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hca.py
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# -*- coding: utf-8 -*-
"""
Created on Sat Oct 22 20:54:02 2022
@author: wwang2
"""
import pandas as pd
import random
import os
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import opendssdirect as dss
from opendssdirect.utils import run_command
## read partition regions of the feeder
PATH = Path(os.getcwd())
r0 = pd.read_csv(PATH/'partition'/'low_income_0.csv')
r1 = pd.read_csv(PATH/'partition'/'low_income_1.csv')
r2 = pd.read_csv(PATH/'partition'/'low_income_2.csv')
load_r0 = set(r0[r0['type']=='Load']['name'])
load_r1 = set(r1[r1['type']=='Load']['name'])
load_r2 = set(r2[r2['type']=='Load']['name'])
load_region = [load_r0, load_r1, load_r2]
fname = PATH/'p30uhs8_1247--p30udt9870'/'Master.dss'
run_command('compile '+fname)
dss.Vsources.PU(1.0)
run_command('solve')
if dss.Text.Result() == '':
print('----- Success for the test run ----')
else:
print('---- Opendss failed ------')
print(dss.Text.Result())
summary = dss.run_command('summary')
print(summary)
v = dss.Circuit.AllBusMagPu()
vname = dss.Circuit.AllNodeNames()
df_v = pd.DataFrame.from_dict(dict(zip(vname,v)),orient='index')
df_v = df_v[df_v[0]>=0.1]
print('==== max voltage ====')
print(df_v.idxmax().item(), df_v.max())
print('==== min voltage ====')
print(df_v.idxmin().item(), df_v.min())
I = dss.PDElements.AllPctNorm()
Iname = dss.PDElements.AllNames()
df_I = pd.DataFrame.from_dict(dict(zip(Iname,I)),orient='index')
df_I['element'] = df_I.index.str.split('.',expand=True)
df_I_line = df_I[df_I['element'].str[0]=='Line']
df_I_line = df_I_line.drop(columns = ['element'])
print('==== max current percentage ====')
print(df_I_line.idxmax().item(), df_I_line.max())
print('==== min current percentage ====')
print(df_I_line.idxmin().item(), df_I_line.min())
df_I_line_sort = df_I_line[0].sort_values(ascending=False)
df_I_line_sort_ab100 = df_I_line_sort[df_I_line_sort>=100]
print('==== above 100% ====')
print(df_I_line_sort_ab100.index)
########## get load ###########
load_df = dss.utils.loads_to_dataframe()
load_df = load_df[load_df.index.str.contains("mv")==False]
load_name = load_df['Name']
region_zone = []
for ln in load_df.index:
if ln.split('_')[0] + '_' + ln.split('_')[1] in list(load_r0):
region_zone.append(0)
elif ln.split('_')[0] + '_' + ln.split('_')[1] in list(load_r1):
region_zone.append(1)
else:
region_zone.append(2)
load_df['zone'] = region_zone
total_list = True
snapshot_count = 0
snapshot_count_list = []
v_min_list = []
v_max_list = []
pen_level_list = []
mc_count = []
zone_list = []
zone = 0
if total_list == True:
for i in range(0,10):
print(f"=== Working on scenario {i} ===")
run_command('compile '+fname)
#run_command('Edit Vsource.vsource pu=1.0')
dss.Vsources.PU(1.0)
run_command('solve')
load_list = list(load_df.index)
# drop mv load
#load_list = [x for x in load_list_orig if "mv" not in x]
add_pv_total = []
pen_level = 0
for pen_level_target in range(5,105,5):
print(f" ==== working on pen_level_target={pen_level_target}% ==== " )
txt = ''
while pen_level < pen_level_target and len(load_list)!=0 :
# choose load from region
#print(load_list[:3])
load_select = random.choice(load_list) # load select location for PV generator
