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Fixes/tweaks to RTS-GMLC parser.
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* Zone name can be any string, not just integers
* Don't include startup_cost or p_cost. Include startup_fuel, p_fuel, and non_fuel_startup_cost instead.
* More flexibility in how startup fuel is specified when you have fewer than 3 points. It no longer matters which of the 3 startup fuel columns you leave blank in this case, as long as the provided data is consistent (cold is longer than hot, for example).
* More flexibility in how p_fuel fuel curves are specified. You can have any number of columns (up to 50). For a fuel curve with N valid points, you only have to fill in the first N fuel curve columns and leave the rest blank.  The number of points in the fuel curve can be different for each generator.
* Omit several properties that were in the original RTS-GMLC parser but have no meaning to Egret.
* Some optional properties are now left out of the JSON if the corresponding cells in the csv are left blank
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@darrylmelander
darrylmelander committed May 19, 2021
1 parent 4316c9c commit 17226fa
Showing 1 changed file with 38 additions and 48 deletions.
86 changes: 38 additions & 48 deletions egret/parsers/rts_gmlc/parser.py
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Original file line number Diff line number Diff line change
Expand Up @@ -324,6 +324,7 @@ def _create_rtsgmlc_skeleton(rts_gmlc_dir):
data : dict
Returns a dict loaded from the RTS-GMLC data
"""
from math import isnan

base_dir = rts_gmlc_dir

Expand Down Expand Up @@ -364,7 +365,7 @@ def _create_rtsgmlc_skeleton(rts_gmlc_dir):
"v_min": 0.95,
"v_max": 1.05,
"area": str(row['Area']),
"zone": str(int(row['Zone'])),
"zone": str(row['Zone']),
}

if bus_dict["base_kv"] <= 0:
Expand Down Expand Up @@ -448,6 +449,7 @@ def _create_rtsgmlc_skeleton(rts_gmlc_dir):

name = str(row['UID'])
elements["branch"][name] = branch_dict
branch_df = None

# add the DC branches
if os.path.exists(os.path.join(base_dir,'dc_branch.csv')):
Expand All @@ -466,6 +468,7 @@ def _create_rtsgmlc_skeleton(rts_gmlc_dir):

name = str(row['UID'])
elements["branch"][name] = branch_dict
branch_df = None

# add the generators
elements["generator"] = {}
Expand Down Expand Up @@ -500,6 +503,11 @@ def _create_rtsgmlc_skeleton(rts_gmlc_dir):
"zone": elements['bus'][bus_name]['zone']
}

# Remove optional values if not present
for key in ('p_min', 'p_max', 'q_min', 'q_max', 'ramp_q'):
if isnan(gen_dict[key]):
del gen_dict[key]

UNIT_TYPE = str(row['Unit Type'])
if UNIT_TYPE in RENEWABLE_TYPES:
gen_dict["generator_type"] = "renewable"
Expand Down Expand Up @@ -527,6 +535,8 @@ def valid_output_pcts():
for i in range(50):
try:
val = float(row[f'Output_pct_{i}'])
if isnan(val):
return
yield (i, val)
except:
return
Expand All @@ -543,15 +553,6 @@ def valid_output_pcts():
for i in range(1,fuel_field_count):
f[i] = (((x[i]-x[i-1])*(float(row[f'HR_incr_{i}'])*1000. / 1000000.))) + f[i-1]

fuel_price = float(row['Fuel Price $/MMBTU'])
y = {i: fuel_price*f[i] for i in range(fuel_field_count)}

# only include the cost coeffecients that matter
P_COEFF = [ (x[i], round(y[i],2)) for i in range(fuel_field_count) if (((i == 0) or (x[i-1],y[i-1]) != (x[i], y[i])) and (x[i], y[i]) != (0.,0.)) ]
if P_COEFF == []:
P_COEFF = [(pmax, 0.0)]
gen_dict["p_cost"] = {"data_type": "cost_curve", "cost_curve_type":"piecewise", "values": P_COEFF }

F_COEFF = [ (x[i], round(f[i],2)) for i in range(fuel_field_count) if (((i == 0) or (x[i-1],f[i-1]) != (x[i], f[i])) and (x[i], f[i]) != (0.,0.)) ]
if F_COEFF == []:
F_COEFF = [(pmax, 0.0)]
Expand All @@ -560,66 +561,55 @@ def valid_output_pcts():
# UC Data
MIN_DN_TIME = float(row['Min Down Time Hr'])

