def run(self,
Testsys=case24_ieee_rts(),
BETAlimit=0.0017,
ITER_max=10000,
SIMUNIT=1000):
Nb = Testsys["bus"].shape[0] # Load test system，Nb为节点数，Ng为发电机组数，Nl为馈线数
Ng = Testsys["gen"].shape[0]
Nl = Testsys["branch"].shape[0]
# Set initial value
iter = 0
betavalue = float('inf') # The stopping criteria停止迭代的标准
row_index = 0
# Build matrices that have fix dimension to avoid changing size in each loop
eqstatus_total = np.zeros(
(ITER_max, Ng + Nl + 3)) # 建一个100000*（33+38+3）的矩阵
beta_table = np.zeros((1, ITER_max // SIMUNIT)) # "//"除法得到的才是整数
edns_table = np.zeros((1, ITER_max // SIMUNIT)) # 存放评价指标，大小为1*1000
lole_table = np.zeros((1, ITER_max // SIMUNIT))
plc_table = np.zeros((1, ITER_max // SIMUNIT))
genbus = np.nonzero((Testsys["bus"][:, PD]))[
0] # 第三列（python中坐标是2）是节点的有功功率，表示节点有有功负荷,此处返回该列非零元素的索引，共有17个元素非零
sizegenbus = genbus.shape[0] # 有负荷的节点数量赋值给sizegenbus
Testsys["load"] = sum(Testsys["bus"][:, PD]) # 系统需要的总有功功率
Testsys["gencost"] = np.tile([2, 0, 0, 3, 0, 0, 0],
(Ng, 1)) # np.tile建立重复矩阵块（设置机组费用）
# treat all load as negtive generator and set their parameters, then add these vitual generators to real gens
# 将所有载荷视为负发电机，并设置其参数，然后将这些发电机加到实际的发电机中
loadcost = np.tile([2, 0, 0, 3, 0, 1, 0],
(sizegenbus, 1)) # np.tile建立重复矩阵块（负荷的“机组费用”）
Testsys["gencost"] = np.append(Testsys["gencost"], loadcost, axis=0)
Index = copy.deepcopy(Testsys["gen"][0:sizegenbus, :]) # 将前17台机组的数据取出
Index[:, 0:10] = np.hstack(
(Testsys["bus"][genbus, 0].reshape(-1, 1),
-Testsys["bus"][genbus, 2].reshape(-1, 1),
-Testsys["bus"][genbus, 3].reshape(-1, 1),
np.zeros(
(sizegenbus, 1)), -Testsys["bus"][genbus, 3].reshape(-1, 1),
np.zeros((sizegenbus, 1)), Testsys["baseMVA"] * np.ones(
(sizegenbus, 1)), np.ones((sizegenbus, 1)),
np.zeros(
(sizegenbus, 1)), -Testsys["bus"][genbus, 2].reshape(-1, 1)))
# 负荷参数代替取出的机组数据，将负荷套入机组模型,上面矩阵取数注意与matlab相比坐标要减一
Testsys["gen"] = np.append(Testsys["gen"], Index, axis=0)
del Index
Testsys["bus"][genbus, 2:4] = 0 # 将原来节点中的第3、4列（有功、无功）负荷设为零
totalprob = failprob() # 引用前面定义的函数
ppopt = ppoption(
PF_DC=1, VERBOSE=0, OUT_ALL=0, OPF_ALG_DC=200, OPF_FLOW_LIM=1
) # 可以通过ppoption()采用默认变量来看里面需要什么样的输入，这个按照matlab来输入没问题吧？
result = runopf(casedata=Testsys, ppopt=ppopt)
while (betavalue > BETAlimit) & (iter < ITER_max):
eqstatus_indi = mc_sampling(
totalprob, SIMUNIT, Ng,
Nl) # eqstatus为元件的状态矩阵，为1表示元件故障，为0表示原件正常
eqstatus_indi = np.hstack(
(eqstatus_indi, np.ones((eqstatus_indi.shape[0], 1)),
np.zeros((eqstatus_indi.shape[0], 2))))
# 在eqstatus_indi矩阵中加入三列，第一列代表状态重复次数，第二列记载切负荷量大小（没有切负荷则为零），第三列记载是否为容量不足
eqstatus_indi, ia1 = np.unique(eqstatus_indi,
axis=0,
return_inverse=True) # 找出抽样中的相同结果
for i in range(eqstatus_indi.shape[0]):
eqstatus_indi[i,
Ng + Nl] = sum(ia1 == i) # 将重复记录次数在第Ng + Nl + 1
if iter:
x = 0
y = eqstatus_indi.shape[0]
for i in range(y):
indi_x = eqstatus_indi[x, 0:Ng + Nl]
for j in range(row_index):
if (indi_x == eqstatus_total[j, 0:Ng + Nl]).all():
eqstatus_total[j, Ng + Nl] = eqstatus_total[
j, Ng + Nl] + eqstatus_indi[
x,
Ng + Nl] # 遇见相同的，就在eqstatus_total的计数中累加次数
eqstatus_indi = np.delete(eqstatus_indi, x, axis=0)
