updated historical silver demand

working on adding literature comparisons

PV_ICE/baselines/SupportingMaterial/Ag_Literature_Compare.csv

@@ -0,0 +1,32 @@
+Year,Hallam 2022
+2020,3.77
+2021,6.2
+2022,7
+2023,7.5
+2024,8.1
+2025,9.1
+2026,10.7181842
+2027,11.84964576
+2028,13.06201347
+2029,14.92023091
+2030,15.40461821
+2031,15.4838625
+2032,15.23939473
+2033,14.8
+2034,15
+2035,15
+2036,15.88034637
+2037,16.76873961
+2038,17.6
+2039,18.74713548
+2040,19.1
+2041,19
+2042,18.86416514
+2043,18.70069098
+2044,18.65
+2045,19
+2046,20.31382839
+2047,21.6
+2048,23.30420712
+2049,24.3
+2050,25.80923642

PV_ICE/baselines/SupportingMaterial/WorldSilverSurvey-AgProduction-PVuse.csv

@@ -0,0 +1,48 @@
+Year,PV Silver Demand [million oz],PV Silver Demand [metric tonnes],Silver Production [million ounces],Silver Production [metric tonnes],Total Supply  [million troy ounces,Total Supply [metric tonnes]
+2004,,,613.6,19084.94293,872,27122.01798
+2005,,,639.7,19896.73727,954.1,29675.59329
+2006,,,642.7,19990.04697,915.6,28478.11888
+2007,,,666.1,20717.86259,887.3,27597.89742
+2008,,,713.8,22201.48673,905.7,28170.19688
+2009,,,750.6,23346.08566,911.7,28356.81627
+2010,,,754.6,23470.49858,1070.7,33302.2301
+2011,67.4,2096.357812,792.3,24643.09042,1037.6,32272.71313
+2012,55,1710.677739,795.9,24755.06205,1005.8,31283.63037
+2013,50.5,1570.713197,845.3,26291.56169,1027.3,31952.34985
+2014,48.4,1505.396411,882.1,27436.16062,1054.2,32789.02678
+2015,54.1,1682.684831,896.9,27896.48845,1046.9,32561.97319
+2016,93.7,2914.372803,899.8,27986.68782,1046.4,32546.42157
+2017,101.8,3166.30898,863.6,26860.75083,1011.7,31467.13944
+2018,92.5,2877.048925,850.3,26447.07785,1000,31103.23163
+2019,97.8,3041.896053,836.6,26020.96358,999.5,31087.68001
+2020,100,3110.323163,782.2,24328.94778,957.9,29793.78557
+2021,110,3421.355479,827.6,25741.03449,1004.5,31243.19617
+2022,140.3,4363.783397,822.4,25579.29769,1004.7,31249.41681
+2023,161.1,5010.730615,842.1,26192.03135,1024.9,31877.70209
+2024,,,,,,
+2025,,,,,,
+2026,,,,,,
+2027,,,,,,
+2028,,,,,,
+2029,,,,,,
+2030,,,,,,
+2031,,,,,,
+2032,,,,,,
+2033,,,,,,
+2034,,,,,,
+2035,,,,,,
+2036,,,,,,
+2037,,,,,,
+2038,,,,,,
+2039,,,,,,
+2040,,,,,,
+2041,,,,,,
+2042,,,,,,
+2043,,,,,,
+2044,,,,,,
+2045,,,,,,
+2046,,,,,,
+2047,,,,,,
+2048,,,,,,
+2049,,,,,,
+2050,,,,,,

docs/publications/(dev)10c-EnergyAnalysis_Silver_Demand.py

@@ -40,18 +40,25 @@
 print("PV_ICE version ", PV_ICE.__version__)
 
 
+# In[4]:
+
+
+plt.rcParams.update({'font.size': 14})
+plt.rcParams['figure.figsize'] = (8, 6)
+
+
 # This journal pulls out the silver demand projections for the 3 projected technologies, PERC, TOPCon, SHJ, as projected for the Energy Analysis paper (10a). We also do a literature comparison, since this is a highly studied space.
 # 
 # We pull in the output dataframes from journal 10a and do graphing here.
 
-# In[4]:
+# In[5]:
 
 
 cc_13scen_yearly_dataOut = pd.read_csv(os.path.join(inputfolder, 'EnergyAnalysis','Deploy_MirletzLinear','cc_13scen_yearly.csv'),
            index_col = 0)
 
 
-# In[5]:
+# In[6]:
 
 
 silver_annual_demand = cc_13scen_yearly_dataOut.filter(like='VirginStock_silver') #tonnes
@@ -61,7 +68,7 @@
 silver_annual_demand_shj = silver_annual_demand.filter(like='r_SHJ')
 
 
-# In[6]:
+# In[7]:
 
 
 plt.plot(silver_annual_demand_pvice, color='black', label='Baseline')
@@ -85,9 +92,60 @@
 plt.xlim(2000,2050)
 plt.ylabel('Virgin Material Demand for Silver\n[Metric Tonnes]')
 plt.legend()
+plt.title('Silver Demand by Technology to Achieve 75 TW')
+
+
+# ## Add in Historical Silver Demand and Other Literature projections for Comparison
+
+# In[9]:
+
+
+ag_WSS = pd.read_csv(os.path.join(supportMatfolder, 'WorldSilverSurvey-AgProduction-PVuse.csv'), index_col=0)
+ag_WSS.head()
+
+
+# In[10]:
+
+
+ag_WSS_flatforward = ag_WSS.interpolate()
+
+
+# In[12]:
+
+
+plt.bar(silver_annual_demand_shj.index, silver_annual_demand_shj.iloc[:2051,0], color='tab:red', label='SHJ')
+plt.bar(silver_annual_demand_topcon.index, silver_annual_demand_topcon.iloc[:2051,0], color='tab:orange', label='TOPCon')
+plt.bar(silver_annual_demand_pvice.index, silver_annual_demand_pvice.iloc[:2051,0], color='black', label='Baseline')
+plt.bar(silver_annual_demand_perc.index, silver_annual_demand_perc.iloc[:2051,0], color='tab:blue', label='PERC')
+
+plt.plot(ag_WSS.index, ag_WSS['PV Silver Demand [metric tonnes]'], color='black', label='Historical PV Silver Demand')
+plt.plot(ag_WSS.index, ag_WSS['Silver Production [metric tonnes]'], color='gray', ls='--', label='Historical Mining production')
+plt.plot(ag_WSS_flatforward.loc[2023:,'Silver Production [metric tonnes]'], color='red', ls='--', label='Constant Current Mining')
+plt.plot(ag_WSS.index, ag_WSS['Total Supply [metric tonnes]'], color='gray', ls='-.', label='Historical Total Supply')
+plt.plot(ag_WSS_flatforward.loc[2023:,'Total Supply [metric tonnes]'], color='purple', ls='-.', label='Constant Total Supply')
+
+#plt.grid(axis='y', color='0.9', ls='--', zorder=0)
+#plt.set_axisbelow(True)
+plt.legend(fontsize=12)
+plt.ylim(0,)
+plt.xlim(2005,2050)
+plt.ylabel('Virgin Material Demand for Silver\n[Metric Tonnes]')
+plt.title('Silver Demand by Technology to Achieve 75 TW')
+
+
+# In[13]:
+
+
+pd.read_csv(os.path.join(supportMatfolder, 'Ag_Literature_Compare.csv'))
+
+
+# ### Energy Compare of these techs
+
+# In[ ]:
+
+
 
 
-# ### Add in Literature comparison of projections
 
 # In[ ]: