/
sample_generator.py
2195 lines (2083 loc) · 115 KB
/
sample_generator.py
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from ast import dump
from cgitb import small
import math
import pathlib
from numpy.core.arrayprint import dtype_is_implied
from numpy.random import sample
import ray
from tqdm import tqdm
import collections
import pickle
from sklearn.model_selection import train_test_split
from py_psops import Py_PSOPS
import numpy as np
import time
import matplotlib as mpl
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import os
font1 = {'size': 12}
def plot_dots(x, y, color, lw=1):
assert x.shape[0] == y.shape[0], "x, y dimensional error"
if y.ndim == 1:
plt.scatter(x, y, alpha=0.5)
elif y.ndim == 2:
pass
else:
raise Exception(f"{y.ndim} dimensional data input!")
def plot_show():
plt.show()
def contour_plot(xx, yy, zz):
contour = plt.contour(xx, yy, zz, 100, cmap='rainbow')
plt.clabel(contour, fontsize=6, colors='k')
# 去掉坐标轴刻度
# plt.xticks(())
# plt.yticks(())
# 填充颜色，f即filled,6表示将三色分成三层，cmap那儿是放置颜色格式，hot表示热温图（红黄渐变）
# 更多颜色图参考：https://blog.csdn.net/mr_cat123/article/details/80709099
# 颜色集，6层颜色，默认的情况不用写颜色层数,
# c_set = plt.contourf(xx, yy, zz, cmap='rainbow')
# or c_map='hot'
# 设置颜色条，（显示在图片右边）
# plt.colorbar(c_set)
# 显示
plt.show()
def plot_3d(xx, yy, zz):
fig = plt.figure()
ax = Axes3D(fig)
# ax.plot_surface(xx, yy, zz, cmap='rainbow')
ax.plot_surface(xx, yy, zz, rstride=1, cstride=1,
alpha=0.75, cmap='rainbow')
ax.contour(xx, yy, zz, zdir='z', offset=zz.min(),
cmap='rainbow') # 等高线图，要设置offset，为Z的最小值
ax.contour(xx, yy, zz, zdir='y', offset=yy.max(), cmap='rainbow')
ax.contour(xx, yy, zz, zdir='x', offset=xx.min(), cmap='rainbow')
plt.show()
def read_result(f_path):
file = open(f_path, 'r', encoding='gbk')
lines = file.readlines()
file.close()
num = 0
gen1 = list()
gen2 = list()
list_loss = list()
list_180 = list()
list_500 = list()
list_d = list()
for line in lines:
if line[0] == 'g':
continue
if line.strip() != '':
num += 1
line_array = line.strip().split()
gen1.append(float(line_array[0]))
gen2.append(float(line_array[1]))
list_loss.append(-float(line_array[2]))
list_180.append(float(line_array[3]))
list_500.append(float(line_array[4]))
list_d.append(float(line_array[5]))
mesh = int(num ** 0.5)
assert mesh * mesh == num, 'Line num is not correct!'
gen1 = np.array(gen1).reshape(mesh, mesh)
gen2 = np.array(gen2).reshape(mesh, mesh)
list_loss = np.array(list_loss).reshape(mesh, mesh)
list_180 = np.array(list_180).reshape(mesh, mesh)
list_500 = np.array(list_500).reshape(mesh, mesh)
list_d = np.array(list_d).reshape(mesh, mesh)
# list_d = (360. - list_d) / (360. + list_d) * 100.
# list_d[list_d > 300.] = 300.
# list_loss = list_180
list_loss = -list_loss + list_180 - 10.
loss_min = list_loss[list_d < 180.].max()
idx = np.where(list_loss == loss_min)
print(list_loss[list_d < 180.].max(), gen1[idx], gen2[idx])
list_loss = np.array(list_loss)
# list_loss = list_d
# fig = plt.figure()
# ax = fig.add_subplot(111, projection='3d')
# # ax.plot_surface(gen2, gen1, list_loss, rstride=1, cstride=1, alpha=0.5, cmap='rainbow', zorder=0)
# # ax.contour(gen2, gen1, list_loss, zdir='z', offset=list_loss.min(), cmap='rainbow') # 等高线图，要设置offset，为Z的最小值
# # ax.set_xlabel('Gen_BUS38', fontdict=font1)
# # ax.set_ylabel('Gen_BUS30', fontdict=font1)
# # ax.set_zlabel('Delta_MAX', fontdict=font1)
# ax.plot_surface(gen1, gen2, list_loss, rstride=1, cstride=1, alpha=0.5, cmap='rainbow', zorder=0)
# ax.contour(gen1, gen2, list_loss, zdir='z', offset=list_loss.min(), cmap='rainbow') # 等高线图，要设置offset，为Z的最小值
# ax.set_xlabel('Gen_BUS30', fontdict=font1)
# ax.set_ylabel('Gen_BUS38', fontdict=font1)
# ax.set_zlabel('Ts', fontdict=font1)
# plt.tick_params(labelsize=12)
# ls = np.load('./result_dist.npz', allow_pickle=True)
# x = ls['action_sequence']
# print(x.shape)
# for search_line in x:
# xd = search_line[:, 0]
# yd = search_line[:, 1]
# zd = search_line[:, 2]
# ax.scatter3D(xd, yd, zd, c='k', marker='o', s=50, linewidths=1, alpha=0.25, zorder=1)
# ax.plot(xd, yd, zd, c='k', lw=2, alpha=0.2, zorder=1)
# ax.scatter3D(xd, yd, zd, c='k', marker='o', s=50, linewidths=5, zorder=2) # 绘制散点图
# ax.plot(xd, yd, zd, c='k', lw=2, zorder=2)
contour = plt.contour(gen1, gen2, list_loss, 100, cmap='rainbow', zorder=2)
plt.clabel(contour, fontsize=8, colors='k')
plt.xlim((1.25, 3.75))
plt.ylim((3.25, 9.75))
plt.xlabel('Gen_BUS30', fontdict=font1)
plt.ylabel('Gen_BUS38', fontdict=font1)
plt.tick_params(labelsize=12)
ls = np.load('../results/result_dist.npz', allow_pickle=True)
x = ls['action_sequence']
print(x.shape)
max_re = -999999999.9
max_no = -1
max_seq = None
for seq_no in range(x.shape[0]):
