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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,264 @@ | ||
| import numpy as np | ||
| import pandas as pd | ||
| import pygfunction as gt | ||
| import matplotlib.pyplot as plt | ||
|
|
||
| from GHEtool import * | ||
|
|
||
| # design parameters | ||
| ground_data = GroundConstantTemperature(2.29, 12.3, 2.41 * 10 ** 6) | ||
| pipe_data = DoubleUTube(2, 0.013, 0.016, 0.42, 0.065 / 2) | ||
| fluid_data = FluidData(vfr=0.8) | ||
| fluid_data.import_fluid_from_pygfunction(gt.media.Fluid('MPG', 25, 2)) | ||
| r_b = 0.13 / 2 # 130 mm diameter | ||
| H = 120 # depth m | ||
|
|
||
| # TCO parameters | ||
| SEER_LW = 5 | ||
| SEER_AC = 7 # EER(np.array([15.943, 6.153]), np.array([5, 30])) | ||
| SEER_PC = 20 | ||
| # SCOP = COP(np.array( | ||
| # [4.42, 5.21, 6.04, 7.52, 9.5, 3.99, 4.58, 5.21, 6.02, 6.83, 3.86, 4.39, 4.97, | ||
| # 5.62, 6.19, 3.8, 4.3, 4.86, 5.44, 5.9, 3.76, 4.25, 4.79, 5.34, 5.74]), | ||
| # np.array([[-5, 1.06], [0, 1.25], [5, 1.45], [10, 1.66], [15, 1.9], [-5, 2.05], [0, 2.42], [5, 2.81], [10, 3.2], | ||
| # [15, 3.54], [-5, 3.05], [0, 3.6], [5, 4.17], [10, 4.73], [15, 5.18], [-5, 4.04], [0, 4.77], [5, 5.54], | ||
| # [10, 6.27], [15, 6.82], [-5, 5.03], [0, 5.95], [5, 6.9], [10, 7.81], [15, 8.46]]), | ||
| # part_load=True, reference_nominal_power=1, nominal_power=1500) | ||
| SCOP = 5 | ||
| SCOP_DHW = 3 | ||
| SIMULATION_PERIOD = 25 | ||
| E_PRICE = 0.10 # €/kWh | ||
| COST_BOREFIELD = 35 # €/lm | ||
| RDR = -0.0011 # % | ||
| COST_GSHP = 550 # €/kW | ||
| COST_ASHP = 650 # €/kW | ||
| COST_HEX = 46 # €/kW | ||
|
|
||
| # load data | ||
| eer_active_passive = EERCombined(SEER_PC, SEER_AC, 17) | ||
|
|
||
| kantoor = HourlyBuildingLoad(simulation_period=25, efficiency_heating=5, efficiency_cooling=20, efficiency_dhw=2.5) | ||
| terminal = HourlyBuildingLoad(simulation_period=25, efficiency_heating=5, efficiency_cooling=20, efficiency_dhw=2.5) | ||
| hotel = HourlyBuildingLoad(simulation_period=25, efficiency_heating=5, efficiency_cooling=20, efficiency_dhw=2.5) | ||
|
|
||
| kantoor.load_hourly_profile('kantoor.csv', decimal_seperator=',', col_cooling=0, col_heating=1) | ||
| terminal.load_hourly_profile('terminal.csv', decimal_seperator=',', col_cooling=0, col_heating=1) | ||
| hotel.load_hourly_profile('hotel.csv', decimal_seperator=',', col_cooling=0, col_heating=1) | ||
|
|
||
| sww = pd.read_csv('hotel.csv', header=0, sep=";", decimal=",") | ||
| hotel.add_dhw(np.array(sww['Totale warmtelevering [kW] SWW'])) | ||
|
|
||
| combined = HourlyBuildingLoad( | ||
| heating_load=kantoor.hourly_heating_load + terminal.hourly_heating_load + hotel.hourly_heating_load, | ||
| cooling_load=kantoor.hourly_cooling_load + terminal.hourly_cooling_load + hotel.hourly_cooling_load, | ||
| simulation_period=SIMULATION_PERIOD, efficiency_heating=SCOP, efficiency_cooling=eer_active_passive, | ||
| efficiency_dhw=SCOP_DHW) | ||
| combined.add_dhw(np.array(sww['Totale warmtelevering [kW] SWW'])) | ||
|
|
||
| # load borefield coordinates | ||
| coordinates = pd.read_csv('coordinatenlijst optie 1.csv', header=0, sep=";", decimal=",") | ||
| borefield1 = [] | ||
| for idx, row in coordinates.iterrows(): | ||
| borefield1.append(gt.boreholes.Borehole(H=H + row['Z'], D=-row['Z'], r_b=r_b, x=row['X'], y=row['Y'])) | ||
