Merge commit '026c837b919ab4380e8a6e6c052364bbf9bbe8a3' as 'core'

core/backend/app/models/energy.py

@@ -0,0 +1,52 @@
+from sqlalchemy import Column, Integer, String, Float, DateTime, ForeignKey, JSON
+from sqlalchemy.sql import func
+from app.core.database import Base
+
+
+class EnergyCategory(Base):
+    """能耗分项类别"""
+    __tablename__ = "energy_categories"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    name = Column(String(100), nullable=False)  # HVAC, 照明, 动力, 特殊
+    code = Column(String(50), unique=True, nullable=False)  # hvac, lighting, power, special
+    parent_id = Column(Integer, ForeignKey("energy_categories.id"))
+    sort_order = Column(Integer, default=0)
+    icon = Column(String(100))
+    color = Column(String(20))  # hex color for charts
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+
+
+class EnergyData(Base):
+    """时序能耗采集数据 - 使用TimescaleDB hypertable"""
+    __tablename__ = "energy_data"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    device_id = Column(Integer, ForeignKey("devices.id"), nullable=False, index=True)
+    timestamp = Column(DateTime(timezone=True), nullable=False, index=True)
+    data_type = Column(String(50), nullable=False)  # power, energy, temperature, flow, etc.
+    value = Column(Float, nullable=False)
+    unit = Column(String(20))  # kW, kWh, ℃, m³/h, etc.
+    quality = Column(Integer, default=0)  # 0=good, 1=interpolated, 2=suspect
+    raw_data = Column(JSON)  # 原始完整数据包
+
+
+class EnergyDailySummary(Base):
+    """每日能耗汇总"""
+    __tablename__ = "energy_daily_summary"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    device_id = Column(Integer, ForeignKey("devices.id"), nullable=False, index=True)
+    date = Column(DateTime(timezone=True), nullable=False, index=True)
+    energy_type = Column(String(50), nullable=False)  # electricity, heat, water, gas
+    total_consumption = Column(Float, default=0)  # 总消耗
+    total_generation = Column(Float, default=0)  # 总产出
+    peak_power = Column(Float)  # 最大功率
+    min_power = Column(Float)  # 最小功率
+    avg_power = Column(Float)  # 平均功率
+    operating_hours = Column(Float)  # 运行小时数
+    avg_cop = Column(Float)  # 平均COP (热泵)
+    avg_temperature = Column(Float)  # 平均温度
+    cost = Column(Float)  # 费用
+    carbon_emission = Column(Float)  # 碳排放 kgCO2
+    created_at = Column(DateTime(timezone=True), server_default=func.now())