openego /
eGon-data
| @@ 2185-2222 (lines=38) @@ | ||
| 2182 | return buildings_gdf |
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| 2183 | ||
| 2184 | ||
| 2185 | def infer_voltage_level( |
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| 2186 | units_gdf: gpd.GeoDataFrame, |
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| 2187 | ) -> gpd.GeoDataFrame: |
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| 2188 | """ |
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| 2189 | Infer nan values in voltage level derived from generator capacity to |
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| 2190 | the power plants. |
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| 2191 | ||
| 2192 | Parameters |
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| 2193 | ----------- |
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| 2194 | units_gdf : geopandas.GeoDataFrame |
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| 2195 | GeoDataFrame containing units with voltage levels from MaStR |
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| 2196 | Returnsunits_gdf: gpd.GeoDataFrame |
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| 2197 | ------- |
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| 2198 | geopandas.GeoDataFrame |
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| 2199 | GeoDataFrame containing units all having assigned a voltage level. |
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| 2200 | """ |
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| 2201 | ||
| 2202 | def voltage_levels(p: float) -> int: |
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| 2203 | if p <= 100: |
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| 2204 | return 7 |
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| 2205 | elif p <= 200: |
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| 2206 | return 6 |
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| 2207 | elif p <= 5500: |
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| 2208 | return 5 |
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| 2209 | elif p <= 20000: |
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| 2210 | return 4 |
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| 2211 | elif p <= 120000: |
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| 2212 | return 3 |
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| 2213 | return 1 |
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| 2214 | ||
| 2215 | units_gdf["voltage_level_inferred"] = False |
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| 2216 | mask = units_gdf.voltage_level.isna() |
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| 2217 | units_gdf.loc[mask, "voltage_level_inferred"] = True |
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| 2218 | units_gdf.loc[mask, "voltage_level"] = units_gdf.loc[ |
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| 2219 | mask |
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| 2220 | ].Nettonennleistung.apply(voltage_levels) |
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| 2221 | ||
| 2222 | return units_gdf |
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| 2223 | ||
| 2224 | ||
| 2225 | def pv_rooftop_to_buildings(): |
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| @@ 117-154 (lines=38) @@ | ||
| 114 | return standort, found |
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| 115 | ||
| 116 | ||
| 117 | def infer_voltage_level( |
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| 118 | units_gdf: gpd.GeoDataFrame, |
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| 119 | ) -> gpd.GeoDataFrame: |
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| 120 | """ |
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| 121 | Infer nan values in voltage level derived from generator capacity to |
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| 122 | the power plants. |
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| 123 | ||
| 124 | Parameters |
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| 125 | ----------- |
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| 126 | units_gdf : geopandas.GeoDataFrame |
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| 127 | GeoDataFrame containing units with voltage levels from MaStR |
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| 128 | Returnsunits_gdf: gpd.GeoDataFrame |
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| 129 | ------- |
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| 130 | geopandas.GeoDataFrame |
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| 131 | GeoDataFrame containing units all having assigned a voltage level. |
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| 132 | """ |
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| 133 | ||
| 134 | def voltage_levels(p: float) -> int: |
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| 135 | if p <= 100: |
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| 136 | return 7 |
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| 137 | elif p <= 200: |
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| 138 | return 6 |
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| 139 | elif p <= 5500: |
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| 140 | return 5 |
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| 141 | elif p <= 20000: |
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| 142 | return 4 |
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| 143 | elif p <= 120000: |
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| 144 | return 3 |
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| 145 | return 1 |
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| 146 | ||
| 147 | units_gdf["voltage_level_inferred"] = False |
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| 148 | mask = units_gdf.voltage_level.isna() |
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| 149 | units_gdf.loc[mask, "voltage_level_inferred"] = True |
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| 150 | units_gdf.loc[mask, "voltage_level"] = units_gdf.loc[ |
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| 151 | mask |
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| 152 | ].Nettonennleistung.apply(voltage_levels) |
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| 153 | ||
| 154 | return units_gdf |
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| 155 | ||
| 156 | ||
| 157 | def import_mastr() -> None: |
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