|
|
||
| # coordinates = pd.read_csv('coordinatenlijst optie 2.csv', header=0, sep=";", decimal=",") | ||
| # borefield2 = [] | ||
| # for idx, row in coordinates.iterrows(): | ||
| # borefield2.append(gt.boreholes.Borehole(H=H + row['Z'], D=-row['Z'], r_b=r_b, x=row['X'], y=row['Y'])) | ||
|
|
||
| # initiate borefield | ||
| borefield = Borefield(borefield=borefield1, load=combined) | ||
|
|
||
| borefield.ground_data = ground_data | ||
| borefield.set_pipe_parameters(pipe_data) | ||
| borefield.set_fluid_parameters(fluid_data) | ||
| borefield.set_max_avg_fluid_temperature(17) | ||
| borefield.set_min_avg_fluid_temperature(2) | ||
|
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||
|
|
||
| def make_results(borefield, name, sec_load=None): | ||
| # get further results | ||
| active_cooling_array = borefield.load.eer.get_time_series_active_cooling(borefield.results.peak_injection, | ||
| borefield.load.month_indices) | ||
| yearly_share_active_cooling = np.sum( | ||
| np.reshape(borefield.load.hourly_cooling_load_simulation_period * active_cooling_array, | ||
| (borefield.load.simulation_period, 8760)), | ||
| axis=1) / borefield.load.yearly_injection_load_simulation_period * 100 | ||
| active_cooling_power = borefield.load.hourly_cooling_load_simulation_period * active_cooling_array | ||
| passive_cooling_power = borefield.load.hourly_cooling_load_simulation_period * np.invert(active_cooling_array) | ||
| active_cooling_energy = np.sum(np.reshape(active_cooling_power, (borefield.load.simulation_period, 8760)), axis=1) | ||
| passive_cooling_energy = np.sum(np.reshape(passive_cooling_power, (borefield.load.simulation_period, 8760)), axis=1) | ||
|
|
||
| # print numerical results | ||
| print(f'\n{name}') | ||
| print(f'Average SEER {borefield.load.SEER:.2f}') | ||
| print( | ||
| f'Geothermal heating: {borefield.load.max_peak_heating:.2f}kW | {borefield.load.yearly_average_heating_load / 1000:.2f}MWh') | ||
| print(f'Geothermal active: {np.max(active_cooling_power):.2f}kW | {np.mean(active_cooling_energy) / 1000:.2f}MWh') | ||
| print( | ||
| f'Geothermal passive: {np.max(passive_cooling_power):.2f}kW | {np.mean(passive_cooling_energy) / 1000:.2f}MWh') | ||
| if sec_load is not None: | ||
| print( | ||
| f'LW cooling: {np.max(sec_load.max_peak_cooling):.2f}kW | {sec_load.yearly_average_cooling_load / 1000:.2f}MWh') | ||
| print( | ||
| f'LW heating: {np.max(sec_load.max_peak_heating):.2f}kW | {sec_load.yearly_average_heating_load / 1000:.2f}MWh') | ||
|
|
||
| make_TCO(borefield, sec_load) | ||
|
|
||
| # plot active/passive and SEER | ||
| fig3, ax5 = plt.subplots() | ||
| ax5.plot(range(1, borefield.load.simulation_period + 1), borefield.load.yearly_SEER, linestyle='-', label='SEER') | ||
| ax2 = ax5.twinx() | ||
| ax2.plot(range(1, borefield.load.simulation_period + 1), yearly_share_active_cooling, linestyle='--', | ||
| label='Actief koelen') | ||
|
|
||
| handles1, labels1 = ax5.get_legend_handles_labels() | ||
| handles2, labels2 = ax2.get_legend_handles_labels() | ||
| handles = handles1 + handles2 | ||
| labels = labels1 + labels2 | ||
| ax5.legend(handles, labels, loc='upper center', ncol=2) | ||
| ax5.set_xlim(left=1, right=borefield.load.simulation_period) | ||
| ax5.set_ylim(bottom=7, top=15) | ||