if max_re < np.max(x[seq_no][:, 3]):
max_re = np.max(x[seq_no][:, 3])
max_no = seq_no
max_seq = x[seq_no]
assert max_seq is not None, 'no max reward'
print(max_re, max_no, max_seq)
xd = max_seq[:7, 1]
yd = max_seq[:7, 2]
plt.scatter(xd, yd, c='k', marker='o', s=50, linewidths=5, zorder=2)
plt.plot(xd, yd, c='k', lw=2, zorder=2)
for search_line in x:
xd = search_line[:, 1]
yd = search_line[:, 2]
plt.scatter(xd, yd, c='darkgrey', marker='o', s=50, linewidths=1, alpha=0.25, zorder=1)
plt.plot(xd, yd, c='darkgrey', lw=2, alpha=0.25, zorder=1)
# plt.scatter(xd, yd, c='r', marker='o', s=50, linewidths=5, zorder=2)
# plt.plot(xd, yd, c='r', lw=2, zorder=2)
# search_line = x[-2]
# xd = search_line[:, 1]
# yd = search_line[:, 2]
# plt.scatter(xd, yd, c='b', marker='o', s=50, linewidths=5, zorder=2)
# plt.plot(xd, yd, c='b', lw=2, zorder=2)
plt.show()
# plot_3d(gen1, gen2, np.array(list_loss))
# contour_plot(gen1, gen2, np.array(list_loss))
# plot_3d(gen1, gen2, np.array(list_180))
# contour_plot(gen1, gen2, np.array(list_180))
# plot_3d(gen1, gen2, np.array(list_500))
# contour_plot(gen1, gen2, np.array(list_500))
# plot_3d(gen2, gen1, list_d)
# contour_plot(gen2, gen1, list_d)
# plot_3d(gen2, gen1, 1. / list_d)
# contour_plot(gen2, gen1, 1. / list_d)
class SampleGenerator:
def __init__(self, worker_no, total_worker, basic_seed):
self.workerNo = worker_no
self.totalWorker = total_worker
self.seed = 42 + worker_no * 42 * basic_seed + worker_no
self.rng = np.random.default_rng(self.seed)
# self.__rng = np.random.default_rng()
self.api = Py_PSOPS(flg=self.workerNo, rng=self.rng)
# self.env = sopf_Env(rng=self.__rng, test_on=True)
# self.env.set_flg(worker_no)
def ts_sampler_basic(
self,
result_path,
total_num=1,
round_num=10,
cut_length=31,
test_per=0.2
):
api = self.api
result_path = pathlib.Path(result_path)
if not result_path.exists(): result_path.mkdir()
print(str(result_path.absolute()))
# random selection range
aclines = np.arange(api.get_acline_number())
fault_duration = 0.08 + np.arange(13) * 0.01
total_step = api.get_info_ts_max_step()
cut_length = min(total_step, cut_length)
sampled = tqdm(total=total_num)
stable_num = tqdm(total=max(int(total_num*0.25), 1))
rotor_unstable_num = tqdm(total=max(int(total_num*0.25), 1))
volt_unstable_num = tqdm(total=max(int(total_num*0.25), 1))
freq_unstable_num = tqdm(total=max(int(total_num*0.25), 1))
topo_list = list()
fault_list = list()
label_list = np.zeros([total_num], dtype=float)
system_list = np.zeros([total_num, cut_length, 6], dtype=float)
delta_list = np.zeros([total_num, cut_length, api.get_generator_number()], dtype=float)
volt_list = np.zeros([total_num, cut_length, api.get_bus_number()], dtype=float)
transfer_list = np.zeros([total_num, cut_length, api.get_acline_number()], dtype=float)
admittance_list = np.zeros([total_num, 3, 2, api.get_bus_number(), api.get_bus_number()], dtype=float)
impedance_list = np.zeros([total_num, 3, 2, api.get_bus_number(), api.get_bus_number()], dtype=float)
fac_imp_LD_list = np.zeros([total_num, 3, api.get_network_n_inverse_non_zero()+api.get_bus_number(), 6], dtype=float)
fac_imp_U_list = np.zeros([total_num, 3, api.get_network_n_inverse_non_zero()+api.get_bus_number(), 6], dtype=float)
fac_imp_Diag_list = np.zeros([total_num, 3, api.get_bus_number(), 6], dtype=float)
topo_no = 0
tmp_list = list()
cur_fault = list()
while(1):
# topo sampling
topo_sample = api.get_network_topology_sample(topo_change=int(topo_no%3))
# power flow sampling
pf_samples = api.get_power_flow_sample_stepwise(num=round_num, check_voltage=False, termination_num=500)
if len(pf_samples) == 0: continue
# ts sampling
for pf_no in range(len(pf_samples)):
# restore power flow
api.set_power_flow_initiation(pf_samples[pf_no])
api.cal_power_flow_basic_nr()
for fault_no in range(round_num):
# fault line sample, n-1 or n-2
while True:
tmp_list = self.rng.choice(aclines, int(fault_no%2)+1, False)
api.set_network_acline_all_connectivity([False]*(int(fault_no%2)+1), tmp_list)
if api.get_network_n_acsystem_check_connectivity() == 1: break
api.set_network_acline_all_connectivity([True]*(int(fault_no%2)+1), tmp_list)
api.set_network_acline_all_connectivity([True]*(int(fault_no%2)+1), tmp_list)
# line fault setting
cur_fault.clear()
api.set_fault_disturbance_clear_all()
for acline_no in tmp_list:
loc = self.rng.choice([0, 100])
f_time = self.rng.choice(fault_duration)
cur_fault.append([acline_no] + api.get_acline_info(acline_no) + [loc, f_time])
api.set_fault_disturbance_add_acline(0, loc, 0.0, f_time, acline_no)
api.set_fault_disturbance_add_acline(1, loc, f_time, 10., acline_no)
# simulation
fin_step = api.cal_transient_stability_simulation_ti_sv()
