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Commit 67923556 authored by Jonas Brucksch's avatar Jonas Brucksch
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Drop heat pump for now and input_profile genration depending on el-profile

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Subproject commit a23357dda91a859b2aca04bb833d11e935106a60 Subproject commit c9a8706272165916d927210c8f58d9e282388fc2
input_files/models/prosumer_models/building_types_aachen_2022/running_179_2022.csv 0 → 100644
+ 197
− 0
View file @ 67923556
,ID_Building,reference_el_demand,reference_heat_demand,reference_hot_water,profile_el,profile_th,Building_type,name_building
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31,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_179_31
32,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_179_32
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60,A_0_PV9.0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_PV9.0_Q_179_60
61,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_179_61
62,A_2,20488.69532,82474.4835,5937.033024,h0,MFH,1,A_2_Q_179_62
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68,A_2,20488.69532,82474.4835,5937.033024,h0,MFH,1,A_2_Q_179_68
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82,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_179_82
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85,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_179_85
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174,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_179_174
175,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_179_175
176,A_0_PV9.0_HP,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_PV9.0_HP_Q_179_176
177,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_179_177
178,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_179_178
179,AC_0,13259.27221,53373.41447,3842.154699,h0+g1,GMF,0,AC_0_Q_179_179
180,A_5,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_Q_179_180
181,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_179_181
182,A_5,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_Q_179_182
183,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_179_183
184,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_179_184
185,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_179_185
186,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_179_186
187,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_179_187
188,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_179_188
189,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_179_189
190,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_179_190
191,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_179_191
192,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_179_192
193,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_179_193
194,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_179_194
195,A_2,20488.69532,82474.4835,5937.033024,h0,MFH,1,A_2_Q_179_195
input_files/models/prosumer_models/building_types_aachen_2022/running_215_2022.csv 0 → 100644
+ 195
− 0
View file @ 67923556
,ID_Building,reference_el_demand,reference_heat_demand,reference_hot_water,profile_el,profile_th,Building_type,name_building
0,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_0
1,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_1
2,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_2
3,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_3
4,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_4
5,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_215_5
6,A_2,20488.69532,82474.4835,5937.033024,h0,MFH,1,A_2_Q_215_6
7,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_7
8,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_8
9,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_9
10,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_10
11,A_2,20488.69532,82474.4835,5937.033024,h0,MFH,1,A_2_Q_215_11
12,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_12
13,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_13
14,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_14
15,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_15
16,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_16
17,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_17
18,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_18
19,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_19
20,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_20
21,A_13_PV5.0,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_PV5.0_Q_215_21
22,A_0_PV9.0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_PV9.0_Q_215_22
23,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_23
24,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_24
25,A_21_PV28.0,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_PV28.0_Q_215_25
26,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_26
27,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_27
28,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_28
29,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_29
30,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_215_30
31,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_31
32,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_32