| ax2.set_ylim(bottom=30, top=70) | ||
| ax5.set_xlabel('Tijd [jaar]') | ||
| ax5.set_ylabel(f'Jaarlijks SEER [-]') | ||
| ax2.set_ylabel(f'Jaarlijks aandeel actieve koeling [%]') | ||
|
|
||
| if sec_load is None: | ||
| # hybrid graph | ||
| fig1, ax1 = plt.subplots() | ||
| # First pie chart - Cooling load | ||
| labels = ['BEO (A)', 'BEO (P)'] | ||
| sizes = [np.mean(active_cooling_energy), np.mean(passive_cooling_energy)] | ||
| ax1.pie(sizes, labels=labels, autopct='%1.1f%%') | ||
| ax1.set_title('Aandeel koeling') | ||
|
|
||
| else: | ||
| # hybrid graph | ||
| fig1, ax1 = plt.subplots() | ||
| # First pie chart - Cooling load | ||
| labels = ['BEO (A)', 'BEO (P)', 'LW'] | ||
| sizes = [np.mean(active_cooling_energy), np.mean(passive_cooling_energy), sec_load.yearly_average_cooling_load] | ||
| ax1.pie(sizes, labels=labels, autopct='%1.1f%%') | ||
| ax1.set_title('Aandeel koeling') | ||
|
|
||
| # energy graph | ||
| fig2, ax3 = plt.subplots() | ||
|
|
||
| # Add sorted loads to plot | ||
| ax3.plot(range(1, borefield.load.simulation_period + 1), | ||
| borefield.load.yearly_heating_load_simulation_period / 1000, | ||
| 'r-', label='Geothermische verwarming') | ||
| ax3.plot(range(1, borefield.load.simulation_period + 1), | ||
| borefield.load.yearly_cooling_load_simulation_period / 1000, | ||
| 'b-', label='Geothermische koeling') | ||
|
|
||
| # Add a second y-axis to the right | ||
| ax4 = ax3.twinx() | ||
|
|
||
| # Optionally, plot something on the second y-axis | ||
| ax4.plot(range(1, borefield.load.simulation_period + 1), borefield.load.yearly_heating_peak_simulation_period, | ||
| 'r--', | ||
| label='Geothermische piekverwarming') | ||
| ax4.plot(range(1, borefield.load.simulation_period + 1), borefield.load.yearly_cooling_peak_simulation_period, | ||
| 'b--', | ||
| label='Geothermische piekkoeling') | ||
|
|
||
| # Combine handles and labels from both axes | ||
| handles1, labels1 = ax3.get_legend_handles_labels() | ||
| handles2, labels2 = ax4.get_legend_handles_labels() | ||
| handles = handles1 + handles2 | ||
| labels = labels1 + labels2 | ||
|
|
||
| # Plot legend with combined handles and labels | ||
| ax3.legend(handles, labels) | ||
|
|
||
| ax3.set_xlim(left=1, right=borefield.load.simulation_period) | ||
| ax3.set_xlabel('Tijd [jaar]') | ||
| ax3.set_ylabel(f'Energie [MWh]') | ||
|
|
||
| # Optional: set labels and properties for the second y-axis | ||
| ax4.set_ylabel(f'Vermogen [kW]') | ||
|
|
||
| # plot borefield | ||
| # borefield.print_temperature_profile(plot_hourly=True) | ||
|
|
||
|
|
||
| def make_TCO(borefield, sec_load): | ||
| active_cooling_array = borefield.load.eer.get_time_series_active_cooling(borefield.results.peak_injection, | ||
| borefield.load.month_indices) | ||
| active_cooling_power = borefield.load.hourly_cooling_load_simulation_period * active_cooling_array | ||
| passive_cooling_power = borefield.load.hourly_cooling_load_simulation_period * np.invert(active_cooling_array) | ||
| active_cooling_energy = np.sum(np.reshape(active_cooling_power, (borefield.load.simulation_period, 8760)), | ||
| axis=1) | ||
| passive_cooling_energy = np.sum(np.reshape(passive_cooling_power, (borefield.load.simulation_period, 8760)), | ||
| axis=1) | ||
|
|
||
| electricity_consumption_per_year = borefield.load.yearly_electricity_consumption | ||