if fin_step < cut_length: continue
# label determination
label = api.get_transient_stability_check_stability()
if label == 0 and stable_num.n >= stable_num.total: continue
if label == 1 and rotor_unstable_num.n >= rotor_unstable_num.total: continue
if label == 2 and volt_unstable_num.n >= volt_unstable_num.total: continue
if label == 3 and freq_unstable_num.n >= freq_unstable_num.total: continue
sim_valid, start_topo, result_all, result_ang, result_vol, result_tran, adm_list, imp_list, fac_imp_list = api.get_transient_stability_all_relevant_data()
if sim_valid == False: continue
# save results
label_list[sampled.n] = label
system_list[sampled.n, :, :] = result_all[:cut_length]
delta_list[sampled.n, :, :] = result_ang[:cut_length, :, 0]
volt_list[sampled.n, :, :] = result_vol[:cut_length, :, 0]
transfer_list[sampled.n, :, :] = result_tran[:cut_length, :, 0]
# save topo and faults
topo_list.append(topo_sample)
fault_list.append(cur_fault.copy())
# topo matrix
admittance_list[sampled.n, :, :, :, :] = adm_list[:, :, :, :]
impedance_list[sampled.n, :, :, :, :] = imp_list[:, :, :, :]
for f_step in range(3):
fac_imp_LD_list[sampled.n, f_step, :, :] = fac_imp_list[f_step][0]
fac_imp_U_list[sampled.n, f_step, :, :] = fac_imp_list[f_step][1]
fac_imp_Diag_list[sampled.n, f_step, :, :] = fac_imp_list[f_step][2]
# sample count
sampled.update(1)
if label == 0: stable_num.update(1)
if label == 1: rotor_unstable_num.update(1)
if label == 2: volt_unstable_num.update(1)
if label == 3: freq_unstable_num.update(1)
if sampled.n >= total_num: break
if sampled.n >= total_num: break
if sampled.n >= total_num: break
topo_no += 1
total_idx = np.arange(total_num)
train_idx, test_idx = train_test_split(total_idx, test_size=test_per, random_state=42)
topo_list = np.array(topo_list, dtype=object)
fault_list = np.array(fault_list, dtype=object)
np.savez(result_path / f'training.{self.workerNo}.{self.seed}.npz',
label=label_list[train_idx],
topo=topo_list[train_idx],
fault=fault_list[train_idx],
sys=system_list[train_idx],
delta=delta_list[train_idx],
volt=volt_list[train_idx],
transfer=transfer_list[train_idx],
admittance=admittance_list[train_idx],
impedance=impedance_list[train_idx],
fipld=fac_imp_LD_list[train_idx],
fipu=fac_imp_U_list[train_idx],
fipdiag=fac_imp_Diag_list[train_idx]
)
np.savez(result_path / f'testing.{self.workerNo}.{self.seed}.npz',
label=label_list[test_idx],
topo=topo_list[test_idx],
fault=fault_list[test_idx],
sys=system_list[test_idx],
delta=delta_list[test_idx],
volt=volt_list[test_idx],
transfer=transfer_list[test_idx],
admittance=admittance_list[test_idx],
impedance=impedance_list[test_idx],
fipld=fac_imp_LD_list[test_idx],
fipu=fac_imp_U_list[test_idx],
fipdiag=fac_imp_Diag_list[test_idx]
)
def ts_sampler_simple_random_for_avr_1(self,
gen_no,
result_path,
num=1,
test_per=0.2,
cut_length=None,
check_voltage=False,
check_slack=False,
limit_3phase_short=False,
must_stable=False,
limit_angle_range = False,
balance_stability=False,
need_larger_than=None,
need_smaller_than=None):
api = self.api
assert must_stable != True or balance_stability != True, "do not need balance_stability when must_stable"
assert must_stable != True or limit_angle_range != True, "do not need balance_stability when must_stable"
assert (need_larger_than is None and need_smaller_than is None) or (need_larger_than is not None and need_smaller_than is not None), "need_larger_than and need_smaller_than must be the same type"
result_path = pathlib.Path(result_path)
if not result_path.exists(): result_path.mkdir()
print(str(result_path.absolute()))
choice_aclines = np.arange(api.get_acline_number())
choice_generators = np.arange(api.get_generator_number())
choice_generators = choice_generators[np.where(choice_generators != gen_no)]
choice_loads = np.arange(api.get_load_number())
total_step = api.get_info_ts_max_step()
total_step = min(total_step, cut_length) if cut_length is not None else total_step
t = np.ones([num, total_step, 1], dtype=np.float32) * -1
mask = np.zeros([num, total_step, 1], dtype=np.float32)
x = np.zeros([num, total_step, 1], dtype=np.float32)
z = np.zeros([num, total_step, 2], dtype=np.float32)
event_t = np.zeros([num, 3], dtype=np.float32)
z_jump = np.zeros([num, 3, 2], dtype = np.float32)
total_sim = 0
sampled = 0
sampled_stable = 0
sampled_unstable = 0
sampled_larger = 0
larger_sample = 0 if need_larger_than is None else int(num * 0.3)
sampled_smaller = 0
smaller_sample = 0 if need_smaller_than is None else int(num * 0.3)
old_sampled = -1
flg_no_change = 0
while sampled < num:
if old_sampled == sampled: flg_no_change += 1
old_sampled = sampled
