delete some cache file

generatedata.py

@@ -1,56 +0,0 @@
-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.")

generatepriceschedule.py

@@ -1,24 +0,0 @@
-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)