# Startup types and costs
COLD_HEAT = float(row['Start Heat Cold MBTU'])
WARM_HEAT = float(row['Start Heat Warm MBTU'])
HOT_HEAT = float(row['Start Heat Hot MBTU'])

COLD_TIME = float(row['Start Time Cold Hr'])
WARM_TIME = float(row['Start Time Warm Hr'])
HOT_TIME = float(row['Start Time Hot Hr'])

FIXED_START_COST = float(row['Non Fuel Start Cost $'])
# Startup types and costs, from hot to cold
startup_heat = (float(row['Start Heat Hot MBTU']),
float(row['Start Heat Warm MBTU']),
float(row['Start Heat Cold MBTU']))
startup_time = (float(row['Start Time Hot Hr']),
float(row['Start Time Warm Hr']),
float(row['Start Time Cold Hr']))

# Arrange fuel requirements from hottest to coldest, ignoring missing values.
startup_fuel = []
for i in range(3):
# Skip blank values
if isnan(startup_time[i]) or isnan(startup_heat[i]):
continue

if (COLD_TIME <= MIN_DN_TIME) or (COLD_TIME == WARM_TIME == HOT_TIME):
STARTUP_COSTS = [(MIN_DN_TIME, round(COLD_HEAT*fuel_price + FIXED_START_COST, 2))]
STARTUP_FUEL = [(MIN_DN_TIME, COLD_HEAT)]
t = max(startup_time[i], MIN_DN_TIME)
f = startup_heat[i]

elif WARM_TIME <= MIN_DN_TIME:
STARTUP_COSTS = [(MIN_DN_TIME, round(WARM_HEAT*fuel_price + FIXED_START_COST, 2)),\
(COLD_TIME, round(COLD_HEAT*fuel_price + FIXED_START_COST, 2))]
STARTUP_FUEL = [(MIN_DN_TIME, WARM_HEAT),\
(COLD_TIME, COLD_HEAT)]
# For entries with matching times, use to the colder data
if len(startup_fuel) > 0 and startup_fuel[-1][0] == t:
startup_fuel[-1] = (t,f)
else:
startup_fuel.append((t,f))

else:
STARTUP_COSTS = [(MIN_DN_TIME, round(HOT_HEAT*fuel_price+FIXED_START_COST,2)),\
(WARM_TIME, round(WARM_HEAT*fuel_price+FIXED_START_COST,2)),\
(COLD_TIME, round(COLD_HEAT*fuel_price+FIXED_START_COST,2))]
STARTUP_FUEL = [(MIN_DN_TIME, HOT_HEAT),\
(WARM_TIME, WARM_HEAT),\
(COLD_TIME, COLD_HEAT)]
gen_dict["startup_cost"] = STARTUP_COSTS
gen_dict["startup_fuel"] = STARTUP_FUEL
gen_dict["startup_fuel"] = startup_fuel
fixed_startup_cost = float(row['Non Fuel Start Cost $'])
if not isnan(fixed_startup_cost):
gen_dict["non_fuel_startup_cost"] = fixed_startup_cost
gen_dict["shutdown_cost"] = 0.0

gen_dict["pc1"] = 0.0
gen_dict["pc2"] = 0.0
gen_dict["qc1_min"] = 0.0
gen_dict["qc1_max"] = 0.0
gen_dict["qc2_min"] = 0.0
gen_dict["qc2_max"] = 0.0
gen_dict["agc_capable"] = True
gen_dict["p_min_agc"] = gen_dict["p_min"]
gen_dict["p_max_agc"] = gen_dict["p_max"]

ramp_q = gen_dict['ramp_q']
gen_dict["ramp_agc"] = ramp_q
gen_dict["ramp_10"] = 10.*ramp_q
gen_dict["ramp_30"] = 30.*ramp_q
gen_dict["ramp_up_60min"] = 60.*ramp_q
gen_dict["ramp_down_60min"] = 60.*ramp_q

gen_dict["power_factor"] = 0.0
gen_dict["fuel_cost"] = fuel_price
gen_dict["fuel_cost"] = float(row['Fuel Price $/MMBTU'])

# these assumptions are the same as prescient-rtsgmlc
gen_dict["startup_capacity"] = gen_dict['p_min']
gen_dict["shutdown_capacity"] = gen_dict['p_min']
gen_dict["min_up_time"] = float(row['Min Up Time Hr'])
gen_dict["min_down_time"] = MIN_DN_TIME
gen_dict["must_run"] = False

elements["generator"][name] = gen_dict
gen_df = None

# Add the reserves
reserve_df = pd.read_csv(os.path.join(base_dir,'reserves.csv'))
Expand Down

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