33,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_33
34,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_34
35,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_215_35
36,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_36
37,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_37
38,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_38
39,A_15_PV1.0,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_PV1.0_Q_215_39
40,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_215_40
41,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_41
42,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_42
43,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_43
44,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_44
45,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_45
46,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_46
47,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_47
48,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_48
49,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_215_49
50,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_50
51,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_51
52,A_13_PV9.0,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_PV9.0_Q_215_52
53,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_53
54,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_54
55,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_55
56,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_215_56
57,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_57
58,G_1_PV30.0_HP,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_PV30.0_HP_Q_215_58
59,A_19_STR,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_STR_Q_215_59
60,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_60
61,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_61
62,A_0_PV5.0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_PV5.0_Q_215_62
63,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_63
64,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_64
65,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_65
66,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_66
67,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_67
68,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_68
69,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_69
70,A_0_PV5.0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_PV5.0_Q_215_70
71,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_71
72,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_72
73,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_73
74,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_74
75,G_1_PV7.0,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_PV7.0_Q_215_75
76,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_76
77,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_77
78,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_215_78
79,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_79
80,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_80
81,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_81
82,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_215_82
83,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_83
84,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_84
85,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_85
86,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_86
87,A_9,24734.64265,99565.97261,7167.386111,h0,MFH,1,A_9_Q_215_87
88,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_88
89,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_215_89
90,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_90
91,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_91
92,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_92
93,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_93
94,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_94
95,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_95
96,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_96
97,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_97
98,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_98
99,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_99
100,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_100
101,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_101
102,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_102
103,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_103
104,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_104
105,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_105
106,A_5,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_Q_215_106
107,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_107
108,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_215_108
109,A_2,20488.69532,82474.4835,5937.033024,h0,MFH,1,A_2_Q_215_109
110,A_5_PV8.0_HP,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_PV8.0_HP_Q_215_110
111,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_111
112,N_0,16602.35612,29318.56517,1312.394883,g1,GBD,0,N_0_Q_215_112
113,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_113
114,A_22_PV9.0,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_PV9.0_Q_215_114
115,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_115
116,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_116
