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chenxiaodong 2024-06-25 15:08:50 +08:00
parent 438dbe5bf6
commit f66de9fb54
6 changed files with 5837 additions and 1400 deletions
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AgentPPO/DRL__plots/Evoluation Information.svg
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AgentPPO/DRL__plots/evaluation_information.svg Normal file
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AgentPPO/DRL__plots/optimization_information.svg
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4
PPO.py
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@ -331,8 +331,8 @@ if __name__ == '__main__':
buffer = list() buffer = list()
'''init training parameters''' '''init training parameters'''
num_episode = args.num_episode num_episode = args.num_episode
args.train = False # args.train = False
args.save_network = False # args.save_network = False
# args.test_network = False # args.test_network = False
# args.save_test_data = False # args.save_test_data = False
# args.compare_with_gurobi = False # args.compare_with_gurobi = False

11
environment.py
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@ -1,7 +1,7 @@
import gym import gym
import numpy as np import numpy as np
import pandas as pd import pandas as pd
from gym import spaces
from module import * from module import *
from parameters import * from parameters import *
from data_manager import * from data_manager import *
@ -39,8 +39,8 @@ class ESSEnv(gym.Env):
self.solar = Solar(self.solar_parameters) self.solar = Solar(self.solar_parameters)
self.wind = Wind(self.wind_parameters) self.wind = Wind(self.wind_parameters)
self.action_space = spaces.Box(low=-1, high=1, shape=(5,), dtype=np.float32) # 已增加调节电压动作 self.action_space = gym.spaces.Box(low=-1, high=1, shape=(5,), dtype=np.float32) # 已增加调节电压动作
self.state_space = spaces.Box(low=-np.inf, high=np.inf, shape=(10,), dtype=np.float32) self.state_space = gym.spaces.Box(low=0, high=1, shape=(10,), dtype=np.float32)
def reset(self, *args): def reset(self, *args):
self.month = np.random.randint(1, 13) # choose 12 month self.month = np.random.randint(1, 13) # choose 12 month
@ -69,7 +69,7 @@ class ESSEnv(gym.Env):
temperature = self.data_manager.get_temperature_data(self.month, self.day, self.current_time) temperature = self.data_manager.get_temperature_data(self.month, self.day, self.current_time)
irradiance = self.data_manager.get_irradiance_data(self.month, self.day, self.current_time) irradiance = self.data_manager.get_irradiance_data(self.month, self.day, self.current_time)
wind_speed = self.data_manager.get_wind_data(self.month, self.day, self.current_time) wind_speed = self.data_manager.get_wind_data(self.month, self.day, self.current_time)
# print('house_load:', house_load)
pv_generation = self.solar.step(temperature, irradiance) pv_generation = self.solar.step(temperature, irradiance)
wd_generation = self.wind.step(wind_speed) wd_generation = self.wind.step(wind_speed)
generation = pv_generation + wd_generation generation = pv_generation + wd_generation
@ -129,10 +129,9 @@ class ESSEnv(gym.Env):
solar_cost = self.solar.get_cost(self.solar.current_power) solar_cost = self.solar.get_cost(self.solar.current_power)
wind_cost = self.wind.gen_cost(self.wind.current_power) wind_cost = self.wind.gen_cost(self.wind.current_power)
reward -= (battery_cost + dg1_cost + dg2_cost + dg3_cost + solar_cost + wind_cost + excess_penalty +
deficient_penalty - sell_benefit + buy_cost) / 1e3
self.operation_cost = (battery_cost + dg1_cost + dg2_cost + dg3_cost + solar_cost + wind_cost + excess_penalty + self.operation_cost = (battery_cost + dg1_cost + dg2_cost + dg3_cost + solar_cost + wind_cost + excess_penalty +
deficient_penalty - sell_benefit + buy_cost) deficient_penalty - sell_benefit + buy_cost)
reward -= self.operation_cost / 1e3
self.unbalance = unbalance self.unbalance = unbalance
self.real_unbalance = self.shedding + self.excess self.real_unbalance = self.shedding + self.excess
final_step_outputs = [self.dg1.current_output, self.dg2.current_output, self.dg3.current_output, final_step_outputs = [self.dg1.current_output, self.dg2.current_output, self.dg3.current_output,

2
plotDRL.py
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@ -134,7 +134,7 @@ def plot_evaluation_information(datasource, directory):
axs[1, 1].set_ylabel('Costs') axs[1, 1].set_ylabel('Costs')
axs[1, 1].bar(eval_data['time_step'], eval_data['operation_cost']) axs[1, 1].bar(eval_data['time_step'], eval_data['operation_cost'])
fig.savefig(f"{directory}/evaluation_information.svg", format='svg', dpi=600, bbox_inches='tight') fig.savefig(f"{directory}/evaluation_information.svg", format='svg', dpi=600, bbox_inches='tight')
print('evaluation figure have been plot and saved') print('evaluation figure have been ploted and saved')
def make_dir(directory, feature_change): def make_dir(directory, feature_change):