_factor(pv, s.site.latitude, s.site.longitude; 
             time_steps_per_hour=s.settings.time_steps_per_hour)
         for location in pvlocations
             if pv.location == String(location) # Must convert symbol to string

src/core/scenario.jl

@@ -432,12 +432,12 @@ function Scenario(d::Dict; flex_hvac_from_json=false)
             # By assigning pv.production_factor_series here, it will skip the PVWatts call in get_production_factor(PV) call from reopt_input.jl
             if !isempty(pvs)
                 for pv in pvs
-                    pv.production_factor_series, ambient_temp_celcius = call_pvwatts_api(site.latitude, site.longitude; tilt=pv.tilt, azimuth=pv.azimuth, module_type=pv.module_type, 
+                    pv.production_factor_series, ambient_temp_celcius, pv_station_distance_km = call_pvwatts_api(site.latitude, site.longitude; tilt=pv.tilt, azimuth=pv.azimuth, module_type=pv.module_type, 
                         array_type=pv.array_type, losses=round(pv.losses*100, digits=3), dc_ac_ratio=pv.dc_ac_ratio,
                         gcr=pv.gcr, inv_eff=pv.inv_eff*100, timeframe="hourly", radius=pv.radius, time_steps_per_hour=settings.time_steps_per_hour)
                 end
             else
-                pv_prodfactor, ambient_temp_celcius = call_pvwatts_api(site.latitude, site.longitude; time_steps_per_hour=settings.time_steps_per_hour)    
+                pv_prodfactor, ambient_temp_celcius, pv_station_distance_km = call_pvwatts_api(site.latitude, site.longitude; time_steps_per_hour=settings.time_steps_per_hour)    
             end
             ambient_temp_degF = ambient_temp_celcius * 1.8 .+ 32.0
         else

src/core/utils.jl

@@ -363,6 +363,7 @@ end
 This calls the PVWatts API and returns both:
  - PV production factor
  - Ambient outdoor air dry bulb temperature profile [Celcius] 
+ - pv_station_distance_km
 """
 function call_pvwatts_api(latitude::Real, longitude::Real; tilt=latitude, azimuth=180, module_type=0, array_type=1, 
     losses=14, dc_ac_ratio=1.2, gcr=0.4, inv_eff=96, timeframe="hourly", radius=0, time_steps_per_hour=1)
@@ -394,6 +395,7 @@ function call_pvwatts_api(latitude::Real, longitude::Real; tilt=latitude, azimut
         # Get both possible data of interest
         watts = collect(get(response["outputs"], "ac", []) / 1000)  # scale to 1 kW system (* 1 kW / 1000 W)
         tamb_celcius = collect(get(response["outputs"], "tamb", []))  # Celcius
+        pv_station_distance_km = response["station_info"]["distance"] / 1000 # Distance between the input location and the climate station. (meters)
         # Validate outputs
         if length(watts) != 8760
             throw(@error("PVWatts did not return a valid prodfactor. Got $watts"))
@@ -407,7 +409,7 @@ function call_pvwatts_api(latitude::Real, longitude::Real; tilt=latitude, azimut
             watts = repeat(watts, inner=time_steps_per_hour)
             tamb_celcius = repeat(tamb_celcius, inner=time_steps_per_hour)
         end
-        return watts, tamb_celcius
+        return watts, tamb_celcius, pv_station_distance_km
     catch e
         throw(@error("Error occurred when calling PVWatts: $e"))
     end

src/results/electric_load.jl

@@ -6,8 +6,8 @@
 - `annual_calculated_kwh` sum of the `load_series_kw`
 - `offgrid_load_met_series_kw` vector of electric load met by generation techs, for off-grid scenarios only
 - `offgrid_load_met_fraction` percentage of total electric load met on an annual basis, for off-grid scenarios only
-- `offgrid_annual_oper_res_required_series_kwh` , total operating reserves required (for load and techs) on an annual basis, for off-grid scenarios only
-- `offgrid_annual_oper_res_provided_series_kwh` , total operating reserves provided on an annual basis, for off-grid scenarios only
+- `offgrid_annual_oper_res_required_series_kw` , total operating reserves required (for load and techs) on an annual basis, for off-grid scenarios only
+- `offgrid_annual_oper_res_provided_series_kw` , total operating reserves provided on an annual basis, for off-grid scenarios only
 
