def init_global_vraibles(parameter_row_from_matrix):
#"string is the path to the file in which the experiment is defined"
g.random_change = parameter_row_from_matrix[0]
g.copy_best_change = parameter_row_from_matrix[1]
g.learn_change = parameter_row_from_matrix[2]
g.copy_al = parameter_row_from_matrix[3]
g.institutional_success_rate = parameter_row_from_matrix[4]
if int(parameter_row_from_matrix[5]) == 0:
g.majority_vote = False
if int(parameter_row_from_matrix[5]) == 1:
g.majority_vote = True
#reset some of the values to the original
g.institutional_rule = zeros(6)
g.agents = dict()
g.time = 0
g.testcase = cases(g.time)
g.average_arrival_time = 72
g.average_laeving_time = 32
g.sd_average = 1
g.average_battery_drain = 10
g.sd_average_battery_drain = 2
g.average_soc = 20
g.sd_average_soc = 2
g.soc_max_gloabl = 40
def test_do_interaction(self):
time = 32
testcase = cases(time)
testcase.set_base(time)
for k in range(2, 26):
agents[k] = agent(30, k, time)
agents[k].Voltage = 0.98
agents[k].set_rule(array([1, 0.97, 20, 5, 2, 0]))
for i in agents:
agents[i].do_interaction(testcase)
for i in agents:
self.assertEqual(agents[i].time, 33, "do interaction time test")
load_vector = array([
0, -0.002, -0.002, -0.002, -0.002, -0.002, -0.002, -0.002, -0.002,
-0.002, -0.002, -0.002, -0.002, -0.002, -0.002, -0.002, -0.002,
-0.002, -0.002, -0.002, -0.002, -0.002, -0.002, -0.002, -0.002
])
for i in range(0, 25):
self.assertEqual(testcase.dispatch_load[i], load_vector[i],
"do interaction dispatchabel load test")
def run_model(str2_out, run_id):
time_experiment = 96 * 6 * 30
time = 0
soc = 20
testcase = cases(time)
soc_data = zeros((time_experiment, 24))
time_data = zeros((time_experiment, 1))
run_ids = ones((time_experiment, 1)) * run_id
agents = dict()
for k in range(2, 26):
#soc = random.normal(average_soc, sd_average_soc, 1)
agents[k] = agent(soc, k, time)
for i in agents:
soc_data[0, agents[i].node - 2] = agents[i].get_soc()
while (time < time_experiment - 1):
time_data[time, 0] = time
time += 1
testcase.set_base(time)
for i in agents:
if agents[i].at_home:
agents[i].do_interaction(testcase)
else:
if time % 96 == agents[i].arrival_time:
agents[i].arrive_at_home()
testcase.adapt_main_generator()
output = testcase.get_output()
for i in agents:
if agents[i].at_home:
agents[i].get_feedback(output)
if time % 96 == agents[i].leaving_time:
agents[i].at_home = False
for i in agents:
soc_data[time, agents[i].node - 2] = agents[i].get_soc()
time_data[time, 0] = time
output_values_to_csv = concatenate((soc_data, time_data, run_ids), axis=1)
with open(str2_out, 'a') as csvfile:
schreiber = csv.writer(csvfile, delimiter=',', quotechar='"')
for row in output_values_to_csv:
schreiber.writerow(row)
def test_get_feedback(self):
time = 32
testcase = cases(time)
testcase.ppc["bus"][:,
12] = 0.90 #basically drop the voltage restriction
testcase.set_base(time)
for k in range(2, 26):
agents[k] = agent(30, k, time)
agents[k].Voltage = 0.98
agents[k].set_rule(array([1, 0.99, 20, 4, 2, 0]))
for i in agents:
agents[i].do_interaction(testcase)
testcase.adapt_main_generator()
output = testcase.get_output()
for i in agents:
agents[i].get_feedback(output)
for i in agents:
self.assertEqual(agents[i].SOC, 31, "test get feedback check SOC")
Created on Apr 25, 2015
@author: saur
'''
from cases_second import cases
from pypower.api import ppoption, runopf, runpf
from numpy import linspace
from scipy import array,ones , zeros
import matplotlib.pyplot as plt
from scipy.stats import linregress
time = 72
test_object = cases(time)
#test_object.set_base(time)
result , y = runpf(test_object.ppc,test_object.ppopt)
power = linspace(0,25,num=25)
slopes = zeros(6)
power_data_matrix = zeros((25,6))
voltage_data_matrix = zeros((25,6))
for index in range(2,8):
count = 0
voltages = zeros(25)
powers = zeros(25)
for p in power:
test_object = cases(time)
test_object.ppc["gen"][index-1,1] = - p /1000.0
result , y = runpf(test_object.ppc,test_object.ppopt)
global average_battery_drain global sd_average_battery_drain global soc_max_gloabl global random_change global copy_best_change global learn_change global agents global institutional_success_rate global majority_vote global copy_al global run_id institutional_rule = zeros(6) agents = dict() time = 0 testcase = cases(time) average_arrival_time = 72 average_laeving_time = 32 sd_average = 1 average_battery_drain = 10 sd_average_battery_drain = 2 average_soc = 20 sd_average_soc = 2 soc_max_gloabl = 40 #steps_threshhold = 96 action_options = [0,1,2,3,4,5] t_end_options = linspace(1,96,96) t_begin_options = t_end_options soc_threshold_options = linspace(0, soc_max_gloabl, 9) voltage_options = linspace(0.96,1,5)
def test_pypower_constrained(load_difference):
correct = True
for k in range(0, 4):
for i in range(0, 6):
if (load_difference[k, i] > 0) & (load_difference[k, i] < 1):
if i != 5:
for z in range(i + 1, 6):
if (load_difference[k, z] != 1):
correct = False
return correct
for i in range(0, number_of_runs):
testcase = cases(time)
for k in range(0, 24):
load_vector[k, 0] = random.choice(actions)
testcase.set_base(time)
for k in range(2, 26):
testcase.set_power(k, load_vector[k - 2, 0])
testcase.adapt_main_generator()
output = testcase.get_output()
constraint_matrix[0, i] = output["bus"][6, 7]
constraint_matrix[1, i] = output["bus"][12, 7]
constraint_matrix[2, i] = output["bus"][18, 7]
constraint_matrix[3, i] = output["bus"][24, 7]
difference_vector = -(testcase.ppc["gen"][
1:25, 1] - testcase.dispatch_load[1:25]) / testcase.dispatch_load[1:25]