Update time_reduction.py
So that representative point can be printed.
@@ -325,6 +325,7 @@ def kmeans_time_clustering(
pass
resource_df = resource_df.fillna(value=1)
+
# load_df["Sub_Weights"] = np.nan
# load_df.loc[: len(EachClusterWeight) - 1, "Sub_Weights"] = (
# np.array(EachClusterWeight) * NumGrpDays * 24
@@ -336,7 +337,7 @@ def kmeans_time_clustering(
# renewable_df = renewable_df.drop(columns=["GrpWeight"])
# renewable_df.insert(loc=0, column="Resource", value=renewable_df.index + 1)
# renewable_df.to_csv("renewables_time_reduced.csv", index=False)
-
+ EachClusterRepPoint = pd.DataFrame(EachClusterRepPoint, columns=['slot'])
return (
{
"load_profiles": load_df, # Scaled Output Load and Renewables profiles for the sampled representative groupings
