Adding a copy of the hea pump test from the java code (4bb9e4a6) · Commits · AGS_public / pythermogis

tests/test_pyThermoGIS_Doublet_Benchmark.py→tests/test_pythermogis_Doublet_Benchmark.py

+101 −22

Changes for tests/test_pythermogis_Doublet_Benchmark.py: 101 added lines, 22 removed lines.
Original line number	Diff line number	Diff line
		@@ -2,6 +2,7 @@ from unittest import TestCase

		from pythermogis import *


		class ThermoGISDoubletBenchmark(TestCase):
		"""
		This is a series of tests which produce the same results found in the Java code and in test_ThermoGISDoublet_Benchmark, but using the ntended pythermogis implementation
		@@ -9,12 +10,15 @@ class ThermoGISDoubletBenchmark(TestCase):

		def test_calculateDoubletPerformanceTest(self):
		viscosity_mode = get_viscosity_mode("kestin")
		utc_properties = (instantiate_utc_properties_builder()
		utc_properties = (
		instantiate_utc_properties_builder()
		.setDhReturnTemp(40)
		.setViscosityMode(viscosity_mode)
		.build())
		.build()
		)

		input_data = xr.Dataset({
		input_data = xr.Dataset(
		{
		"thickness_mean": ((), 100),
		"thickness_sd": ((), 0.0),
		"ntg": ((), 1.0),
		@@ -23,9 +27,12 @@ class ThermoGISDoubletBenchmark(TestCase):
		"temperature": ((), 76),
		"ln_permeability_mean": ((), np.log(175)),
		"ln_permeability_sd": ((), 0.0),
		})
		}
		)

		results = calculate_doublet_performance_stochastic(input_data, utc_properties=utc_properties, rng_seed=0)
		results = calculate_doublet_performance_stochastic(
		input_data, utc_properties=utc_properties, rng_seed=0
		)

		# Assert
		self.assertTrue(np.isclose(17500, results.transmissivity.data[0], 0.001))
		@@ -43,9 +50,12 @@ class ThermoGISDoubletBenchmark(TestCase):
		"""
		# Arrange
		# Instantiate the UTC properties class
		utc_properties = self.setup_template_utc_properties_builder().setOpexBase(0).build()
		utc_properties = (
		self.setup_template_utc_properties_builder().setOpexBase(0).build()
		)

		input_data = xr.Dataset({
		input_data = xr.Dataset(
		{
		"thickness_mean": ((), 100),
		"thickness_sd": ((), 0.0),
		"ntg": ((), 1.0),
		@@ -54,11 +64,13 @@ class ThermoGISDoubletBenchmark(TestCase):
		"temperature": ((), 76),
		"ln_permeability_mean": ((), np.log(175)),
		"ln_permeability_sd": ((), 0.0),
		})
		}
		)

		# Act
		results = calculate_doublet_performance_stochastic(input_data, utc_properties=utc_properties, rng_seed=0)

		results = calculate_doublet_performance_stochastic(
		input_data, utc_properties=utc_properties, rng_seed=0
		)

		# Assert
		self.assertTrue(np.isclose(17500, results.transmissivity.data[0], 0.001))
		@@ -76,13 +88,18 @@ class ThermoGISDoubletBenchmark(TestCase):
		"""
		# Arrange
		# Instantiate the UTC properties class
		utc_properties = (self.setup_template_utc_properties_builder().setCapexConst(0.5)
		utc_properties = (
		self.setup_template_utc_properties_builder()
		.setCapexConst(0.5)
		.setCapexVariable(1100)
		.setHeatExchangerEfficiency(0.4)
		.setDhReturnTemp(60)
		.setHeatExchangerParasitic(0.1).build())
		.setHeatExchangerParasitic(0.1)
		.build()
		)

		input_data = xr.Dataset({
		input_data = xr.Dataset(
		{
		"thickness_mean": ((), 100),
		"thickness_sd": ((), 0.0),
		"ntg": ((), 1.0),
		@@ -91,10 +108,13 @@ class ThermoGISDoubletBenchmark(TestCase):
		"temperature": ((), 76),
		"ln_permeability_mean": ((), np.log(175)),
		"ln_permeability_sd": ((), 0.0),
		})
		}
		)

		# Act
		results = calculate_doublet_performance_stochastic(input_data, utc_properties=utc_properties, rng_seed=0)
		results = calculate_doublet_performance_stochastic(
		input_data, utc_properties=utc_properties, rng_seed=0
		)

