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Debugging solar api for missing panel config
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parent
01c688da23
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1 changed files with 19 additions and 1 deletions
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@ -309,7 +309,7 @@ class GoogleSolarApi:
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}
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}
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)
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)
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panel_performance = pd.DataFrame(panel_performance)
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panel_performance = pd.DataFrame([panel_performance])
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if panel_performance.empty:
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if panel_performance.empty:
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self.panel_performance = pd.DataFrame(
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self.panel_performance = pd.DataFrame(
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@ -329,12 +329,30 @@ class GoogleSolarApi:
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return
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return
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# We can have duplicate configurations
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# We can have duplicate configurations
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panel_performance = panel_performance.drop_duplicates()
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panel_performance = panel_performance.drop_duplicates()
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# If we look at the building level, we don't include any projects fewer than 10 panels, otherwise the
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# If we look at the building level, we don't include any projects fewer than 10 panels, otherwise the
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# minimum is 4
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# minimum is 4
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min_panels = 10 if is_building else 4
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min_panels = 10 if is_building else 4
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panel_performance = panel_performance[panel_performance["n_panels"] >= min_panels]
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panel_performance = panel_performance[panel_performance["n_panels"] >= min_panels]
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if panel_performance.empty:
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self.panel_performance = pd.DataFrame(
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columns=[
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"n_panels",
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"yearly_dc_energy",
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"total_cost",
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"panneled_roof_area",
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"array_wattage",
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"initial_ac_kwh_per_year",
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"lifetime_ac_kwh",
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"roi",
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"expected_payback_years",
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"lifetime_dc_kwh"
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]
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)
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return
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panel_performance["initial_ac_kwh_per_year"] = panel_performance["yearly_dc_energy"] * self.dc_to_ac_rate
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panel_performance["initial_ac_kwh_per_year"] = panel_performance["yearly_dc_energy"] * self.dc_to_ac_rate
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# Remove anything where the total ac energy is less than half of the array wattage
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# Remove anything where the total ac energy is less than half of the array wattage
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