117,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_117
118,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_118
119,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_119
120,A_0_PV8.0_STR,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_PV8.0_STR_Q_215_120
121,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_121
122,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_122
123,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_123
124,E_0,9979.480577,27156.03132,1075.905206,g4,GHA,0,E_0_Q_215_124
125,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_215_125
126,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_126
127,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_127
128,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_128
129,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_129
130,A_2,20488.69532,82474.4835,5937.033024,h0,MFH,1,A_2_Q_215_130
131,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_131
132,A_14_STR,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_STR_Q_215_132
133,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_133
134,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_215_134
135,A_26,44777.02232,180243.8726,12975.08973,h0,MFH,1,A_26_Q_215_135
136,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_136
137,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_215_137
138,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_138
139,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_139
140,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_140
141,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_141
142,A_2,20488.69532,82474.4835,5937.033024,h0,MFH,1,A_2_Q_215_142
143,A_5,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_Q_215_143
144,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_144
145,E_0,9979.480577,27156.03132,1075.905206,g4,GHA,0,E_0_Q_215_145
146,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_146
147,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_147
148,N_0,16602.35612,29318.56517,1312.394883,g1,GBD,0,N_0_Q_215_148
149,N_0,16602.35612,29318.56517,1312.394883,g1,GBD,0,N_0_Q_215_149
150,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_150
151,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_151
152,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_152
153,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_153
154,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_154
155,A_0_PV9.0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_PV9.0_Q_215_155
156,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_156
157,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_157
158,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_158
159,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_159
160,A_5,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_Q_215_160
161,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_161
162,A_15,1093.874944,4403.24626,316.9734123,h0,MFH,1,A_15_Q_215_162
163,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_163
164,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_164
165,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_165
166,A_21_PV10.0,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_PV10.0_Q_215_166
167,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_167
168,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_168
169,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_215_169
170,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_170
171,G_1,6694.222472,19832.34201,2013.477135,g2,GGA,0,G_1_Q_215_171
172,A_5,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_Q_215_172
173,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_173
174,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_174
175,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_215_175
176,A_19_PV10.0,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_PV10.0_Q_215_176
177,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_177
178,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_178
179,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_215_179
180,A_2,20488.69532,82474.4835,5937.033024,h0,MFH,1,A_2_Q_215_180
181,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_181
182,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_182
183,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_183
184,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_184
185,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_215_185
186,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_186
187,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_215_187
188,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_188
189,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_189
190,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_190
191,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_215_191
192,U_0,483.909035,16624.73222,3890.554002,g3,GKO,0,U_0_Q_215_192
193,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_215_193
input_files/models/prosumer_models/building_types_aachen_2022/running_77_2022.csv 0 → 100644
+ 200
− 0
View file @ 67923556
,ID_Building,reference_el_demand,reference_heat_demand,reference_hot_water,profile_el,profile_th,Building_type,name_building
0,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_0
1,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_1