 !!! note "'Series' and 'Annual' energy outputs are average annual"
 	REopt performs load balances using average annual production values for technologies that include degradation. 
@@ -33,8 +33,8 @@ function add_electric_load_results(m::JuMP.AbstractModel, p::REoptInputs, d::Dic
                 sum(p.s.electric_load.critical_loads_kw))
         r["offgrid_load_met_fraction"] = round(value(LoadMetPct), digits=6)
 
-        r["offgrid_annual_oper_res_required_series_kwh"] = round.(value.(m[:OpResRequired][ts] for ts in p.time_steps_without_grid), digits=3)
-        r["offgrid_annual_oper_res_provided_series_kwh"] = round.(value.(m[:OpResProvided][ts] for ts in p.time_steps_without_grid), digits=3)
+        r["offgrid_annual_oper_res_required_series_kw"] = round.(value.(m[:OpResRequired][ts] for ts in p.time_steps_without_grid), digits=3)
+        r["offgrid_annual_oper_res_provided_series_kw"] = round.(value.(m[:OpResProvided][ts] for ts in p.time_steps_without_grid), digits=3)
     end
 
     d["ElectricLoad"] = r

src/results/electric_storage.jl

@@ -43,6 +43,9 @@ function add_electric_storage_results(m::JuMP.AbstractModel, p::REoptInputs, d::
                 ))
             end
          end
+        if p.s.settings.off_grid_flag
+            r["operating_reserve_provided_series_kw"] = value.(m[Symbol("dvOpResFromBatt"*_n)][b,ts] for ts in p.time_steps)
+        end
     else
         r["soc_series_fraction"] = []
         r["storage_to_load_series_kw"] = []

src/results/generator.jl

@@ -13,6 +13,7 @@
 - `electric_to_grid_series_kw` Vector of power sent to grid in an average year
 - `electric_to_load_series_kw` Vector of power sent to load in an average year
 - `annual_energy_produced_kwh` Average annual energy produced over analysis period
+- `operating_reserve_provided_series_kw` For offgrid analyses: operating reserve provided by generator in each time step
 
 !!! note "'Series' and 'Annual' energy outputs are average annual"
 	REopt performs load balances using average annual production values for technologies that include degradation. 
@@ -68,6 +69,12 @@ function add_generator_results(m::JuMP.AbstractModel, p::REoptInputs, d::Dict; _
 			for t in p.techs.gen, ts in p.time_steps)
 	)
 	r["annual_energy_produced_kwh"] = round(value(AverageGenProd), digits=0)
+
+	if p.s.settings.off_grid_flag
+		GeneratorOR = @expression(m, [ts in p.time_steps],
+			sum(m[:dvOpResFromTechs][t,ts] for t in p.techs.gen))
+		r["operating_reserve_provided_series_kw"] = round.(value.(GeneratorOR), digits=3)
+    end
 
 	d["Generator"] = r
     nothing
@@ -117,7 +124,7 @@ function add_generator_results(m::JuMP.AbstractModel, p::MPCInputs, d::Dict; _n=
 			for t in p.techs.gen, ts in p.time_steps)
 	)
 	r["energy_produced_kwh"] = round(value(Year1GenProd), digits=0)
-    
+
 	d["Generator"] = r
     nothing
 end

src/results/pv.jl

@@ -12,6 +12,7 @@
 - `electric_curtailed_series_kw` Vector of power curtailed over the first year
 - `annual_energy_exported_kwh` Average annual energy exported to the grid
 - `production_factor_series` PV production factor in each time step, either provided by user or obtained from PVWatts
+- `operating_reserve_provided_series_kw` For offgrid analyses: operating reserve provided by PV in each time step
 
