Merge remote-tracking branch 'upstream/greensteel-eco-sync' into gree…

…nheart-layout

greenheart/simulation/technologies/hydrogen/h2_storage/storage_sizing.py

@@ -0,0 +1,84 @@
+import math
+import numpy as np
+
+
+def hydrogen_storage_capacity(H2_Results, electrolyzer_size_mw, hydrogen_demand_kgphr):
+    """Calculate storage capacity based on hydrogen demand and production.
+
+    Args:
+        H2_Results (dict): Dictionary including electrolyzer physics results.
+        electrolyzer_size_mw (float): Electrolyzer size in MW.
+        hydrogen_demand_kgphr (float): Hydrogen demand in kg/hr.
+
+    Returns:
+        hydrogen_storage_capacity_kg (float): Hydrogen storage capacity in kilograms.
+        hydrogen_storage_duration_hr (float): Hydrogen storage duration in hours using HHV/LHV.
+        hydrogen_storage_soc (list): Timeseries of the hydrogen storage state of charge.
+    """
+
+    hydrogen_production_kgphr = H2_Results["Hydrogen Hourly Production [kg/hr]"]
+
+    hydrogen_demand_kgphr = max(
+        hydrogen_demand_kgphr, np.mean(hydrogen_production_kgphr)
+    )  # TODO: potentially add buffer No buffer needed since we are already oversizing
+
+    # TODO: SOC is just an absolute value and is not a percentage. Ideally would calculate as shortfall in future.
+    hydrogen_storage_soc = []
+    for j in range(len(hydrogen_production_kgphr)):
+        if j == 0:
+            hydrogen_storage_soc.append(
+                hydrogen_production_kgphr[j] - hydrogen_demand_kgphr
+            )
+        else:
+            hydrogen_storage_soc.append(
+                hydrogen_storage_soc[j - 1]
+                + hydrogen_production_kgphr[j]
+                - hydrogen_demand_kgphr
+            )
+
+    minimum_soc = np.min(hydrogen_storage_soc)
+
+    #adjust soc so it's not negative.
+    if minimum_soc < 0:
+        hydrogen_storage_soc = [x + np.abs(minimum_soc) for x in hydrogen_storage_soc]
+
+    hydrogen_storage_capacity_kg = np.max(hydrogen_storage_soc) - np.min(
+        hydrogen_storage_soc
+    )
+    h2_LHV = 119.96  # MJ/kg
+    h2_HHV = 141.88  # MJ/kg
+    hydrogen_storage_capacity_MWh_LHV = hydrogen_storage_capacity_kg * h2_LHV / 3600
+    hydrogen_storage_capacity_MWh_HHV = hydrogen_storage_capacity_kg * h2_HHV / 3600
+
+    # # Get max injection/withdrawal rate
+    # hydrogen_injection_withdrawal_rate = []
+    # for j in range(len(hydrogen_production_kgphr)):
+    #     hydrogen_injection_withdrawal_rate.append(
+    #         hydrogen_production_kgphr[j] - hydrogen_demand_kgphr
+    #     )
+    # max_h2_injection_rate_kgphr = max(hydrogen_injection_withdrawal_rate)
+
+    # # Get storage compressor capacity. TODO: sync compressor calculation here with GreenHEART compressor model
+    # compressor_total_capacity_kW = (
+    #     max_h2_injection_rate_kgphr / 3600 / 2.0158 * 8641.678424
+    # )
+
+    # compressor_max_capacity_kw = 16000
+    # n_comps = math.ceil(compressor_total_capacity_kW / compressor_max_capacity_kw)
+
+    # small_positive = 1e-6
+    # compressor_avg_capacity_kw = compressor_total_capacity_kW / (
+    #     n_comps + small_positive
+    # )
+
+    # Get average electrolyzer efficiency
+    electrolyzer_average_efficiency_HHV = H2_Results['Sim: Average Efficiency [%-HHV]']
+
+    # Calculate storage durationhyd
+    hydrogen_storage_duration_hr = (
+        hydrogen_storage_capacity_MWh_LHV
+        / electrolyzer_size_mw
+        / electrolyzer_average_efficiency_HHV
+    )
+
+    return hydrogen_storage_capacity_kg, hydrogen_storage_duration_hr, hydrogen_storage_soc

greenheart/tools/eco/hydrogen_mgmt.py

@@ -44,6 +44,8 @@
 )
 from greenheart.simulation.technologies.offshore.all_platforms import calc_platform_opex
 