samples = api.get_power_flow_sample_stepwise(num=num, check_voltage=check_voltage, check_slack=check_slack)
for sample in samples:
api.set_power_flow_initiation(sample)
api.cal_power_flow_basic_nr()
api.set_fault_disturbance_clear_all()
if limit_3phase_short:
if flg_no_change < 3: fd_idx = sampled % 5
else: fd_idx = total_sim % 5
if fd_idx == 0:
acline_no = self.rng.choice(choice_aclines)
loc = self.rng.choice([0, 100])
api.set_fault_disturbance_add_acline(0, loc, 1.0, 1.3, acline_no)
api.set_fault_disturbance_add_acline(1, loc, 1.3, 10., acline_no)
elif fd_idx == 1 or fd_idx == 2:
g_no = self.rng.choice(choice_generators)
api.set_fault_disturbance_add_generator(0, 1.0, 0.5, g_no)
api.set_fault_disturbance_add_generator(0, 1.3, 0.5, g_no)
elif fd_idx == 3 or fd_idx == 4:
l_no = self.rng.choice(choice_loads)
api.set_fault_disturbance_add_load(0, 1.0, 0.5, l_no)
api.set_fault_disturbance_add_load(0, 1.3, 0.5, l_no)
else:
acline_no = self.rng.choice(choice_aclines)
loc = self.rng.choice([0, 100])
api.set_fault_disturbance_add_acline(0, loc, 1.0, 1.3, acline_no)
api.set_fault_disturbance_add_acline(1, loc, 1.3, 10., acline_no)
real_fin_step = api.cal_transient_stability_simulation_ti_sv()
total_sim += 1
# cut length check
if cut_length is not None:
if real_fin_step > cut_length: real_fin_step = cut_length
# check e step
e_step = api.get_info_fault_step_sequence()
for flt_no in range(len(e_step)):
e_step += 1
api.set_info_ts_step_element_state(e_step[flt_no], is_real_step=False)
tmp_re = api.get_generator_exciter_ts_cur_step_result(gen_no, rt=True)
if np.any(tmp_re != tmp_re): continue
# get results
result_all = api.get_acsystem_all_ts_result()[0]
if np.any(result_all != result_all): continue
# check stability
fin_step = real_fin_step
delta_diff = result_all[:fin_step, 1]
min_vol = result_all[:fin_step, 4]
min_freq = result_all[:fin_step, 2]
max_freq = result_all[:fin_step, 3]
label = 0
vol_count = 0
for step in range(fin_step):
if delta_diff[step] > 360.:
label = 1
break
# if min_vol[step] < 0.7: vol_count += 1
# else: vol_count = 0
# if vol_count > 100:
# label = 2
# break
# if min_freq[step] < 49.:
# label = 3
# break
# if max_freq[step] > 51.:
# label = 4
# break
if label != 0:
if must_stable: continue
if balance_stability and sampled_unstable >= num / 2: continue
if limit_angle_range: fin_step = step
else:
if balance_stability and sampled_stable >= num / 2: continue
# check result
result = api.get_generator_exciter_ts_all_step_result(gen_no)
if np.any(result[:fin_step] != result[:fin_step]): continue
# check sample requirement
if need_larger_than is not None and sampled >= num - larger_sample - larger_sample:
if sampled_larger >= larger_sample and sampled_smaller >= smaller_sample: pass
else:
if result[:fin_step, -1].max() < need_larger_than and result[:fin_step, -1].min() > need_smaller_than: continue
flg = False
if sampled_larger < larger_sample and result[:fin_step, -1].max() > need_larger_than: flg = True
if sampled_smaller < smaller_sample and result[:fin_step, -1].min() < need_smaller_than: flg = True
if flg == False: continue
# time step
assert np.all(t[sampled] == -1), "this sample space has been polluted!!!!!!!!!!!!!!!!!"
t[sampled, :fin_step, 0] = result_all[:fin_step, 0]
# masks
mask[sampled, :fin_step, 0] = 1.
# event time
event_t[sampled] = api.get_info_fault_time_sequence()
# event data
e_step = api.get_info_fault_step_sequence()
for flt_no in range(len(e_step)):
e_step += 1
api.set_info_ts_step_element_state(e_step[flt_no], is_real_step=False)
tmp_re = api.get_generator_exciter_ts_cur_step_result(gen_no, rt=True)
z_jump[sampled][flt_no][0] = tmp_re[0]
z_jump[sampled][flt_no][1] = tmp_re[-2]
x[sampled, :fin_step, 0] = result[:fin_step, -1] # efd
# voltages and vs
z[sampled, :fin_step, 0] = result[:fin_step, 0] # vt
z[sampled, :fin_step, 1] = result[:fin_step, -2] # VS
# check requirements
if need_larger_than is not None and sampled >= num - larger_sample - larger_sample:
if sampled_larger >= larger_sample and sampled_smaller >= smaller_sample: pass
else:
if sampled_larger < larger_sample and result[:fin_step, -1].max() > need_larger_than: sampled_larger += 1
if sampled_smaller < smaller_sample and result[:fin_step, -1].min() < need_smaller_than: sampled_smaller += 1
# check stability balance
if balance_stability:
if label != 0: sampled_unstable += 1
else: sampled_stable += 1
# count samples
sampled += 1
if sampled >= num: break
print(f'sampled: {sampled}, stable: {sampled_stable}, unstable: {sampled_unstable}, larger: {sampled_larger}, smaller: {sampled_smaller}')
total_idx = np.arange(num)
train_idx, test_idx = train_test_split(total_idx, test_size=test_per, random_state=4242)
data_name = [
['Efd', 'p.u.']