x = x - 1
break
x = x + 1
parfortemp = np.zeros((eqstatus_indi.shape[0], 2))
para = [0] * eqstatus_indi.shape[0]
n_sample = [0] * eqstatus_indi.shape[0]
for i in range(eqstatus_indi.shape[0]):
para[i] = [0] * 5
para[i][0] = eqstatus_indi[i, 0:Ng + Nl]
para[i][1] = Testsys
para[i][2] = ppopt
para[i][3] = Ng
para[i][4] = Nl
with Pool(self.n_processors) as p:
load_shedding = list(p.map(mc_simulation, para))
parfortemp[:, 0] = np.asarray(load_shedding)
parfortemp[:, 1] = (parfortemp[:, 0]) != 0
eqstatus_indi[:, Ng + Nl + 1:Ng + Nl + 3] = parfortemp
eqstatus_total[row_index:row_index +
eqstatus_indi.shape[0], :] = eqstatus_indi
row_index = row_index + eqstatus_indi.shape[0]
else:
parfortemp = np.zeros((eqstatus_indi.shape[0], 2))
para = [0] * eqstatus_indi.shape[0]
c = [0] * eqstatus_indi.shape[0]
for i in range(eqstatus_indi.shape[0]):
para[i] = [0] * 5
para[i][0] = eqstatus_indi[i, 0:Ng + Nl]
para[i][1] = Testsys
para[i][2] = ppopt
para[i][3] = Ng
para[i][4] = Nl
with Pool(self.n_processors) as p:
load_shedding = list(p.map(mc_simulation, para)) # 计算负荷短缺值
parfortemp[:, 0] = np.asarray(load_shedding)
parfortemp[:, 1] = (parfortemp[:, 0]) != 0 # 记录是否负荷短缺
eqstatus_indi[:, Ng + Nl + 1:Ng + Nl + 3] = parfortemp
eqstatus_total[row_index:row_index +
eqstatus_indi.shape[0], :] = eqstatus_indi
row_index = row_index + eqstatus_indi.shape[0]
## Update index
edns = sum(
eqstatus_total[0:row_index, Ng + Nl] *
eqstatus_total[0:row_index, Ng + Nl + 1]) / (iter + SIMUNIT)
lole = sum(eqstatus_total[0:row_index, Ng + Nl] *
eqstatus_total[0:row_index, Ng + Nl + 2]) / (
iter + SIMUNIT) * 8760
plc = sum(
eqstatus_total[0:row_index, Ng + Nl] *
eqstatus_total[0:row_index, Ng + Nl + 2]) / (iter + SIMUNIT)
betavalue = (sum(eqstatus_total[0:row_index, Ng + Nl] *
(eqstatus_total[0:row_index, Ng + Nl + 1] - edns)
**2))**0.5 / (iter + SIMUNIT) / edns
beta_table[0, ((iter + SIMUNIT) // SIMUNIT) - 1] = betavalue
edns_table[0, ((iter + SIMUNIT) // SIMUNIT) - 1] = edns
lole_table[0, ((iter + SIMUNIT) // SIMUNIT) - 1] = lole
plc_table[0, ((iter + SIMUNIT) // SIMUNIT) - 1] = plc
iter = iter + SIMUNIT
return edns
def save_recovery_result():
G0 = case24_ieee_rts()
G1 = case39()
G2 = case57()
G3 = case118()
G4 = Power_Graph.case_preprocess(case300())
G = G2
round = 5
delete_num = 15
ramp_rate = 0.3
seq_len = 5
path = 'exhaustive/case' + str(len(G['bus']))
if os.path.exists(path) == False:
os.mkdir(path)
file_name = path + '/case' + str(len(G['bus'])) + '_exh2' + '.txt'
new_file = open(file_name, 'w')
new_file.write('ramp_rate = ' + str(ramp_rate) + '\n')
new_file.write('length of recovery seq ' + str(seq_len) + '\n')
g = Power_Graph()
g.init_by_case(G)
g.set_ramp_rate(ramp_rate)
delete_list = []
while len(delete_list) != delete_num:
ran_num = random.randint(1, len(G['bus']))
if ran_num not in delete_list:
delete_list.append(ran_num)
#delete_list = [66, 289, 298, 255, 72, 87, 263, 290, 83, 167, 241, 13, 225, 243, 232, 34, 147, 269, 132, 249, 122, 2, 37, 127, 94, 199, 202, 76, 156, 67, 131, 248, 188, 238, 15, 84, 44, 8, 220, 189, 206, 162, 169, 107, 17, 282, 164, 198, 115, 261]