 !!! warn
     The key(s) used to access PV outputs in the results dictionary is determined by the `PV.name` value to allow for modeling multiple PV options. (The default `PV.name` is "PV".)
@@ -66,6 +67,9 @@ function add_pv_results(m::JuMP.AbstractModel, p::REoptInputs, d::Dict; _n="")
 		PVPerUnitSizeOMCosts = p.om_cost_per_kw[t] * p.pwf_om * m[Symbol("dvSize"*_n)][t]
 		r["lifecycle_om_cost_after_tax"] = round(value(PVPerUnitSizeOMCosts) * (1 - p.s.financial.owner_tax_rate_fraction), digits=0)
         r["lcoe_per_kwh"] = calculate_lcoe(p, r, get_pv_by_name(t, p.s.pvs))
+        if p.s.settings.off_grid_flag
+            r["operating_reserve_provided_series_kw"] = value.(m[Symbol("dvOpResFromTechs"*_n)][t,ts] for ts in p.time_steps)
+        end
         d[t] = r
 	end
     nothing

src/results/wind.jl

@@ -12,6 +12,7 @@
 - `lcoe_per_kwh` Levelized Cost of Energy produced by the PV system
 - `electric_curtailed_series_kw` Vector of power curtailed over an average year
 - `production_factor_series` Wind production factor in each time step, either provided by user or obtained from SAM
+- `operating_reserve_provided_series_kw` For offgrid analyses: operating reserve provided by wind in each time step
 
 !!! note "'Series' and 'Annual' energy outputs are average annual"
 	REopt performs load balances using average annual production values for technologies that include degradation. 
@@ -66,6 +67,11 @@ function add_wind_results(m::JuMP.AbstractModel, p::REoptInputs, d::Dict; _n="")
 	r["annual_energy_produced_kwh"] = round(value(AvgWindProd), digits=0)
 
     r["lcoe_per_kwh"] = calculate_lcoe(p, r, p.s.wind)
+
+	if p.s.settings.off_grid_flag
+		r["operating_reserve_provided_series_kw"] = value.(m[Symbol("dvOpResFromTechs"*_n)][t,ts] for ts in p.time_steps)
+	end
+
 	d[t] = r
     nothing
 end

test/test_with_xpress.jl

@@ -228,7 +228,7 @@ end
         =#
 
         # Austin, TX -> existing_chiller and existing_boiler added with FlexibleHVAC
-        pf, tamb = REopt.call_pvwatts_api(30.2672, -97.7431);
+        pf, tamb, dist = REopt.call_pvwatts_api(30.2672, -97.7431);
         R = 0.00025  # K/kW
         C = 1e5   # kJ/K
         # the starting scenario has flat fuel and electricty costs
@@ -1075,7 +1075,7 @@ end
     # Test outputs
     @test r["ElectricUtility"]["annual_energy_supplied_kwh"] ≈ 0 # no interaction with grid
     @test r["Financial"]["lifecycle_offgrid_other_capital_costs"] ≈ 2617.092 atol=0.01 # Check straight line depreciation calc
-    @test sum(r["ElectricLoad"]["offgrid_annual_oper_res_provided_series_kwh"]) >= sum(r["ElectricLoad"]["offgrid_annual_oper_res_required_series_kwh"]) # OR provided >= required
+    @test sum(r["ElectricLoad"]["offgrid_annual_oper_res_provided_series_kw"]) >= sum(r["ElectricLoad"]["offgrid_annual_oper_res_required_series_kw"]) # OR provided >= required
     @test r["ElectricLoad"]["offgrid_load_met_fraction"] >= scen.electric_load.min_load_met_annual_fraction
     @test r["PV"]["size_kw"] ≈ 5050.0
     f = r["Financial"]
@@ -1140,7 +1140,7 @@ end
 
     windOR = sum(results["Wind"]["electric_to_load_series_kw"]  * post["Wind"]["operating_reserve_required_fraction"])
     loadOR = sum(post["ElectricLoad"]["loads_kw"] * scen.electric_load.operating_reserve_required_fraction)
-    @test sum(results["ElectricLoad"]["offgrid_annual_oper_res_required_series_kwh"]) ≈ loadOR  + windOR atol=1.0
+    @test sum(results["ElectricLoad"]["offgrid_annual_oper_res_required_series_kw"]) ≈ loadOR  + windOR atol=1.0
 
 end