+from greenheart.simulation.technologies.hydrogen.h2_storage.storage_sizing import hydrogen_storage_capacity
+
 
 def run_h2_pipe_array(
     greenheart_config,
@@ -289,8 +291,16 @@ def run_h2_storage(
         greenheart_config["h2_capacity"] = 0.0
         h2_storage_results["h2_storage_kg"] = 0.0
     else:
-        greenheart_config["h2_capacity"] = h2_capacity
-        h2_storage_results["h2_storage_kg"] = h2_capacity
+        if greenheart_config['h2_storage']['size_capacity_from_demand']['flag']:
+            hydrogen_storage_demand = np.mean(electrolyzer_physics_results["H2_Results"][
+            "Hydrogen Hourly Production [kg/hr]"
+        ])   # TODO: update demand based on end-use needs
+            hydrogen_storage_capacity_kg, hydrogen_storage_duration_hr, hydrogen_storage_soc = hydrogen_storage_capacity(electrolyzer_physics_results['H2_Results'], greenheart_config['electrolyzer']['rating'], hydrogen_storage_demand)
+            greenheart_config["h2_capacity"] = hydrogen_storage_capacity_kg
+            h2_storage_results["h2_storage_kg"] = hydrogen_storage_capacity_kg
+        else:
+            greenheart_config["h2_capacity"] = h2_capacity
+            h2_storage_results["h2_storage_kg"] = h2_capacity
 
     # if storage_hours == 0:
     if (

greenheart/tools/optimization/gc_PoseOptimization.py

@@ -160,11 +160,23 @@ def set_driver(self, opt_prob):
             opt_options = self.config.greenheart_config["opt_options"]["driver"]["optimization"]
             step_size = self._get_step_size()
 
-            if opt_options["step_calc"] == "None":
+            if "step_calc" in opt_options.keys():
+                if opt_options["step_calc"] == "None":
+                    step_calc = None
+                else:
+                    step_calc = opt_options["step_calc"]
+            else:
                 step_calc = None
+
+            if "form" in opt_options.keys():
+                if opt_options["form"] == "None":
+                    form = None
+                else:
+                    form = opt_options["form"]
             else:
-                step_calc = opt_options["step_calc"]
-            opt_prob.model.approx_totals(method="fd", step=step_size, form=opt_options["form"], step_calc=step_calc)
+                form = None
+
+            opt_prob.model.approx_totals(method="fd", step=step_size, form=form, step_calc=step_calc)
 
             # Set optimization solver and options. First, Scipy's SLSQP and COBYLA
             if opt_options["solver"] in self.scipy_methods:

requirements.txt

@@ -43,7 +43,7 @@ openpyxl
 CoolProp
 attrs
 utm
-orbit-nrel @ git+https://github.com/WISDEM/ORBIT.git@SemiTaut_Mooring_Update
+orbit-nrel @ git+https://github.com/WISDEM/ORBIT.git@3baed36052d7503de6ea6f2db0b40945d637ea35
 pyyaml-include <= 1.4.1
 electrolyzer @ git+https://github.com/jaredthomas68/electrolyzer.git@smoothing
 ProFAST @ git+https://github.com/NREL/ProFAST.git

tests/greenheart/input_files/plant/greenheart_config.yaml

@@ -80,10 +80,11 @@ h2_storage_compressor:
 h2_transport_pipe:
   outlet_pressure: 10 # bar - from example in code from Jamie #TODO check this value
 h2_storage:
-  # capacity_kg: 18750 # kg
+  size_capacity_from_demand:
+    flag: False # If True, then storage is sized to provide steady-state storage    
   capacity_from_max_on_turbine_storage: False # if True, then days of storage is ignored and storage capacity is based on how much h2 storage fits on the turbines in the plant using Kottenstete 2003.
   type: "none" # can be one of ["none", "pipe", "turbine", "pressure_vessel", "salt_cavern", "lined_rock_cavern"]  
-  days: 3 # [days] how many days worth of production we should be able to store (this is ignored if `capacity_from_max_on_turbine_storage` is set to True)
+  days: 3 # [days] how many days worth of production we should be able to store (this is ignored if `capacity_from_max_on_turbine_storage` or `size_capacity_from_demand` is set to True)
 