2,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_2
3,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_3
4,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_4
5,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_5
6,E_0,9979.480577,27156.03132,1075.905206,g4,GHA,0,E_0_Q_77_6
7,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_7
8,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_8
9,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_9
10,A_21_PV28.0,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_PV28.0_Q_77_10
11,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_11
12,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_12
13,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_13
14,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_14
15,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_15
16,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_16
17,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_17
18,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_18
19,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_19
20,A_5_PV8.0,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_PV8.0_Q_77_20
21,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_21
22,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_22
23,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_23
24,A_11,36178.51608,145631.7438,10483.4906,h0,MFH,1,A_11_Q_77_24
25,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_25
26,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_26
27,L_0,4160.278216,11840.43691,468.9450257,l2,GGB,0,L_0_Q_77_27
28,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_28
29,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_29
30,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_77_30
31,A_11,36178.51608,145631.7438,10483.4906,h0,MFH,1,A_11_Q_77_31
32,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_32
33,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_33
34,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_34
35,AC_0,9386.775092,47801.37623,2003.879256,h0+g1,GMF,0,AC_0_Q_77_35
36,A_4,54611.4143,219830.893,15824.81291,h0,MFH,1,A_4_Q_77_36
37,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_37
38,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_38
39,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_77_39
40,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_40
41,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_41
42,A_11,36178.51608,145631.7438,10483.4906,h0,MFH,1,A_11_Q_77_42
43,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_43
44,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_44
45,E_0_PV8.0,9979.480577,27156.03132,1075.905206,g4,GHA,0,E_0_PV8.0_Q_77_45
46,AC_0,8095.942719,45944.03015,1391.120775,h0+g1,GMF,0,AC_0_Q_77_46
47,AC_0,8095.942719,45944.03015,1391.120775,h0+g1,GMF,0,AC_0_Q_77_47
48,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_48
49,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_77_49
50,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_50
51,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_51
52,A_4,54611.4143,219830.893,15824.81291,h0,MFH,1,A_4_Q_77_52
53,C_0,5895.243735,45146.8427,177.0449093,g1,GBD,0,C_0_Q_77_53
54,A_21_PV28.0_STR,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_PV28.0_STR_Q_77_54
55,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_55
56,D_0,4108.428458,11693.41854,74.68525454,l0,GMK,0,D_0_Q_77_56
57,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_77_57
58,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_58
59,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_77_59
60,A_11,36178.51608,145631.7438,10483.4906,h0,MFH,1,A_11_Q_77_60
61,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_61
62,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_62
63,A_4,54611.4143,219830.893,15824.81291,h0,MFH,1,A_4_Q_77_63
64,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_64
65,AC_0_PV30.0,7450.526532,45015.35711,1084.741535,h0+g1,GMF,0,AC_0_PV30.0_Q_77_65
66,A_27_PV4.0,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_PV4.0_Q_77_66
67,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_67
68,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_68
69,A_11,36178.51608,145631.7438,10483.4906,h0,MFH,1,A_11_Q_77_69
70,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_70
71,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_71
72,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_72
73,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_73
74,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_74
75,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_75
76,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_76
77,E_0,9979.480577,27156.03132,1075.905206,g4,GHA,0,E_0_Q_77_77
78,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_78
79,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_79
80,A_16_STR,67895.81632,273305.4641,19674.2495,h0,MFH,1,A_16_STR_Q_77_80
81,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_81
82,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_82
83,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_83
84,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_84
85,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_85
86,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_86