]
np.savez(result_path / 'full.npz', name=data_name, t=t, x=x, z=z, event_t=event_t, z_jump=z_jump, mask=mask)
np.savez(result_path / 'training.npz', name=data_name, t=t[train_idx], x=x[train_idx], z=z[train_idx],
event_t=event_t[train_idx], z_jump=z_jump[train_idx], mask=mask[train_idx])
np.savez(result_path / 'testing.npz', name=data_name, t=t[test_idx], x=x[test_idx], z=z[test_idx],
event_t=event_t[test_idx], z_jump=z_jump[test_idx], mask=mask[test_idx])
def ts_sampler_simple_random_for_gen_0(self,
gen_no,
result_path,
num=1,
test_per=0.2,
cut_length=None,
check_voltage=False,
check_slack=False,
limit_3phase_short=False,
must_stable=False,
limit_angle_range = False,
balance_stability=False
):
api = self.api
assert must_stable != True or balance_stability != True, "do not need balance_stability when must_stable"
assert must_stable != True or limit_angle_range != True, "do not need balance_stability when must_stable"
result_path = pathlib.Path(result_path)
if not result_path.exists(): result_path.mkdir()
print(str(result_path.absolute()))
choice_aclines = np.arange(api.get_acline_number())
choice_generators = np.arange(api.get_generator_number())
choice_generators = choice_generators[np.where(choice_generators != gen_no)]
choice_loads = np.arange(api.get_load_number())
total_length = api.get_info_ts_max_step() if cut_length is None else cut_length
t = np.ones([num, total_length, 1], dtype=np.float32) * -1
mask = np.zeros([num, total_length, 1], dtype=np.float32)
x = np.zeros([num, total_length, 2], dtype=np.float32)
z = np.zeros([num, total_length, 0], dtype=np.float32)
v = np.zeros([num, total_length, 2], dtype=np.float32)
i = np.zeros([num, total_length, 2], dtype=np.float32)
event_t = np.zeros([num, 3], dtype=np.float32)
z_jump = np.zeros([num, 3, 0], dtype = np.float32)
v_jump = np.zeros([num, 3, 2], dtype = np.float32)
total_sim = 0
sampled = 0
sampled_stable = 0
sampled_unstable = 0
old_sampled = -1
flg_no_change = 0
while sampled < num:
if old_sampled == sampled: flg_no_change += 1
old_sampled = sampled
samples = api.get_power_flow_sample_stepwise(num=num, check_voltage=check_voltage, check_slack=check_slack)
for sample in samples:
api.set_power_flow_initiation(sample)
api.cal_power_flow_basic_nr()
api.set_fault_disturbance_clear_all()
if limit_3phase_short:
if flg_no_change < 3: fd_idx = sampled % 5
else: fd_idx = total_sim % 5
if fd_idx == 0:
acline_no = self.rng.choice(choice_aclines)
loc = self.rng.choice([0, 100])
api.set_fault_disturbance_add_acline(0, loc, 1.0, 1.3, acline_no)
api.set_fault_disturbance_add_acline(1, loc, 1.3, 10., acline_no)
elif fd_idx == 1 or fd_idx == 2:
g_no = self.rng.choice(choice_generators)
api.set_fault_disturbance_add_generator(0, 1.0, 0.5, g_no)
api.set_fault_disturbance_add_generator(0, 1.3, 0.5, g_no)
elif fd_idx == 3 or fd_idx == 4:
l_no = self.rng.choice(choice_loads)
api.set_fault_disturbance_add_load(0, 1.0, 0.5, l_no)
api.set_fault_disturbance_add_load(0, 1.3, 0.5, l_no)
else:
acline_no = self.rng.choice(choice_aclines)
loc = self.rng.choice([0, 100])
api.set_fault_disturbance_add_acline(0, loc, 1.0, 1.3, acline_no)
api.set_fault_disturbance_add_acline(1, loc, 1.3, 10., acline_no)
real_fin_step = api.cal_transient_stability_simulation_ti_sv()
total_sim += 1
# cut length check
if cut_length is not None:
if real_fin_step > cut_length: real_fin_step = cut_length
# check e step
e_step = api.get_info_fault_step_sequence()
for flt_no in range(len(e_step)):
e_step += 1
api.set_info_ts_step_element_state(e_step[flt_no], is_real_step=False)
tmp_re = api.get_generator_ts_cur_step_result(gen_no, rt=True)
if np.any(tmp_re != tmp_re): continue
# get results
result_all = api.get_acsystem_all_ts_result()[0]
if np.any(result_all != result_all): continue
# check stability
fin_step = real_fin_step
delta_diff = result_all[:fin_step, 1]
min_vol = result_all[:fin_step, 4]
min_freq = result_all[:fin_step, 2]
max_freq = result_all[:fin_step, 3]
label = 0
vol_count = 0
for step in range(fin_step):
if delta_diff[step] > 360.:
label = 1
break
if min_vol[step] < 0.7: vol_count += 1
else: vol_count = 0
if vol_count > 100:
label = 2
break
if min_freq[step] < 49.:
label = 3
break
if max_freq[step] > 51.:
label = 4
break
if label != 0:
if must_stable: continue
if balance_stability and sampled_unstable >= num / 2: continue
if limit_angle_range: fin_step = step
else:
if balance_stability and sampled_stable >= num / 2: continue
# check result
result = api.get_generator_ts_all_step_result(gen_no, need_inner_e=True)
if np.any(result[:fin_step] != result[:fin_step]): continue
# time step
assert np.all(t[sampled] == -1), "this sample space has been polluted!!!!!!!!!!!!!!!!!"
t[sampled, :fin_step, 0] = result_all[:fin_step, 0]
# masks
mask[sampled, :fin_step, 0] = 1.
