def __init__(self,server):

self.server=server

self.all_brokers=[]

def clear_old_genes(self):

shutil.rmtree("C:/Users/lomiag/PycharmProjects/Energy_Broker/Genetic_Library/")

os.mkdir("C:/Users/lomiag/PycharmProjects/Energy_Broker/Genetic_Library/")

shutil.copy("C:/Users/lomiag/PycharmProjects/Energy_Broker/Genetic_Code_ground_zero.csv",

"C:/Users/lomiag/PycharmProjects/Energy_Broker/Genetic_Library/Genetic_Code_ground_zero.csv")

def move_new_to_old(self):

# self.clear_old_genes()

new_gen="C:/Users/lomiag/PycharmProjects/Energy_Broker/New_Generation/"

old_gen="C:/Users/lomiag/PycharmProjects/Energy_Broker/Genetic_Library/"

new_life=os.listdir(new_gen)

for life in new_life:

shutil.move(new_gen+life, old_gen+life)

def write_best_genes(self,best):

for broker in best:

self.save_current_gen(randomString(7),self.all_brokers[broker])

def save_current_gen(self,index,brk):

brk.genetic_table.to_csv("C:/Users/lomiag/PycharmProjects/Energy_Broker/New_Generation/Genetic_Code_{}.csv".format(index))

def evolve(self,generations):

for g in range(generations):

# current_generation=os.listdir("C:/Users/lomiag/PycharmProjects/Energy_Broker/Genetic_Library")

self.all_brokers=self.server.run()

bst=self.find_best_broker()

print("Max Cash: ",self.all_brokers[bst[len(bst)-1]].cash,"Max Power: ",self.all_brokers[bst[len(bst)-1]].power)

print(self.all_brokers[bst[len(bst)-1]].genetic_table)

self.write_best_genes(bst)

self.clear_old_genes()

self.move_new_to_old()

self.server=Server()

def find_best_broker(self):

broker_dict={}

five_highest=[]

for broker in self.all_brokers:

broker_dict[broker.cash]=broker.idx

for i in sorted(broker_dict.keys()):

five_highest.append(broker_dict[i])

def __init__(self,gen_code="Genetic_Code_ground_zero"):

global brk_id

## Default tariff

self.DT = self.get_default_tariff()

## List of Brokers participating

## List of Customers

## List of published Tariffs

## You need to initialize a Broker here (change the name in the

## imports at the top to reflect your broker's name), and then

## put it in the list self.brokers.

self.brokers = []

NUMBER_OF_BROKERS=10

self.brokers=self.create_brokers(15)

self.customers = [Customer() for i in range(100)]

self.tariffs = [self.DT]

# self.run()

def create_brokers(self,children_num):

path="C:/Users/lomiag/PycharmProjects/Energy_Broker/"

parents=os.listdir(path+"Genetic_Library")

brks=[Broker(1)]

brk_id=1

for parent in range(len(parents)):

for child in range(children_num):

br=Broker(brk_id,parents[parent][:-4])

brks.append(br)

mutation_table=br.create_mutation_table()

random_gene=random.choice(brks).genetic_table

# print(random.choice(brks).genetic_table)

mutaion_options = [br.apply_mutation_multiplication(mutation_table),

br.apply_mutation_combine(random_gene),

br.apply_mutation_reverse()]

br.genetic_table=random.choice(mutaion_options)

brks.append(br)

brk_id += 1

return brks

def expand_broker(self,brk_list):

for brk in self.brokers:

brk_list.append(brk)

return brk_list

def run(self):

NUMSTEPS = 24

## Gather bootstrap data and send it off to brokers

usage_data, other_data = self.read_initial_data()

for b in self.brokers:

b.get_initial_data(usage_data, other_data)

## Run simulation for a number of steps

for step in range(NUMSTEPS):

## Let brokers post asks in the wholesale market

asks = []

asks_by_broker = dict()

for b in self.brokers:

a = b.post_asks(step)

asks.extend(a)

asks_by_broker[b.idx] = a

## Get bids from producers

## Clear market

## Distribute energy to brokers

price, quantity = self.clear_market(asks, self.get_bids())

for b in self.brokers:

for ask in asks_by_broker[b.idx]:

if ask[0] >= price:

b.power += ask[1]

usage = []

for c in self.customers:

usage.append(c.get_use_at_time(step))

## Get total demand for each broker

## Pay brokers based on their subscriptions

## Assess each broker's surplus or deficit

## Pay/charge brokers accordingly

for b in self.brokers:

b.gain_revenue(self.customers, usage)

b.adjust_cash(b.get_energy_imbalance(usage) * price)

b.power = 0

## Let customers decide between tariffs and subscribe

for c in range(len(self.customers)):

t = self.customers[c].choose_tariff(self.tariffs)

for b in self.brokers:

b.customers = [i for i in range(len(self.customers)) if \

self.customers[i].tariff.publisher == b.idx]

## newdata is a dictionary to hold updated information from the current

## time step. Total is the total energy demand from all 100 customers,

## Cleared Price is the wholesale clearing price, Cleared Quantity is

## the wholesale market clearing quantity, and Customer Usage is a list

## in which element i is customer i's energy usage for the current time

## step.

newdata = {'Total': sum(usage),

'Cleared Price': price,

'Cleared Quantity': quantity,

'Customer Usage': usage,

'Tariffs': self.tariffs}

for b in self.brokers:

b.receive_message(newdata)

for t in self.tariffs:

if t.publisher != 0: t.dec_time()

self.tariffs = [t for t in self.tariffs if t.duration > 0]

print(newdata)

## Let brokers post new tariffs

for b in self.brokers:

self.tariffs.extend(b.post_tariffs(step))

return self.brokers

def clear_market(self, asks, bids):

bids.sort()

asks.sort(reverse=True)

total_asked = 0

total_bidded = 0

i, j = 0, 0

while True:

if total_asked < total_bidded:

total_asked += asks[i][1]

i += 1

elif total_bidded < total_asked:

total_bidded += bids[j][1]

j += 1

else:

total_asked += asks[i][1]

total_bidded += bids[j][1]

i += 1

j += 1

try:

if asks[i][0] < bids[j][0]:

price = bids[j - 1][0]

quantity = total_asked

break

except:

if i == len(asks):

i -= 1

if j == len(bids):

j -= 1

price = (abs(asks[i][0] + bids[j][0])) / 2

quantity = total_asked

return price, quantity

def read_initial_data(self):

customer_usage = dict()

other_data = dict()

f = open('CustomerNums.csv', 'r')

raw = [i[:-1].split(',')[1:] for i in f.readlines()[1:]]

for i in range(1, len(raw) + 1):

customer_usage[i] = [float(dat) for dat in raw[i - 1]]

f.close()

f = open('OtherData.csv')

raw = [i[:-1].split(',')[1:] for i in f.readlines()[1:]]

other_data['Cleared Price'] = [float(dat) for dat in raw[0]]

other_data['Cleared Quantity'] = [float(dat) for dat in raw[1]]

other_data['Difference'] = [float(dat) for dat in raw[2]]

other_data['Total Demand'] = [float(dat) for dat in raw[3]]

return customer_usage, other_data

def get_bids(self):

f = open('GenCos.csv', 'r')

data = [i[:-1].split(',') for i in f.readlines()[1:]]

f.close()

bids = []

## Get a bid from each plant, keep their capacity as well

for d in data:

bids.append((get_random_bid(float(d[5])), int(d[4])))

return bids

def get_default_tariff(self):

return Tariff(0, price=1000, duration=1, exitfee=500)

def expand_brokers(self,broker_list):

for brk in self.brokers:

broker_list.apend(brk)