87,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_77_87
88,N_0,16602.35612,29318.56517,1312.394883,g1,GBD,0,N_0_Q_77_88
89,A_5_PV4.0,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_PV4.0_Q_77_89
90,A_16,67895.81632,273305.4641,19674.2495,h0,MFH,1,A_16_Q_77_90
91,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_91
92,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_92
93,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_93
94,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_94
95,A_5,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_Q_77_95
96,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_96
97,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_97
98,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_98
99,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_99
100,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_100
101,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_101
102,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_102
103,A_27_PV4.0,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_PV4.0_Q_77_103
104,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_104
105,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_105
106,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_106
107,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_107
108,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_108
109,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_109
110,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_110
111,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_111
112,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_112
113,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_113
114,A_4,54611.4143,219830.893,15824.81291,h0,MFH,1,A_4_Q_77_114
115,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_115
116,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_116
117,E_0,9979.480577,27156.03132,1075.905206,g4,GHA,0,E_0_Q_77_117
118,A_16,67895.81632,273305.4641,19674.2495,h0,MFH,1,A_16_Q_77_118
119,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_77_119
120,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_77_120
121,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_121
122,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_122
123,AC_0,13259.27221,53373.41447,3842.154699,h0+g1,GMF,0,AC_0_Q_77_123
124,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_77_124
125,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_125
126,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_126
127,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_127
128,A_0_PV9.0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_PV9.0_Q_77_128
129,A_11,36178.51608,145631.7438,10483.4906,h0,MFH,1,A_11_Q_77_129
130,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_77_130
131,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_131
132,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_132
133,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_133
134,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_134
135,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_135
136,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_136
137,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_137
138,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_138
139,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_139
140,A_14_STR,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_STR_Q_77_140
141,A_21_PV28.0_HP_STR,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_PV28.0_HP_STR_Q_77_141
142,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_142
143,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_143
144,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_144
145,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_145
146,A_13_PV9.0,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_PV9.0_Q_77_146
147,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_147
148,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_148
149,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_149
150,A_22_PV9.0,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_PV9.0_Q_77_150
151,L_0,4160.278216,11840.43691,468.9450257,l2,GGB,0,L_0_Q_77_151
152,AC_0_PV8.0,13259.27221,53373.41447,3842.154699,h0+g1,GMF,0,AC_0_PV8.0_Q_77_152
153,A_5,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_Q_77_153
154,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_77_154
155,A_11,36178.51608,145631.7438,10483.4906,h0,MFH,1,A_11_Q_77_155
156,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_77_156
157,L_0,4160.278216,11840.43691,468.9450257,l2,GGB,0,L_0_Q_77_157
158,A_4_PV27.0,54611.4143,219830.893,15824.81291,h0,MFH,1,A_4_PV27.0_Q_77_158
159,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_159
160,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_77_160
161,C_0,5895.243735,45146.8427,177.0449093,g1,GBD,0,C_0_Q_77_161
162,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_77_162
163,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_77_163
164,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_164
165,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_77_165
166,A_5,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_Q_77_166
167,A_4,54611.4143,219830.893,15824.81291,h0,MFH,1,A_4_Q_77_167