| peak_ac = np.max(active_cooling_power) | ||
| peak_pc = np.max(passive_cooling_power) | ||
| peak_heating = borefield.load.max_peak_heating | ||
|
|
||
| investment_cost = max(peak_heating, | ||
| peak_ac) * COST_GSHP + peak_pc * COST_HEX + borefield.number_of_boreholes * borefield.H * COST_BOREFIELD | ||
|
|
||
| if sec_load is not None: | ||
| electricity_consumption_per_year += sec_load.yearly_cooling_load_simulation_period / SEER_LW | ||
| investment_cost += max(np.max(sec_load.max_peak_cooling), 1481) * COST_ASHP | ||
| else: | ||
| # there is always an ASHP | ||
| investment_cost += 1481 * COST_ASHP | ||
|
|
||
| TCO = investment_cost + np.sum( | ||
| [electricity_consumption_per_year[i - 1] * E_PRICE / (1 + RDR) ** i for i in range(1, 26)]) | ||
| print('---------------------------------------') | ||
| print(f'Investment: €{investment_cost:,.0f}') | ||
| print( | ||
| f'Electricity cost: €{np.sum([electricity_consumption_per_year[i - 1] * E_PRICE / (1 + RDR) ** i for i in range(1, 26)]):,.0f}') | ||
| print(f'TCO: €{TCO:,.0f}') | ||
|
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||
|
|
||
| # do calculations | ||
| # 1) all load on one field | ||
| borefield.set_max_avg_fluid_temperature(17) | ||
| borefield.calculate_temperatures(hourly=True) | ||
| make_results(borefield, 'All load on one field') | ||
|
|
||
| # 2p) optimise power (100% passive) | ||
| _, sec_load = borefield.optimise_load_profile_power(combined) | ||
| borefield.calculate_temperatures(hourly=True) | ||
| make_results(borefield, 'Optimise power, 100% passive', sec_load) | ||
|
|
||
| # # 2e) optimise energy (100% passive) | ||
| # borefield.set_max_avg_fluid_temperature(16) | ||
| # _, sec_load = borefield.optimise_load_profile_energy(combined) | ||
| # borefield.calculate_temperatures(hourly=True) | ||
| # make_results(borefield, 'Optimise energy, 100% passive', sec_load) | ||
|
|
||
| # # 3p) optimise power | ||
| # borefield.set_max_avg_fluid_temperature(25) | ||
| # _, sec_load = borefield.optimise_load_profile_power(combined) | ||
| # borefield.calculate_temperatures(hourly=True) | ||
| # make_results(borefield, 'Optimise power', sec_load) | ||
| # | ||
| # # 3e) optimise energy | ||
| # borefield.set_max_avg_fluid_temperature(25) | ||
| # _, sec_load = borefield.optimise_load_profile_energy(combined) | ||
| # borefield.calculate_temperatures(hourly=True) | ||
| # make_results(borefield, 'Optimise energy', sec_load) | ||
|
|
||
| # adapt size borefield | ||
|
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||
| borefield_smaller = [bor for bor in borefield1 if bor.y < 74] | ||
| borefield.borefield = borefield_smaller | ||
| # 4p) optimise power | ||
| borefield.set_max_avg_fluid_temperature(25) | ||
| _, sec_load = borefield.optimise_load_profile_power(combined) | ||
| borefield.calculate_temperatures(hourly=True) | ||
| make_results(borefield, 'Optimise power, +- 50% koelvermogen', sec_load) | ||
|
|
||
| # # 4e) optimise energy | ||
| # borefield.set_max_avg_fluid_temperature(25) | ||
| # _, sec_load = borefield.optimise_load_profile_energy(combined) | ||
| # borefield.calculate_temperatures(hourly=True) | ||
| # make_results(borefield, 'Optimise energy, max 50% cooling', sec_load) |
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