		# Assert
		self.assertTrue(np.isclose(17500, results.transmissivity.data[0], 0.001))
		@@ -113,16 +133,19 @@ class ThermoGISDoubletBenchmark(TestCase):
		"""
		# Arrange
		# Instantiate the UTC properties class
		utc_properties = (self.setup_template_utc_properties_builder()
		utc_properties = (
		self.setup_template_utc_properties_builder()
		.setCapexConst(0)
		.setCapexVariable(2300)
		.setHeatExchangerEfficiency(0.6)
		.setUseORC(True)
		.setHeatExchangerBasetemp(20)
		.setDhReturnTemp(60)
		.build())
		.build()
		)

		input_data = xr.Dataset({
		input_data = xr.Dataset(
		{
		"thickness_mean": ((), 100),
		"thickness_sd": ((), 0.0),
		"ntg": ((), 1.0),
		@@ -131,10 +154,13 @@ class ThermoGISDoubletBenchmark(TestCase):
		"temperature": ((), 100),
		"ln_permeability_mean": ((), np.log(175)),
		"ln_permeability_sd": ((), 0.0),
		})
		}
		)

		# Act
		results = calculate_doublet_performance_stochastic(input_data, utc_properties=utc_properties, rng_seed=0)
		results = calculate_doublet_performance_stochastic(
		input_data, utc_properties=utc_properties, rng_seed=0
		)

		# Assert
		self.assertTrue(np.isclose(17500, results.transmissivity.data[0], 0.001))
		@@ -146,10 +172,62 @@ class ThermoGISDoubletBenchmark(TestCase):
		self.assertTrue(np.isclose(0.06459403120103477, results.cop.data[0], 0.001))
		self.assertTrue(np.isclose(12.44409167482118, results.capex.data[0], 0.001))

		def test_calculateDoubletPerformance_directHeat_and_heatpump(self):
		"""
		This is a copy of a test from the Java ThermoGisDoubletTest.java script; to validate that this python implementation of the ThermoGIS Doublet
		returns the same values.
		"""
		# Arrange
		# Instantiate the UTC properties class
		utc_properties = (
		self.setup_template_utc_properties_builder()
		.setOpexPerPower(100)
		.setOpexBase(0)
		.setHpDirectHeatInputTemp(70)
		.setUseHeatPump(True)
		.setDhReturnTemp(35)
		.build()
		)

		input_data = xr.Dataset(
		{
		"thickness_mean": ((), 100),
		"thickness_sd": ((), 0.0),
		"ntg": ((), 1.0),
		"porosity": ((), 0.0),
		"depth": ((), 2000),
		"temperature": ((), 50),
		"ln_permeability_mean": ((), np.log(175)),
		"ln_permeability_sd": ((), 0.0),
		}
		)

		# Act
		results = calculate_doublet_performance_stochastic(
		input_data, utc_properties=utc_properties, rng_seed=0
		)
		power_hpelec = results.heat_pump_power / (results.cophp - 1)
		power_ratio = results.power / (results.power + power_hpelec)


		# Assert
		self.assertTrue(np.isclose(5.856159806251526, results.power + power_hpelec, 0.1))
		self.assertTrue(np.isclose(8.83718197747828, results.utc * power_ratio, 0.1))
		self.assertTrue(np.isclose(17499.99940, 17500, 0.001))
		self.assertTrue(np.isclose(163.99771118164062, results.flow_rate, 0.001))
		self.assertTrue(np.isclose(60, results.pres, 0.001))
		self.assertTrue(np.isclose(4.97566556930542, results.power, 0.001))
		self.assertTrue(np.isclose(989.2578125, results.welld, 0.001))
		self.assertTrue(np.isclose(4.383212200392486, results.cop, 0.001))
		self.assertTrue(np.isclose(3.798196792602539, results.cophp, 0.001))
		self.assertTrue(np.isclose(10.401010755009017, results.utc, 0.001))
		self.assertTrue(np.isclose(16.50359210062243, results.capex, 0.001))

		def setup_template_utc_properties_builder(self):
		viscosity_mode = get_viscosity_mode("kestin")

		return (instantiate_utc_properties_builder()
		return (
		instantiate_utc_properties_builder()
		.setSalinityGradient(47.0)
		.setDrillingTime(1)
		.setTaxRate(20)
		@@ -162,4 +240,5 @@ class ThermoGISDoubletBenchmark(TestCase):
		.setWellCostZ(1050)
		.setWellCostZ2(0.3)
		.setDhReturnTemp(40)
		.setViscosityMode(viscosity_mode))
		No newline at end of file
		.setViscosityMode(viscosity_mode)
		)
		No newline at end of file