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input_Parse.py
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input_Parse.py
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""" Simple MATPOWER format parser
"""
import logging
import re
import numpy as np
# import numpy.random.common
# import numpy.random.bounded_integers
# import numpy.random.entropy
import market_obj as MO
def read_structure(market, file):
"""Read a MATPOWER data file and build market elements"""
func = re.compile(r'function\s')
mva = re.compile(r'\s*mpc.baseMVA\s*=\s*')
bus = re.compile(r'\s*mpc.bus\s*=\s*\[?')
gen = re.compile(r'\s*mpc.gen\s*=\s*\[')
branch = re.compile(r'\s*mpc.branch\s*=\s*\[')
area = re.compile(r'\s*mpc.areas\s*=\s*\[')
gencost = re.compile(r'\s*mpc.gencost\s*=\s*\[')
bus_name = re.compile(r'\s*mpc.bus_name\s*=\s*{')
coordinates = re.compile(r'\s*mpc.coordinates\s*=\s*\[')
end = re.compile(r'\s*\];?')
has_digit = re.compile(r'.*\d+\s*]?;?')
ret = True
field = None
info = True
base_mva = 100
mpc = {
'bus': [],
'gen': [],
'branch': [],
'area': [],
'gencost': [],
'bus_name': [],
'coordinates': [],
}
fid = open(file, 'r')
for line in fid:
line = line.strip().rstrip(';')
if not line:
continue
elif func.search(line): # skip function declaration
continue
elif len(line.split('%')[0]) == 0:
if info is True:
info = False
else:
continue
elif mva.search(line):
base_mva = float(line.split('=')[1])
if not field:
if bus.search(line):
field = 'bus'
elif gen.search(line):
field = 'gen'
elif branch.search(line):
field = 'branch'
elif area.search(line):
field = 'area'
elif gencost.search(line):
field = 'gencost'
elif bus_name.search(line):
field = 'bus_name'
elif coordinates.search(line):
field = 'coordinates'
else:
continue
elif end.search(line):
field = None
continue
# parse mpc sections
if field:
if line.find('=') >= 0:
line = line.split('=')[1]
if line.find('[') >= 0:
line = re.sub(r'\[', '', line)
elif line.find('{') >= 0:
line = re.sub(r'{', '', line)
if line.find('\'') >= 0: # bus_name
line = line.split(';')
data = [i.strip('\'').strip() for i in line]
mpc['bus_name'].extend(data)
else:
if not has_digit.search(line):
continue
line = line.split('%')[0].strip()
line = line.split(';')
for item in line:
if not has_digit.search(item):
continue
try:
data = np.array([float(val) for val in item.split()])
except Exception as e:
raise e
mpc[field].append(data)
fid.close()
# convert mpc to np array
mpc_array = dict()
for key, val in mpc.items():
mpc_array[key] = np.array(val)
# list of buses with slack gen
sw = []
for data in mpc['bus_name']:
market_type = market.Type
Bus = MO.Bus(market_type)
Bus.name = data
market.bus.append(Bus)
bus_idx = 0
for data in mpc['coordinates']:
market.bus[bus_idx].latitude = data[0]
market.bus[bus_idx].longitude = data[1]
bus_idx += 1
bus_idx = 0
for data in mpc['bus']:
# idx ty pd qd gs bs area vmag vang baseKV zone vmax vmin
# 0 1 2 3 4 5 6 7 8 9 10 11 12
market_type = market.Type
load = MO.Load(market_type)
load.P = data[2]
bus_idx += 1
if data[1] == 3:
market.sw = data[0]
market.load.append(load)
market.Nb = int(bus_idx)
gen_idx = 0
for data in mpc['gen']:
# bus pg qg qmax qmin vg mbase status pmax pmin pc1 pc2
# 0 1 2 3 4 5 6 7 8 9 10 11
# qc1min qc1max qc2min qc2max ramp_agc ramp_10 ramp_30 ramp_q
# 12 13 14 15 16 17 18 19
# apf
# 20
gen_idx += 1
market_type = market.Type
