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