#delete_list = [44, 54, 11, 3, 6, 28, 2, 15, 30, 9]
new_file.write('delete length ' + str(len(delete_list)) + '\n')
new_file.write('delete list ' + str(delete_list) + '\n')
for item in delete_list:
g.delete_bus(item)
cf = Power_Failure(g)
for item in delete_list:
cf.failed_bus_id.append(item)
cf.failure_process()
new_file.write('num of failed bus ' + str(len(cf.failed_bus_id)) + '\n')
new_file.write('failed bus ' + str(cf.failed_bus_id) + '\n')
steady_bus_num = 0
steady_branch_num = 0
for graph in cf.steady_list:
steady_bus_num += len(graph.bus_id)
steady_branch_num += len(graph.branch)
new_file.write('num of steady bus ' + str(steady_bus_num) + '\n')
new_file.write('num of steady branch ' + str(steady_branch_num) + '\n\n')
ini_g = Power_Graph()
ini_g.init_by_case(G)
gr = Grid_Recovery(cf.steady_list, ini_g)
candidate_num = len(gr.connect_bus_list(cf.steady_list))
new_file.write('num of failed bus which can be recovered ' +
str(candidate_num) + '\n')
ini_residual_per = gr.cal_residual_power()
new_file.write('residual power before recovery ' + str(ini_residual_per) +
'\n\n')
R_srg = Recovery_SAG.Recovery_SAG(cf.steady_list, ini_g)
R_srg.initialize_param(44, 16, round)
candidate_P_set = R_srg.cal_candidate_set()
sorted_list = sorted(candidate_P_set.items(),
key=lambda item: item[1],
reverse=True)
new_file.write('candidate P set ' + '\n')
for item in sorted_list:
new_file.write(str(item[0]) + ' ' + str(item[1]) + '\n')
new_file.write('\n')
R_ex = Recovery_exhaustive(cf.steady_list, ini_g)
for num in range(1, seq_len + 1):
seq_dic = R_ex.recovery_exhaustive(num)
sorted_list = sorted(seq_dic.items(),
key=lambda item: item[1],
reverse=True)
new_file.write('exhaustive search recovery sequence length: ' +
str(num) + '\n')
for item in sorted_list:
new_file.write(str(item[0]) + ' ' + str(item[1]) + '\n')
new_file.write('\n')
new_file.close()
seq.append(item)
if len(seq) == num:
break
print 'random based recovery seq', seq
return self.recover_with_sequence(seq), seq
if __name__ == '__main__':
G = case24_ieee_rts()
#G = case118()
g = Power_Graph()
g.init_by_case(G)
g.set_ramp_rate(0.3)
g.draw_P_graph()
print 'draw initial graph'
#g.delete_branch(24, 70)
g.delete_branch(2, 4)
cf = Power_Failure(g)
cf.failure_process()
for graph in cf.steady_list:
print 'steady graph', graph.bus_id
cf.draw_graph()
print 'draw steady graph before recovery'
def test_case24():
net = from_ppc(c24.case24_ieee_rts())
pp.runopp(net)
assert net.OPF_converged
def mc_simulation(eqstatus, Testsys, ppopt, Ng, Nl):
statusgen = eqstatus[0:Ng]
Testsys["gen"][0:Ng, 8] = 1 - statusgen
statusbranch = eqstatus[Ng:Ng + Nl]
Testsys["branch"][0:Nl, 10] = 1 - statusbranch
Result = runopf(casedata=Testsys, ppopt=ppopt)
dns = Result["f"] + Testsys["load"]
if dns < 0.1:
dns = 0
return dns
Testsys = case24_ieee_rts()
# Load test system，Nb为节点数，Ng为发电机组数，Nl为馈线数
Nb = Testsys["bus"].shape[0]
Ng = Testsys["gen"].shape[0]
Nl = Testsys["branch"].shape[0]
# Set initial value
BETAlimit = 0.0017