gen = MO.Genco(market_type)
gen.bus = int(data[0])
gen.status = int(data[7])
gen.pmax = data[8]
gen.pmin = data[9]
gen.ramp_up = data[18]*2
gen.ramp_down = data[18] * 2
market.genco.append(gen)
market.Ng = int(gen_idx)
gen_idx = 0
for data in mpc['gencost']:
# idx startup shutdown ~ a b c
if data[3] == 2:
# linear
market.genco[gen_idx].bid_type = 2
market.genco[gen_idx].bids = data[4]
elif data[3] == 3:
# quadratic
market.genco[gen_idx].bid_type = 3
market.genco[gen_idx].bids = [data[4], data[5], data[6],]
market.genco[gen_idx].start_up = data[1]
market.genco[gen_idx].shut_down = data[2]
gen_idx += 1
line_idx = 0
for data in mpc['branch']:
# fbus tbus r x b rateA rateB rateC ratio angle
# 0 1 2 3 4 5 6 7 8 9
# status angmin angmax Pf Qf Pt Qt
# 10 11 12 13 14 15 16
market_type = market.Type
line = MO.Line(market_type)
line.fbus = int(data[0])
line.tbus = int(data[1])
line.r = data[2]
line.x = data[3]
line.b = data[4]
if data[5] == 0:
line.rating = 1000000000
else:
line.rating = data[5]
line.status = data[10]
market.Line.append(line)
line_idx += 1
market.Nl = line_idx
return ret
def read_load(market, file):
fid = open(file, 'r')
Read_Type = re.compile(r'\s*Type\s*=\s*')
Read_load_level = re.compile(r'\s*Load_level\s*=\s*')
Read_factor= re.compile(r'\s*Factor\s*=\s*')
Read_load = re.compile(r'\s*Load\s*=\s*')
Title = " "
for line in fid:
line = line.strip().rstrip(';')
if Read_Type.search(line):
Type = int(line.split('=')[1])
fid.close()
load = []
load_level = []
factor = []
if Type == 1:
fid = open(file, 'r')
for line in fid:
if Read_load.search(line):
Title = "Load"
continue
if line.find(']') >= 0:
Title = " "
elif Title == "Load":
load_txt = line.split()
load_float = [float(load_txt[i]) for i in range(load_txt.__len__())]
load.append(load_float)
N_T = load[0].__len__()
for idx, ld in enumerate(market.load):
ld.T_P = load[idx]
for i in range(N_T):
load_level.append(sum([load[x][i] for x in range(market.load.__len__())]))
market.N_T = N_T
market.load_level = load_level
if Type == 2:
fid = open(file, 'r')
for line in fid:
line = line.strip().rstrip(';')
if line == "" or line == "\n":
continue
if Read_load_level.search(line):
Title = "Load level"
continue
if Read_factor.search(line):
Title = "Factor"
continue
# Switch "Title" case ....
if line.find(']') >= 0:
Title = " "
elif Title == "Load level":
load_level.append(float(line))
elif Title == "Factor":
factor.append(float(line))
# Read the load profile into market objective
N_T = load_level.__len__()
for idx, ld in enumerate(market.load):
par_fac = factor[idx]/sum(factor)
ld.T_P = [load_level[i]*par_fac for i in range(N_T)]
market.N_T = N_T
market.load_level = load_level
def read_xgd(market, file):
fid = open(file, 'r')
Read_factor= re.compile(r'\s*xgd_table.data\s*=\s*')
CommitKey = []
MinUp = []
MinDown = []
Title = " "
for line in fid:
line = line.strip().rstrip(';')
if line == "" or line == "\n":
continue
if Read_factor.search(line):
Title = "xgd_table.data"
continue
# Switch "Title" case ....
if line.find(']') >= 0:
Title = " "
if Title == "xgd_table.data":
line = line.split(' ')
line = [x for x in line if x]
CommitKey.append(int(line[0]))
MinUp.append(int(line[2]))
MinDown.append(int(line[3]))
# Read the load profile into market objective
for idx, gen in enumerate(market.genco):
gen.commit_key = CommitKey[idx]
gen.min_dowm = MinDown[idx]
gen.min_up = MinUp[idx]