168,L_0,4160.278216,11840.43691,468.9450257,l2,GGB,0,L_0_Q_77_168
169,A_24_PV9.0,29861.09516,120201.8167,8652.884205,h0,MFH,1,A_24_PV9.0_Q_77_169
170,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_170
171,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_171
172,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_172
173,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_173
174,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_77_174
175,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_175
176,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_176
177,E_0,9979.480577,27156.03132,1075.905206,g4,GHA,0,E_0_Q_77_177
178,A_19,8523.514643,34310.26021,2469.868732,h0,MFH,1,A_19_Q_77_178
179,AC_0,13259.27221,53373.41447,3842.154699,h0+g1,GMF,0,AC_0_Q_77_179
180,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_77_180
181,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_181
182,A_4_STR,54611.4143,219830.893,15824.81291,h0,MFH,1,A_4_STR_Q_77_182
183,A_11_STR,36178.51608,145631.7438,10483.4906,h0,MFH,1,A_11_STR_Q_77_183
184,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_184
185,A_13,6666.867267,26836.57626,1931.865866,h0,MFH,1,A_13_Q_77_185
186,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_186
187,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_187
188,A_21,5091.9992,20497.15697,1475.514519,h0,MFH,1,A_21_Q_77_188
189,A_22,13329.62261,53656.60053,3862.540216,h0,MFH,1,A_22_Q_77_189
190,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_190
191,A_11,36178.51608,145631.7438,10483.4906,h0,MFH,1,A_11_Q_77_191
192,A_27,2365.64327,9522.578367,685.4951961,h0,MFH,1,A_27_Q_77_192
193,A_0,3642.673994,14663.09355,1055.541872,h0,MFH,1,A_0_Q_77_193
194,A_4,54611.4143,219830.893,15824.81291,h0,MFH,1,A_4_Q_77_194
195,A_5,10739.11627,43228.86614,3111.886186,h0,MFH,1,A_5_Q_77_195
196,A_14,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_Q_77_196
197,A_4,54611.4143,219830.893,15824.81291,h0,MFH,1,A_4_Q_77_197
198,A_14_PV84.0_STR,16630.23974,66942.79025,4818.963874,h0,MFH,1,A_14_PV84.0_STR_Q_77_198
runme.py
+ 84
− 24
View file @ 67923556
...@@ -7,6 +7,8 @@ import Model_Library.Prosumer.main as main_prosumer ...@@ -7,6 +7,8 @@ import Model_Library.Prosumer.main as main_prosumer
import Model_Library.District.main as main_district import Model_Library.District.main as main_district
from enum import Enum from enum import Enum
import os import os
import random
import pickle
class SimulationScope(Enum): class SimulationScope(Enum):
PROSUMER = 1 PROSUMER = 1
...@@ -14,29 +16,55 @@ class SimulationScope(Enum): ...@@ -14,29 +16,55 @@ class SimulationScope(Enum):
simulation_scope = SimulationScope.DISTRICT simulation_scope = SimulationScope.DISTRICT
t_start = pd.Timestamp("2019-01-01 00:00:00") # start time of simulation t_start = pd.Timestamp("2019-01-01 00:00:00") # start time of simulation
t_horizon = 100 # number of time steps to be simulated t_horizon = 8760 # number of time steps to be simulated
t_step = 1 # length of a time step in hours t_step = 1 # length of a time step in hours
inputpath_dataframe = 'input_files/models/prosumer_models/building_types_aachen_2022/running_77_2022.csv'
#inputpath_dataframe = 'input_files/models/district_models/quarter_extraction_df_Q_0.csv'
building_types = pd.read_csv(inputpath_dataframe)
input_profile_dict = {'pv_factors_aachen_1': ['pv_factors', 'input_files/data/irradiance/aachen_pv_factors_ninja_2019_1h_to_2019_15min.csv'], input_profile_dict = {'pv_factors_aachen_1': ['pv_factors', 'input_files/data/irradiance/aachen_pv_factors_ninja_2019_1h_to_2019_15min.csv'],
'pv_factors_germany_1': ['pv_factors', 'input_files/data/irradiance/irr_ren_ninja_avg_Germany.csv'],
'temperature_1': ['air_temperature', 'input_files/data/temperature/temperature_TRY2010.csv'], 'temperature_1': ['air_temperature', 'input_files/data/temperature/temperature_TRY2010.csv'],
'elec_demand_htw': ['elec_demand', r"input_files\data\demand\electricity\PL_SUM_15.csv"], 'elec_demand_htw': ['elec_demand', 'input_files/data/demand/electricity/PL_SUM_15.csv'],
'room_heating_sfh_passive': ['room_heating_demand', 'input_files/data/demand/room_heating/synPRO_passive_single_family_house_rh_2021_to_2019_kW.csv'], 'room_heating_sfh_passive': ['room_heating_demand', 'input_files/data/demand/room_heating/synPRO_passive_single_family_house_rh_2021_to_2019_kW.csv'],
'dhw_shf_passive': ['hot_water_demand', 'input_files/data/demand/domestic_hot_water/synPRO_passive_single_family_house_dhw_2021_to_2019_kW.csv'], 'dhw_shf_passive': ['hot_water_demand', 'input_files/data/demand/domestic_hot_water/synPRO_passive_single_family_house_dhw_2021_to_2019_kW.csv'],
'room_heating_mfh_passive': ['room_heating_demand', 'input_files/data/demand/room_heating/synPRO_passive_multi_party_house_rh_2021_to_2019_kW.csv'],
'dhw_mhf_passive': ['hot_water_demand', 'input_files/data/demand/domestic_hot_water/synPRO_passive_multi_party_house_dhw_2021_to_2019_kW.csv'],
'elec_price_1': ['prices', 'input_files/data/prices/day-ahead/hourly_price.csv']} 'elec_price_1': ['prices', 'input_files/data/prices/day-ahead/hourly_price.csv']}
for i in building_types.index[44:55]:
if 'A_' in building_types.iloc[i]['ID_Building']:
pass
else:
if len(building_types['profile_el'][i]) > 2:
profile_list = building_types['profile_el'][i].split('+')