# state variables
result[:, 0] /= 180. / math.pi
result[:, 1] = (result[:, 1] - 50)
result[:, 3] /= 180. / math.pi
x[sampled, :fin_step, 0] = result[:fin_step, 0]
x[sampled, :fin_step, 1] = result[:fin_step, 1]
v[sampled, :fin_step, 0] = result[:fin_step, 2] * np.cos(result[:fin_step, 3])
v[sampled, :fin_step, 1] = result[:fin_step, 2] * np.sin(result[:fin_step, 3])
vv = v[sampled, :fin_step, :2]
# inject currents
i[sampled, :fin_step, 0] = (result[:fin_step, 4] * vv[:fin_step, 0] + result[:fin_step, 5] * vv[:fin_step, 1]) / (vv[:fin_step, 0] * vv[:fin_step, 0] + vv[:fin_step, 1] * vv[:fin_step, 1])
i[sampled, :fin_step, 1] = (result[:fin_step, 4] * vv[:fin_step, 1] - result[:fin_step, 5] * vv[:fin_step, 0]) / (vv[:fin_step, 0] * vv[:fin_step, 0] + vv[:fin_step, 1] * vv[:fin_step, 1])
# event time
event_t[sampled] = api.get_info_fault_time_sequence()
# event data
e_step = api.get_info_fault_step_sequence()
for flt_no in range(len(e_step)):
e_step += 1
api.set_info_ts_step_element_state(e_step[flt_no], is_real_step=False)
tmp_re = api.get_generator_ts_cur_step_result(gen_no, rt=True)
tmp_re[3] /= 180. / math.pi
v_jump[sampled][flt_no][0] = tmp_re[2] * np.cos(tmp_re[3])
v_jump[sampled][flt_no][1] = tmp_re[2] * np.sin(tmp_re[3])
# check stability balance
if balance_stability:
if label != 0: sampled_unstable += 1
else: sampled_stable += 1
# count samples
sampled += 1
if sampled >= num: break
print(f'sampled: {sampled}, stable: {sampled_stable}, unstable: {sampled_unstable}')
total_idx = np.arange(num)
train_idx, test_idx = train_test_split(total_idx, test_size=test_per, random_state=4242)
data_name = [
['Rotor Angle', 'Rad.'],
['Omega', 'p.u.'],
['Ix', 'p.u.'],
['Iy', 'p.u.']
]
np.savez(result_path / 'full.npz', name=data_name, t=t, x=x, z=z, v=v, i=i, event_t=event_t, z_jump=z_jump, v_jump=v_jump, mask=mask)
np.savez(result_path / 'training.npz', name=data_name, t=t[train_idx], x=x[train_idx], z=z[train_idx], v=v[train_idx], i=i[train_idx],
event_t=event_t[train_idx], z_jump=z_jump[train_idx], v_jump=v_jump[train_idx], mask=mask[train_idx])
np.savez(result_path / 'testing.npz', name=data_name, t=t[test_idx], x=x[test_idx], z=z[test_idx], v=v[test_idx], i=i[test_idx],
event_t=event_t[test_idx], z_jump=z_jump[test_idx], v_jump=v_jump[test_idx], mask=mask[test_idx])
def ts_sampler_simple_random_for_custom_district(self,
result_path,
num=1,
test_per=0.2,
cut_length=None,
check_voltage=False,
check_slack=False,
limit_3phase_short=False,
must_stable=False,
limit_angle_range = False,
balance_stability=False
):
api = self.api
assert must_stable != True or balance_stability != True, "do not need balance_stability when must_stable"
assert must_stable != True or limit_angle_range != True, "do not need balance_stability when must_stable"
result_path = pathlib.Path(result_path)
if not result_path.exists(): result_path.mkdir()
print(str(result_path.absolute()))
choice_aclines = np.arange(api.get_acline_number())
choice_aclines = choice_aclines[np.where(choice_aclines != 0)]
choice_generators = np.arange(api.get_generator_number())
choice_generators = choice_generators[np.where(choice_generators != 3)]
choice_generators = choice_generators[np.where(choice_generators != 4)]
choice_loads = np.arange(api.get_load_number())
choice_loads = choice_loads[np.where(choice_loads != 4)]
total_length = api.get_info_ts_max_step() if cut_length is None else cut_length
t = np.ones([num, total_length, 1], dtype=np.float32) * -1
mask = np.zeros([num, total_length, 1], dtype=np.float32)
# x = np.zeros([num, total_length, 0], dtype=np.float32)
x = np.zeros([num, total_length, 6], dtype=np.float32)
z = np.zeros([num, total_length, 0], dtype=np.float32)
v = np.zeros([num, total_length, 2], dtype=np.float32)
i = np.zeros([num, total_length, 2], dtype=np.float32)
event_t = np.zeros([num, 3], dtype=np.float32)
z_jump = np.zeros([num, 3, 0], dtype = np.float32)
v_jump = np.zeros([num, 3, 2], dtype = np.float32)
total_sim = 0
sampled = 0
sampled_stable = 0
sampled_unstable = 0
old_sampled = -1
flg_no_change = 0
while sampled < num:
if old_sampled == sampled: flg_no_change += 1
old_sampled = sampled
samples = api.get_power_flow_sample_stepwise(num=num, check_voltage=check_voltage, check_slack=check_slack)
for sample in samples:
api.set_power_flow_initiation(sample)
api.cal_power_flow_basic_nr()
api.set_fault_disturbance_clear_all()
if limit_3phase_short:
if flg_no_change < 3: fd_idx = sampled % 5
else: fd_idx = total_sim % 5
if fd_idx == 0:
acline_no = self.rng.choice(choice_aclines)
loc = self.rng.choice([0, 100])
api.set_fault_disturbance_add_acline(0, loc, 1.0, 1.3, acline_no)
api.set_fault_disturbance_add_acline(1, loc, 1.3, 10., acline_no)
elif fd_idx == 1 or fd_idx == 2:
g_no = self.rng.choice(choice_generators)
api.set_fault_disturbance_add_generator(0, 1.0, 0.5, g_no)
