delete some cache file

This commit is contained in:
mhrooz 2024-05-04 10:02:08 +02:00
parent 651833b521
commit 1679831dbd
6 changed files with 0 additions and 80 deletions

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import pandas as pd
import numpy as np
# 设置随机种子以重现结果
np.random.seed(43)
def simulate_sunlight(hour, month):
# 假设最大日照强度在正午,根据月份调整最大日照强度
max_intensity = 1.0 # 夏季最大日照强度
if month in [12, 1, 2]: # 冬季
max_intensity = 0.6
elif month in [3, 4, 10, 11]: # 春秋
max_intensity = 0.8
# 计算日照强度,模拟早晚日照弱,中午日照强
intensity = max_intensity * np.sin(np.pi * (hour - 6) / 12)**2 if 6 <= hour <= 18 else 0
return intensity
def simulate_factory_demand(hour, day_of_week):
# 周末工厂需求可能减少
if day_of_week in [5, 6]: # 周六和周日
base_demand = 3000
else:
base_demand = 6000
# 日常波动
if 8 <= hour <= 20:
return base_demand + np.random.randint(100, 200) # 白天需求量大
else:
return base_demand - np.random.randint(0, 100) # 夜间需求量小
def generate_data(days=10):
records = []
month_demand = 0
for day in range(days):
month = (day % 365) // 30 + 1
day_of_week = day % 7
day_demand = 0
for hour in range(24):
for minute in [0, 10, 20, 30, 40, 50]:
time = f'{hour:02d}:{minute:02d}'
sunlight = simulate_sunlight(hour, month)
demand = simulate_factory_demand(hour, day_of_week)
day_demand+=demand
records.append({'time': time, 'sunlight': sunlight, 'demand': demand})
print(f"day:{day}, day_demand: {day_demand}")
month_demand += day_demand
if day%30 == 0:
print(f"month:{month}, month_demand:{month_demand}")
month_demand = 0
return pd.DataFrame(records)
# 生成数据
data = generate_data(365) # 模拟一年的数据
data.to_csv('simulation_data.csv', index=False)
print("Data generated and saved to simulation_data.csv.")

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import pandas as pd
import numpy as np
def generate_price_schedule():
records = []
# 假设一天分为三个时段:谷时、平时、峰时
times = [('00:00', '06:00', 0.25),
('06:00', '18:00', 0.3),
('18:00', '24:00', 0.35)]
# 随机调整每天的电价以增加现实性
for time_start, time_end, base_price in times:
# 随机浮动5%以内
fluctuation = np.random.uniform(-0.005, 0.005)
price = round(base_price + fluctuation, 3)
records.append({'time_start': time_start, 'time_end': time_end, 'price': price})
return pd.DataFrame(records)
# 生成电价计划
price_schedule = generate_price_schedule()
price_schedule.to_csv('price_schedule.csv', index=False)
print("Price schedule generated and saved to price_schedule.csv.")
print(price_schedule)

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