input_profile_dict['elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building'])] = ['elec_demand','generate',
building_types['reference_el_demand'][i],
profile_list[0]]
input_profile_dict['Add_elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building'])] = ['elec_demand','generate',
building_types['reference_el_demand'][i],
profile_list[1]]
else:
input_profile_dict['elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building'])] = ['elec_demand', 'generate',
building_types['reference_el_demand'][i],
building_types['profile_el'][i]]
input_profiles = Tooling.input_profile_processor.input_profile_processor.process_input_profiles(input_profile_dict, t_start, t_horizon, t_step) input_profiles = Tooling.input_profile_processor.input_profile_processor.process_input_profiles(input_profile_dict, t_start, t_horizon, t_step)
for i in input_profiles['elec_demand_htw']: for i in input_profiles['elec_demand_htw']:
input_profiles['ref_elec_demand_id_' + str(i)] = input_profiles['elec_demand_htw'][i] input_profiles['ref_elec_demand_id_' + str(i)] = input_profiles['elec_demand_htw'][i]
for i in input_profiles.keys():
if 'Add_' in i:
strings = i.split('Add_')
profile2 = input_profiles[i]
input_profiles[strings[1]] += profile2
# get the annual electric, heating and hw demand s of the example buildings # get the annual electric, heating and hw demand s of the example buildings
ref_yearly_elec_demand = input_profiles['elec_demand_htw'].sum()*t_step # in kWh ref_yearly_elec_demand = input_profiles['elec_demand_htw'].sum()*t_step # in kWh
ref_yearly_rh_demand = input_profiles['room_heating_sfh_passive'].sum()*t_step # in kWh ref_yearly_rh_demand = input_profiles['room_heating_mfh_passive'].sum()*t_step # in kWh
ref_yearly_dhw_demand = input_profiles['dhw_shf_passive'].sum()*t_step # in kWh ref_yearly_dhw_demand = input_profiles['dhw_mhf_passive'].sum()*t_step # in kWh
inputpath_dataframe = r'input_files\models\prosumer_models\building_types_aachen\running_77_2022.csv'
#inputpath_dataframe = 'input_files/models/district_models/quarter_extraction_df_Q_0.csv'
building_types = pd.read_csv(inputpath_dataframe)
# Create a new column in building_types to store the index of the closest value # Create a new column in building_types to store the index of the closest value
building_types['closest_index'] = building_types.apply( building_types['closest_index'] = building_types.apply(
...@@ -47,8 +75,36 @@ building_types['closest_index'] = building_types.apply( ...@@ -47,8 +75,36 @@ building_types['closest_index'] = building_types.apply(
# 'topology_path': path to directory that contains the matrices that define the prosumer topology # 'topology_path': path to directory that contains the matrices that define the prosumer topology
prosumer_dict = {} prosumer_dict = {}
for i in building_types.index[0:10]: # drop the heatpump
building_types.drop(index=141, inplace=True)
building_types.reset_index(inplace=True)
# building_types.index[53:61]
community_sample = random.sample(range(197),30)
# how many storages
ids = building_types.loc[:]['ID_Building']
string_str = 'STR'
string_pv = 'PV'
string_ac = 'AC'
count_str = 0
count_pv = 0
count_ac = 0
for string in ids:
count_str += string.count(string_str)
count_pv += string.count(string_pv)
count_ac += string.count(string_ac)
print('Number of storages: ' + str(count_str))
print('Number of PV: ' + str(count_pv))
print('Number of AC: ' + str(count_ac))
consumer_count = 0
for i in building_types.index[44:55]:
if 'A_' in building_types.iloc[i]['ID_Building']:
# get the index of the reference profile for this building type # get the index of the reference profile for this building type
index_ref_elec_demand = building_types['closest_index'][i] index_ref_elec_demand = building_types['closest_index'][i]
...@@ -58,36 +114,39 @@ for i in building_types.index[0:10]: ...@@ -58,36 +114,39 @@ for i in building_types.index[0:10]:
input_profiles['elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building'])] = scaled_heat_demand input_profiles['elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building'])] = scaled_heat_demand
# ROOM HEATING # ROOM HEATING
scaled_heat_demand = building_types['reference_heat_demand'][i] / ref_yearly_rh_demand * input_profiles['room_heating_sfh_passive'] scaled_heat_demand = building_types['reference_heat_demand'][i] / ref_yearly_rh_demand * input_profiles['room_heating_mfh_passive']
input_profiles['room_heat_demand_prosumer_' + str(building_types.loc[i,'ID_Building'])] = scaled_heat_demand input_profiles['room_heat_demand_prosumer_' + str(building_types.loc[i,'ID_Building'])] = scaled_heat_demand
# HOT WATER # HOT WATER
scaled_hot_water_demand = building_types['reference_hot_water'][i] / ref_yearly_rh_demand * input_profiles['dhw_shf_passive'] scaled_hot_water_demand = building_types['reference_hot_water'][i] / ref_yearly_rh_demand * input_profiles['dhw_mhf_passive']
input_profiles['hot_water_demand_prosumer_' + str(building_types.loc[i, 'ID_Building'])] = scaled_hot_water_demand input_profiles['hot_water_demand_prosumer_' + str(building_types.loc[i, 'ID_Building'])] = scaled_hot_water_demand
if 'PV' in building_types.loc[i,'ID_Building'] and 'HP' in building_types.loc[i, 'ID_Building']: if 'PV' in building_types.loc[i,'ID_Building'] and 'HP' in building_types.loc[i, 'ID_Building']:
prosumer_dict[building_types.loc[i,'name_building']]= {'config_path': 'input_files/models/prosumer_models/building_types_aachen/'+ str(building_types.loc[i,'ID_Building']) + '/config.csv', prosumer_dict[building_types.loc[i,'name_building']]= {'config_path': 'input_files/models/prosumer_models/building_types_aachen_2022/'+ str(building_types.loc[i,'ID_Building']) + '/config.csv',
'topology_path': 'input_files/models/prosumer_models/building_types_aachen/'+ str(building_types.loc[i,'ID_Building']), 'topology_path': 'input_files/models/prosumer_models/building_types_aachen_2022/'+ str(building_types.loc[i,'ID_Building']),
'profiles':{'elec_cns': 'elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building']), 'profiles':{'elec_cns': 'elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building']),
'therm_cns': 'room_heat_demand_prosumer_' + str(building_types.loc[i,'ID_Building']), 'therm_cns': 'room_heat_demand_prosumer_' + str(building_types.loc[i,'ID_Building']),
'dhw_dmd': 'hot_water_demand_prosumer_' + str(building_types.loc[i, 'ID_Building']), 'dhw_dmd': 'hot_water_demand_prosumer_' + str(building_types.loc[i, 'ID_Building']),
'pv_roof': ['pv_factors_aachen_1'], 'pv_roof': ['pv_factors_aachen_1'],
'heat_pump': 'temperature_1'}} 'heat_pump': 'temperature_1'}}
elif 'PV' in building_types.loc[i,'ID_Building']: elif 'PV' in building_types.loc[i,'ID_Building']:
prosumer_dict[building_types.loc[i, 'name_building']] = {'config_path': 'input_files/models/prosumer_models/building_types_aachen/'+ str(building_types.loc[i, 'ID_Building']) + '/config.csv', prosumer_dict[building_types.loc[i, 'name_building']] = {'config_path': 'input_files/models/prosumer_models/building_types_aachen_2022/'+ str(building_types.loc[i, 'ID_Building']) + '/config.csv',
'topology_path': 'input_files/models/prosumer_models/building_types_aachen/'+ str(building_types.loc[i, 'ID_Building']), 'topology_path': 'input_files/models/prosumer_models/building_types_aachen_2022/'+ str(building_types.loc[i, 'ID_Building']),
'profiles': {'elec_cns': 'elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building']), 'profiles': {'elec_cns': 'elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building']),
'therm_cns': 'room_heat_demand_prosumer_' + str(building_types.loc[i,'ID_Building']), 'therm_cns': 'room_heat_demand_prosumer_' + str(building_types.loc[i,'ID_Building']),
'dhw_dmd': 'hot_water_demand_prosumer_' + str(building_types.loc[i, 'ID_Building']), 'dhw_dmd': 'hot_water_demand_prosumer_' + str(building_types.loc[i, 'ID_Building']),
'pv_roof': ['pv_factors_aachen_1']}} 'pv_roof': ['pv_factors_aachen_1']}}
else: else:
prosumer_dict[building_types.loc[i, 'name_building']] = {'config_path': 'input_files/models/prosumer_models/building_types_aachen/'+ str(building_types.loc[i, 'ID_Building']) + '/config.csv', prosumer_dict[building_types.loc[i, 'name_building']] = {'config_path': 'input_files/models/prosumer_models/building_types_aachen_2022/'+ str(building_types.loc[i, 'ID_Building']) + '/config.csv',
'topology_path': 'input_files/models/prosumer_models/building_types_aachen/'+ str(building_types.loc[i, 'ID_Building']), 'topology_path': 'input_files/models/prosumer_models/building_types_aachen_2022/'+ str(building_types.loc[i, 'ID_Building']),
'profiles': {'elec_cns': 'elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building']), 'profiles': {'elec_cns': 'elec_demand_prosumer_' + str(building_types.loc[i, 'ID_Building']),
'therm_cns': 'room_heat_demand_prosumer_' + str(building_types.loc[i,'ID_Building']), 'therm_cns': 'room_heat_demand_prosumer_' + str(building_types.loc[i,'ID_Building']),
'dhw_dmd': 'hot_water_demand_prosumer_' + str(building_types.loc[i, 'ID_Building'])}} 'dhw_dmd': 'hot_water_demand_prosumer_' + str(building_types.loc[i, 'ID_Building'])}}
num=0 num=0
""" """
...@@ -104,7 +163,7 @@ prosumer_dict = {'SCN2_CAT1_PV11_3000_6000':{'config_path': 'input_files/models/ ...@@ -104,7 +163,7 @@ prosumer_dict = {'SCN2_CAT1_PV11_3000_6000':{'config_path': 'input_files/models/
'dhw_dmd': 'demand_hot_water_2'}}} 'dhw_dmd': 'demand_hot_water_2'}}}
""" """
prosumer_main = main_prosumer.ProsumerMain(prosumer_dict, input_profiles, t_horizon, t_step) prosumer_main = main_prosumer.ProsumerMain(prosumer_dict, input_profiles, t_horizon, t_step, new_prosumers=True)
prosumer_sizing_strategy = 'annuity' prosumer_sizing_strategy = 'annuity'
prosumer_main.optimize_sizing(prosumer_sizing_strategy) prosumer_main.optimize_sizing(prosumer_sizing_strategy)
...@@ -119,6 +178,7 @@ if simulation_scope == SimulationScope.PROSUMER: ...@@ -119,6 +178,7 @@ if simulation_scope == SimulationScope.PROSUMER:
district_assets_dict = {'da_bat': {'config_path': 'input_files/models/district_models/example_CA/config.csv', district_assets_dict = {'da_bat': {'config_path': 'input_files/models/district_models/example_CA/config.csv',
'topology_path': 'input_files/models/district_models/example_CA', 'topology_path': 'input_files/models/district_models/example_CA',
'profiles': {}}} 'profiles': {}}}
district_assets_dict = {}
district_assets = main_prosumer.DistrictAssetMain(district_assets_dict, input_profiles, t_horizon, t_step).district_assets district_assets = main_prosumer.DistrictAssetMain(district_assets_dict, input_profiles, t_horizon, t_step).district_assets
......
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