ITER_max = 100000
SIMUNIT = 100
iter = 0
lole = 0
edns = 0
betavalue = float('inf')
row_index = 0
# Build matrices that have fix dimension to avoid changing size in each loop
eqstatus_total = np.zeros((ITER_max, Ng + Nl + 3))
def save_recovery_result_2():
G0 = case24_ieee_rts()
G1 = case39()
G2 = case57()
G3 = case118()
G4 = Power_Graph.case_preprocess(case300())
G_list = [G0, G1, G2, G3, G4]
G = G4
P = 30
R = 16
round = 9
delete_num = 15
#iter_times = 11
ramp_rate = 0.3
seq_len = 9
random_rep_num = 50
ramp_arr = np.arange(0.1, 1.1, 0.1)
P_arr = np.arange(10, 32, 2)
R_arr = np.arange(2, 32, 2)
for p in P_arr:
path = 'recovery_result4/case' + str(len(G['bus'])) + '_0.3'
if os.path.exists(path) == False:
os.mkdir(path)
file_name = path + '/case' + str(len(
G['bus'])) + '_setup_' + str(p) + '.txt'
new_file = open(file_name, 'w')
new_file.write('ramp_rate = ' + str(ramp_rate) + '\n')
new_file.write('P=' + str(p) + ' , ' + 'R=' + str(R) + ' , ' +
'round=' + str(round) + '\n')
new_file.write('length of recovery seq ' + str(seq_len) + '\n')
g = Power_Graph()
g.init_by_case(G)
g.set_ramp_rate(ramp_rate)
delete_list = []
while len(delete_list) != delete_num:
ran_num = random.randint(1, len(G['bus']))
if ran_num not in delete_list:
delete_list.append(ran_num)
delete_list = [
66, 289, 298, 255, 72, 87, 263, 290, 83, 167, 241, 13, 225, 243,
232, 34, 147, 269, 132, 249, 122, 2, 37, 127, 94, 199, 202, 76,
156, 67, 131, 248, 188, 238, 15, 84, 44, 8, 220, 189, 206, 162,
169, 107, 17, 282, 164, 198, 115, 261
]
#delete_list=[192, 27, 15, 153, 198, 189, 171, 33, 256, 265, 25, 218, 284, 6, 261, 155, 131, 260, 97, 93, 55, 95, 124, 69, 37, 34, 94, 201, 12, 144, 1, 254, 193, 83, 59, 230, 289, 9, 200, 264, 277, 246, 143, 179, 100, 232, 233, 91, 151, 170]
#delete_list=[105, 49, 69, 110, 28, 62, 31, 41, 96, 15, 108, 67, 63, 115, 79, 101, 83, 76, 61, 75, 45, 12, 32, 113, 98, 111, 91, 95, 68, 9]
#delete_list = [74, 45, 51, 1, 106, 3, 82, 67, 90, 114, 81, 30, 7, 17, 79, 103, 95, 46, 115, 118, 40, 117, 96, 116, 88, 27, 57, 110, 28, 21]
#delete_list=[25, 17, 8, 32, 37, 24, 9, 28, 47, 15]
#delete_list = [37, 18, 31, 20, 1, 35, 15, 57, 54, 2, 17, 6, 51, 3, 55]
new_file.write('delete length ' + str(len(delete_list)) + '\n')
new_file.write('delete list ' + str(delete_list) + '\n')
for item in delete_list:
g.delete_bus(item)
cf = Power_Failure(g)
for item in delete_list:
cf.failed_bus_id.append(item)
cf.failure_process()
new_file.write('num of failed bus ' + str(len(cf.failed_bus_id)) +
'\n')
new_file.write('failed bus ' + str(cf.failed_bus_id) + '\n')
steady_bus_num = 0
steady_branch_num = 0
for graph in cf.steady_list:
steady_bus_num += len(graph.bus_id)
steady_branch_num += len(graph.branch)
new_file.write('num of steady bus ' + str(steady_bus_num) + '\n')
new_file.write('num of steady branch ' + str(steady_branch_num) +
'\n\n')
ini_g = Power_Graph()
ini_g.init_by_case(G)
R_SAG = Recovery_SAG(cf.steady_list, ini_g)
R_SAG.initialize_param(p, R, round)
candidate_set = R_SAG.cal_candidate_set()
RRC_set = R_SAG.cal_RRC_set()
RRC_seq = {}