 platform:
   opex_rate: 0.0111 # % of capex to determine opex (see table 5 in https://www.acm.nl/sites/default/files/documents/study-on-estimation-method-for-additional-efficient-offshore-grid-opex.pdf)

tests/greenheart/input_files/plant/greenheart_config_onshore.yaml

@@ -81,7 +81,8 @@ h2_storage_compressor:
 h2_transport_pipe:
   outlet_pressure: 10 # bar - from example in code from Jamie #TODO check this value
 h2_storage:
-  # capacity_kg: 18750 # kg
+  size_capacity_from_demand:
+    flag: False # If True, then storage is sized to provide steady-state storage    
   capacity_from_max_on_turbine_storage: False # if True, then days of storage is ignored and storage capacity is based on how much h2 storage fits on the turbines in the plant using Kottenstete 2003.
   type: "none" # can be one of ["none", "pipe", "turbine", "pressure_vessel", "salt_cavern", "lined_rock_cavern"]  
   days: 3 # [days] how many days worth of production we should be able to store (this is ignored if `capacity_from_max_on_turbine_storage` is set to True)

tests/greenheart/test_greenheart_system.py

@@ -363,4 +363,54 @@ def test_simulation_wind_battery_pv_onshore_steel_ammonia(subtests):
         expected_length = 8760
 
         for key in greenheart_output.hourly_energy_breakdown.keys():
-            assert len(greenheart_output.hourly_energy_breakdown[key]) == expected_length
+            assert len(greenheart_output.hourly_energy_breakdown[key]) == expected_length
+
+def test_simulation_wind_onshore_steel_ammonia_ss_h2storage(subtests):
+
+    config = GreenHeartSimulationConfig(
+        filename_hopp_config=filename_hopp_config,
+        filename_greenheart_config=filename_greenheart_config_onshore,
+        filename_turbine_config=filename_turbine_config,
+        filename_floris_config=filename_floris_config,
+        verbose=False,
+        show_plots=False,
+        save_plots=True,
+        output_dir=os.path.abspath(pathlib.Path(__file__).parent.resolve()) + "/output/",
+        use_profast=True,
+        post_processing=True,
+        incentive_option=1,
+        plant_design_scenario=9,
+        output_level=7,
+    )
+
+    config.greenheart_config['h2_storage']['size_capacity_from_demand']['flag'] = True
+    config.greenheart_config['h2_storage']['type'] = 'pipe'
+
+    # based on 2023 ATB moderate case for onshore wind
+    config.hopp_config["config"]["cost_info"]["wind_installed_cost_mw"] = 1434000.0 
+    # based on 2023 ATB moderate case for onshore wind
+    config.hopp_config["config"]["cost_info"]["wind_om_per_kw"] = 29.567
+    config.hopp_config["technologies"]["wind"]["fin_model"]["system_costs"]["om_fixed"][0] = config.hopp_config["config"]["cost_info"]["wind_om_per_kw"]
+    # set skip_financial to false for onshore wind
+    config.hopp_config["config"]["simulation_options"]["wind"]["skip_financial"] = False
+    lcoe, lcoh, steel_finance, ammonia_finance = run_simulation(config)
+
+    # TODO base this test value on something
+    with subtests.test("lcoh"):
+        assert lcoh == approx(4.023687007795485, rel=rtol)
+
+    # TODO base this test value on something
+    with subtests.test("lcoe"):
+        assert lcoe == approx(0.03486192934806013, rel=rtol)
+
+    # TODO base this test value on something
+    with subtests.test("steel_finance"):
+        lcos_expected = 1414.0330270955506 
+
+        assert steel_finance.sol.get("price") == approx(lcos_expected, rel=rtol)
+
+    # TODO base this test value on something
+    with subtests.test("ammonia_finance"):
+        lcoa_expected = 1.0419096226034346
+
+        assert ammonia_finance.sol.get("price") == approx(lcoa_expected, rel=rtol)