api.set_fault_disturbance_add_generator(0, 1.3, 0.5, g_no)
elif fd_idx == 3 or fd_idx == 4:
l_no = self.rng.choice(choice_loads)
api.set_fault_disturbance_add_load(0, 1.0, 0.5, l_no)
api.set_fault_disturbance_add_load(0, 1.3, 0.5, l_no)
else:
acline_no = self.rng.choice(choice_aclines)
loc = self.rng.choice([0, 100])
api.set_fault_disturbance_add_acline(0, loc, 1.0, 1.3, acline_no)
api.set_fault_disturbance_add_acline(1, loc, 1.3, 10., acline_no)
real_fin_step = api.cal_transient_stability_simulation_ti_sv()
total_sim += 1
# cut length check
if cut_length is not None:
if real_fin_step < cut_length: continue #####################################################################################
if real_fin_step > cut_length: real_fin_step = cut_length
# check e step
e_step = api.get_info_fault_step_sequence()
valid = True
for flt_no in range(len(e_step)):
e_step[flt_no] += 1
if e_step[flt_no] > real_fin_step:
valid = False
break
api.set_info_ts_step_element_state(e_step[flt_no], is_real_step=False)
tmp_re = api.get_bus_ts_cur_step_result(bus_no=30, rt=True)
if np.any(tmp_re != tmp_re):
valid = False
continue
if valid == False:
continue
# get results
result_all = api.get_acsystem_all_ts_result()[0]
if np.any(result_all != result_all): continue
# check stability
fin_step = real_fin_step
delta_diff = result_all[:fin_step, 1]
min_vol = result_all[:fin_step, 4]
min_freq = result_all[:fin_step, 2]
max_freq = result_all[:fin_step, 3]
label = 0
vol_count = 0
for step in range(fin_step):
if delta_diff[step] > 360.:
label = 1
break
# if min_vol[step] < 0.7: vol_count += 1
# else: vol_count = 0
# if vol_count > 100:
# label = 2
# break
# if min_freq[step] < 49.:
# label = 3
# break
# if max_freq[step] > 51.:
# label = 4
# break
if label != 0:
if must_stable: continue
if balance_stability and sampled_unstable >= num / 2: continue
if limit_angle_range: #######################################################################################################################
# result_33 = api.get_generator_ts_all_step_result(3)
# result_34 = api.get_generator_ts_all_step_result(4)
# result_39 = api.get_generator_ts_all_step_result(9)
# d_33_39 = np.abs(result_33[:, 0] - result_39[:, 0])
# d_34_39 = np.abs(result_34[:, 0] - result_39[:, 0])
# if np.any(d_33_39 > 180.) or np.any(d_34_39 > 180.):
# continue
fin_step = step
# continue
else:
if balance_stability and sampled_stable >= num / 2: continue
# check result
result_33 = api.get_generator_ts_all_step_result(3)
result_34 = api.get_generator_ts_all_step_result(4)
result_20 = api.get_load_ts_all_step_result(3)
result_v = api.get_bus_all_ts_result(bus_list=[30])[:, 0, :]
result_pq = api.get_acline_all_ts_result(acline_list=[0])[:, 0, :]
if np.any(result_v != result_v) or np.any(result_pq != result_pq): continue
# time step
assert np.all(t[sampled] == -1), "this sample space has been polluted!!!!!!!!!!!!!!!!!"
t[sampled, :fin_step, 0] = result_all[:fin_step, 0]
# masks
mask[sampled, :fin_step, 0] = 1.
# state variables
x[sampled, :fin_step, 0:2] = result_33[:fin_step, 4:6]
x[sampled, :fin_step, 2:4] = result_34[:fin_step, 4:6]
x[sampled, :fin_step, 4:6] = result_20[:fin_step, 2:4]
# voltage
result_v[:, 1] /= 180. / math.pi
v[sampled, :fin_step, 0] = result_v[:fin_step, 0] * np.cos(result_v[:fin_step, 1])
v[sampled, :fin_step, 1] = result_v[:fin_step, 0] * np.sin(result_v[:fin_step, 1])
vv = v[sampled, :fin_step, :2]
# inject currents
i[sampled, :fin_step, 0] = -(result_pq[:fin_step, 0] * vv[:fin_step, 0] + result_pq[:fin_step, 1] * vv[:fin_step, 1]) / (vv[:fin_step, 0] * vv[:fin_step, 0] + vv[:fin_step, 1] * vv[:fin_step, 1])
i[sampled, :fin_step, 1] = -(result_pq[:fin_step, 0] * vv[:fin_step, 1] - result_pq[:fin_step, 1] * vv[:fin_step, 0]) / (vv[:fin_step, 0] * vv[:fin_step, 0] + vv[:fin_step, 1] * vv[:fin_step, 1])
# event time
event_t[sampled] = api.get_info_fault_time_sequence()
# event data
e_step = api.get_info_fault_step_sequence()
for flt_no in range(len(e_step)):
e_step += 1
api.set_info_ts_step_element_state(e_step[flt_no], is_real_step=False)
tmp_re = api.get_bus_ts_cur_step_result(bus_no=30, rt=True)
tmp_re[1] /= 180. / math.pi
v_jump[sampled][flt_no][0] = tmp_re[0] * np.cos(tmp_re[1])
v_jump[sampled][flt_no][1] = tmp_re[0] * np.sin(tmp_re[1])
# check stability balance
if balance_stability:
if label != 0: sampled_unstable += 1
else: sampled_stable += 1
# count samples
sampled += 1
if sampled >= num: break
print(f'sampled: {sampled}, stable: {sampled_stable}, unstable: {sampled_unstable}')
total_idx = np.arange(num)
train_idx, test_idx = train_test_split(total_idx, test_size=test_per, random_state=4242)
data_name = [
['P_33', 'p.u.'],
['Q_33', 'p.u.'],
['P_34', 'p.u.'],
['Q_34', 'p.u.'],
['P_20', 'p.u.'],
['Q_20', 'p.u.'],
['Ix', 'p.u.'],
['Iy', 'p.u.']