# now define new PV
kv = run_command(f"? load.{load_select}.kV")
bus1 = run_command(f"? load.{load_select}.bus1")
conn = run_command(f"? load.{load_select}.conn")
kw = float(run_command(f"? load.{load_select}.kw"))
txt = txt + f"new generator.pv_{load_select} conn={conn} bus1={bus1} kv={kv} kw={kw} model=1 Phases=1 \n"
run_command(f"new generator.pv_{load_select} conn={conn} bus1={bus1} kv={kv} kw={kw} model=1 Phases=1 kvar=0")
load_list.remove(load_select)
add_pv_total.append(kw)
pen_level = 100*sum(add_pv_total)/load_df['kW'].sum()
run_command("solve")
snapshot_count +=1
v = dss.Circuit.AllBusMagPu()
vname = dss.Circuit.AllNodeNames()
df_v = pd.DataFrame.from_dict(dict(zip(vname,v)),orient='index')
df_v = df_v[df_v[0]>=0.1]
v_min_list.append(float(df_v.min()))
v_max_list.append(float(df_v.max()))
if float(df_v.max()) <=1.05:
print(float(df_v.max()))
else:
pass
pen_level_list.append(pen_level_target)
mc_count.append(i)
#zone_list.append(zone)
snapshot_count_list.append(snapshot_count)
else:
for zone in range(0,3):
print(f"=== Working on zone {zone} ===")
for i in range(0,10):
print(f"=== Working on scenario {i} ===")
run_command('compile '+fname)
#run_command('Edit Vsource.vsource pu=1.0')
dss.Vsources.PU(1.0)
run_command('solve')
load_list = list(load_df[load_df['zone']==zone].index)
if total_list == True:
load_list = list(load_df.index)
# drop mv load
#load_list = [x for x in load_list_orig if "mv" not in x]
add_pv_total = []
pen_level = 0
for pen_level_target in range(5,105,5):
print(f" ==== working on pen_level_target={pen_level_target}% ==== " )
txt = ''
while pen_level < pen_level_target and len(load_list)!=0 :
# choose load from region
#print(load_list[:3])
load_select = random.choice(load_list) # load select location for PV generator
# now define new PV
kv = run_command(f"? load.{load_select}.kV")
bus1 = run_command(f"? load.{load_select}.bus1")
conn = run_command(f"? load.{load_select}.conn")
kw = float(run_command(f"? load.{load_select}.kw"))
txt = txt + f"new generator.pv_{load_select} conn={conn} bus1={bus1} kv={kv} kw={kw} model=1 Phases=1 \n"
run_command(f"new generator.pv_{load_select} conn={conn} bus1={bus1} kv={kv} kw={kw} model=1 Phases=1 kvar=0")
load_list.remove(load_select)
add_pv_total.append(kw)
pen_level = 100*sum(add_pv_total)/load_df[load_df['zone']==zone]['kW'].sum()
run_command("solve")
snapshot_count +=1
v = dss.Circuit.AllBusMagPu()
vname = dss.Circuit.AllNodeNames()
df_v = pd.DataFrame.from_dict(dict(zip(vname,v)),orient='index')
df_v = df_v[df_v[0]>=0.1]
v_min_list.append(float(df_v.min()))
v_max_list.append(float(df_v.max()))
if float(df_v.max()) <=1.05:
print(float(df_v.max()))
else:
pass
pen_level_list.append(pen_level_target)
mc_count.append(i)
zone_list.append(zone)
snapshot_count_list.append(snapshot_count)
########## now save dataframe to results ##########
results_df = pd.DataFrame()
results_df['snapshot_count'] = snapshot_count_list
results_df['v_min'] = v_min_list
results_df['v_max'] = v_max_list
results_df['pen_level'] = pen_level_list
results_df['scenario'] = mc_count
if total_list != True:
results_df['zone'] = zone_list
print(f" ---- Simulation is done! high five! save to results_df {PATH}")
results_df.to_csv(PATH/'results_df.csv')
###################################################