RRC_residual_per = {}
for i in range(1, seq_len + 1):
RRC_residual_per[i] = 0.0
for item in RRC_set.items():
# print item
new_file.write(str(item[0]) + '\n')
current_set = item[1]
sorted_list = sorted(current_set.items(),
key=lambda item: item[1],
reverse=True)
for k, v in sorted_list:
new_file.write(str(k) + ' ' + str(v) + '\n')
if v > RRC_residual_per[len(k)]:
RRC_seq[len(k)] = k
RRC_residual_per[len(k)] = v
new_file.write('\n')
R_SAG.construct_SAG()
new_file.write('node num of SRG ' + str(len(R_SAG.SAG.node_list)) +
'\n\n')
for current in range(2, seq_len + 1):
SAG_seq = R_SAG.cal_SAG_recovery_seq_2(current)
steady_list = copy.deepcopy(cf.steady_list)
gr = Grid_Recovery(steady_list, ini_g)
ini_residual_per = gr.cal_residual_power()
SRG_residual_per = gr.recover_with_sequence(SAG_seq)
steady_list = copy.deepcopy(cf.steady_list)
gr = Grid_Recovery(steady_list, ini_g)
degree_residual_per, degree_seq = gr.recovery_degree_2(current)
steady_list = copy.deepcopy(cf.steady_list)
gr = Grid_Recovery(steady_list, ini_g)
low_degree_residual_per, low_degree_seq = gr.recovery_low_degree_2(
current)
steady_list = copy.deepcopy(cf.steady_list)
gr = Grid_Recovery(steady_list, ini_g)
load_residual_per, load_seq = gr.recovery_load_2(current)
steady_list = copy.deepcopy(cf.steady_list)
gr = Grid_Recovery(steady_list, ini_g)
low_load_residual_per, low_load_seq = gr.recovery_low_load_2(
current)
sum = 0.0
for i in range(0, random_rep_num):
steady_list = copy.deepcopy(cf.steady_list)
gr = Grid_Recovery(steady_list, ini_g)
residual_per, seq = gr.recovery_random_2(current)
sum += residual_per
aver_residual_per = sum / random_rep_num
new_file.write('current length of seq: ' + str(current) + '\n')
new_file.write('SRG recovery seq ' + str(SAG_seq) + '\n')
new_file.write('RRC recovery seq ' + str(RRC_seq[current]) + '\n')
new_file.write('high degree based recovery seq ' +
str(degree_seq) + '\n')
new_file.write('low degree based recovery seq ' +
str(low_degree_seq) + '\n')
new_file.write('high load based recovery seq ' + str(load_seq) +
'\n')
new_file.write('low load based recovery seq ' + str(low_load_seq) +
'\n')
new_file.write('\n')
new_file.write('residual percent of power before recovery ' +
str(ini_residual_per) + '\n')
new_file.write('residual percent of power after SRG recovery ' +
str(SRG_residual_per) + '\n')
new_file.write('residual percent of power after RRC recovery ' +
str(RRC_residual_per[current]) + '\n')
new_file.write(
'residual percent of power after high degree based recovery ' +
str(degree_residual_per) + '\n')
new_file.write(
'residual percent of power after low degree based recovery ' +
str(low_degree_residual_per) + '\n')
new_file.write(
'residual percent of power after high load based recovery ' +
str(load_residual_per) + '\n')
new_file.write(
'residual percent of power after low load based recovery ' +
str(low_load_residual_per) + '\n')
new_file.write(
'average residual percent of power after random based recovery '
+ str(aver_residual_per) + '\n')
new_file.write('\n\n')
new_file.close()