]
np.savez(result_path / 'full.npz', name=data_name, t=t, x=x, z=z, v=v, i=i, event_t=event_t, z_jump=z_jump, v_jump=v_jump, mask=mask)
np.savez(result_path / 'training.npz', name=data_name, t=t[train_idx], x=x[train_idx], z=z[train_idx], v=v[train_idx], i=i[train_idx],
event_t=event_t[train_idx], z_jump=z_jump[train_idx], v_jump=v_jump[train_idx], mask=mask[train_idx])
np.savez(result_path / 'testing.npz', name=data_name, t=t[test_idx], x=x[test_idx], z=z[test_idx], v=v[test_idx], i=i[test_idx],
event_t=event_t[test_idx], z_jump=z_jump[test_idx], v_jump=v_jump[test_idx], mask=mask[test_idx])
def ts_sampler_simple_random_for_Solar_district(self,
result_path,
num_total=1,
test_per=0.2,
cut_length=None,
check_voltage=False,
check_slack=False,
limit_3phase_short=False,
must_stable=False,
limit_angle_range = False,
balance_stability=False,
ratio_3phase=0.2
):
api = self.api
assert must_stable != True or balance_stability != True, "do not need balance_stability when must_stable"
assert must_stable != True or limit_angle_range != True, "do not need balance_stability when must_stable"
result_path = pathlib.Path(result_path)
if not result_path.exists(): result_path.mkdir()
print(str(result_path.absolute()))
choice_aclines = np.arange(api.get_acline_number())
choice_aclines = choice_aclines[np.where(choice_aclines != 0)]
choice_generators = np.arange(api.get_generator_number())
choice_generators = choice_generators[np.where(choice_generators != 3)]
choice_generators = choice_generators[np.where(choice_generators != 4)]
choice_loads = np.arange(api.get_load_number())
choice_loads = choice_loads[np.where(choice_loads != 4)]
total_length = api.get_info_ts_max_step() if cut_length is None else cut_length
t = np.ones([num_total, total_length, 1], dtype=np.float32) * -1
mask = np.zeros([num_total, total_length, 1], dtype=np.float32)
x = np.zeros([num_total, total_length, 0], dtype=np.float32)
z = np.zeros([num_total, total_length, 4], dtype=np.float32)
v = np.zeros([num_total, total_length, 2], dtype=np.float32)
i = np.zeros([num_total, total_length, 2], dtype=np.float32)
event_t = np.zeros([num_total, 3], dtype=np.float32)
z_jump = np.zeros([num_total, 3, 4], dtype = np.float32)
v_jump = np.zeros([num_total, 3, 2], dtype = np.float32)
total_sim = 0
sampled = 0
f_3phase = ratio_3phase * num_total
d_gen = (1 - ratio_3phase) / 2 * num_total
d_load = num_total - f_3phase - d_gen
sampled_stable = 0
sampled_unstable = 0
old_sampled = -1
flg_no_change = 0
while sampled < num_total:
if old_sampled == sampled: flg_no_change += 1
old_sampled = sampled
samples = api.get_power_flow_sample_stepwise(num=num_total, check_voltage=check_voltage, check_slack=check_slack)
for sample in samples:
api.set_power_flow_initiation(sample)
api.cal_power_flow_basic_nr()
api.set_fault_disturbance_clear_all()
# set fault and disturbance
if limit_3phase_short:
if flg_no_change < 3: fd_idx = sampled % 5
else: fd_idx = total_sim % 5
if fd_idx == 0:
acline_no = self.rng.choice(choice_aclines)
loc = self.rng.choice([0, 100])
api.set_fault_disturbance_add_acline(0, loc, 1.0, 1.1, acline_no)
api.set_fault_disturbance_add_acline(1, loc, 1.1, 10., acline_no)
elif fd_idx == 1 or fd_idx == 2:
g_no = self.rng.choice(choice_generators)
api.set_fault_disturbance_add_generator(0, 1.0, 0.5, g_no)
api.set_fault_disturbance_add_generator(0, 5.0, 0.5, g_no)
elif fd_idx == 3 or fd_idx == 4:
l_no = self.rng.choice(choice_loads)
api.set_fault_disturbance_add_load(0, 1.0, 0.5, l_no)
api.set_fault_disturbance_add_load(0, 5.0, 0.5, l_no)
else:
acline_no = self.rng.choice(choice_aclines)
loc = self.rng.choice([0, 100])
api.set_fault_disturbance_add_acline(0, loc, 1.0, 1.2, acline_no)
api.set_fault_disturbance_add_acline(1, loc, 1.2, 10., acline_no)
# temperature sampling, 20-35
temperature = self.rng.random([2]) * 15 + 20.
api.set_generator_all_environment_status([2, 2], temperature.tolist(), [3, 4])
# ts simulation
real_fin_step = api.cal_transient_stability_simulation_ti_sv()
total_sim += 1
# cut length check
if cut_length is not None:
if real_fin_step < cut_length: continue #####################################################################################
if real_fin_step > cut_length: real_fin_step = cut_length
# check e step
e_step = api.get_info_fault_step_sequence()
valid = True
for flt_no in range(len(e_step)):
e_step[flt_no] += 1
if e_step[flt_no] > real_fin_step:
valid = False
break
api.set_info_ts_step_element_state(e_step[flt_no], is_real_step=False)
tmp_re = api.get_bus_ts_cur_step_result(bus_no=30, rt=True)
if np.any(tmp_re != tmp_re):
valid = False
continue
if valid == False:
continue
# get results
result_all = api.get_acsystem_all_ts_result()[0]
if np.any(result_all != result_all): continue
# check stability
fin_step = real_fin_step
delta_diff = result_all[:fin_step, 1]
min_vol = result_all[:fin_step, 4]
min_freq = result_all[:fin_step, 2]
max_freq = result_all[:fin_step, 3]
label = 0
vol_count = 0