Example of using the DB solver to calculate the efficiency map of a 3J solar cell ================================================================================= .. image:: MJ_efficiency_map.png :width: 40% .. image:: MJ_IV_optimal.png :width: 40% .. code-block:: Python import numpy as np import matplotlib.pyplot as plt from matplotlib import cm from solcore.light_source import LightSource from solcore.solar_cell import SolarCell from solcore.solar_cell_solver import solar_cell_solver from solcore.structure import Junction # Illumination spectrum wl = np.linspace(300, 4000, 4000) * 1e-9 light = LightSource(source_type='standard', version='AM1.5g', x=wl, output_units='photon_flux_per_m') T = 298 V = np.linspace(0, 5, 500) # This function assembles the solar cell and calculates the IV cruve def solve_MJ(EgBot, EgMid, EgTop): db_junction0 = Junction(kind='DB', T=T, Eg=EgBot, A=1, R_shunt=np.inf, n=3.5) db_junction1 = Junction(kind='DB', T=T, Eg=EgMid, A=1, R_shunt=np.inf, n=3.5) db_junction2 = Junction(kind='DB', T=T, Eg=EgTop, A=1, R_shunt=np.inf, n=3.5) my_solar_cell = SolarCell([db_junction2, db_junction1, db_junction0], T=T, R_series=0) solar_cell_solver(my_solar_cell, 'iv', user_options={'T_ambient': T, 'db_mode': 'top_hat', 'voltages': V, 'light_iv': True, 'internal_voltages': np.linspace(-6, 5, 1100), 'wavelength': wl, 'mpp': True, 'light_source': light}) return my_solar_cell # We create an efficiency map using Eg0 as the bandgap of the bottom junction and scanning the bandgaps of the middle # and top junctions N1 = 30 N2 = 30 Eg0 = 1.12 all_Eg1 = np.linspace(1.3, 1.8, N1) all_Eg2 = np.linspace(1.7, 2.4, N2) eff = np.zeros((N1, N2)) N = N1 * N2 index = 0 Effmax = -1 Eg1_max = all_Eg1[0] Eg2_max = all_Eg2[0] # And we run the calculation for i, Eg1 in enumerate(all_Eg1): for j, Eg2 in enumerate(all_Eg2): my_solar_cell = solve_MJ(Eg0, Eg1, Eg2) mpp = my_solar_cell.iv.Pmpp eff[i, j] = mpp if mpp > Effmax: Effmax = mpp Eg1_max = Eg1 Eg2_max = Eg2 index += 1 print(int(index / N * 100), '%\n') optimum_MJ = solve_MJ(Eg0, Eg1_max, Eg2_max) plt.figure(1) plt.plot(V, optimum_MJ.iv.IV[1], 'k', linewidth=4, label='Total') plt.plot(V, -optimum_MJ[0].iv(V), 'r', label='Bottom') plt.plot(V, -optimum_MJ[1].iv(V), 'g', label='Middle') plt.plot(V, -optimum_MJ[2].iv(V), 'b', label='Top') plt.ylim(0, 200) plt.xlim(0, 3.75) plt.legend() plt.xlabel('Voltage (V)') plt.ylabel('Current (A/m\$^2\$)') plt.figure(2) eff = eff / light.power_density * 100 plt.contourf(all_Eg2, all_Eg1, eff, 50, cmap=cm.jet) plt.xlabel('TOP Eg (eV)') plt.ylabel('MID Eg (eV)') cbar = plt.colorbar() cbar.set_label('Efficiency (%)', rotation=270, labelpad=10) plt.tight_layout() plt.show()