ems-core v1.0.0: Standard EMS platform core

Shared backend + frontend for multi-customer EMS deployments.
- 12 enterprise modules: quota, cost, charging, maintenance, analysis, etc.
- 120+ API endpoints, 37 database tables
- Customer config mechanism (CUSTOMER env var + YAML config)
- Collectors: Modbus TCP, MQTT, HTTP API, Sungrow iSolarCloud
- Frontend: React 19 + Ant Design + ECharts + Three.js
- Infrastructure: Redis cache, rate limiting, aggregation engine

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

backend/app/models/prediction.py

@@ -0,0 +1,48 @@
+from sqlalchemy import Column, Integer, String, Float, DateTime, ForeignKey, JSON, Text
+from sqlalchemy.sql import func
+from app.core.database import Base
+
+
+class PredictionTask(Base):
+    """AI预测任务元数据"""
+    __tablename__ = "prediction_tasks"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    device_id = Column(Integer, ForeignKey("devices.id"))
+    prediction_type = Column(String(50), nullable=False)  # pv, load, heatpump, optimization
+    horizon_hours = Column(Integer, default=24)
+    status = Column(String(20), default="pending")  # pending, running, completed, failed
+    parameters = Column(JSON)  # extra config for the prediction run
+    error_message = Column(Text)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    completed_at = Column(DateTime(timezone=True))
+
+
+class PredictionResult(Base):
+    """AI预测结果时序数据"""
+    __tablename__ = "prediction_results"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    task_id = Column(Integer, ForeignKey("prediction_tasks.id"), nullable=False, index=True)
+    timestamp = Column(DateTime(timezone=True), nullable=False, index=True)
+    predicted_value = Column(Float, nullable=False)
+    confidence_lower = Column(Float)
+    confidence_upper = Column(Float)
+    actual_value = Column(Float)  # filled later for accuracy tracking
+    unit = Column(String(20))
+
+
+class OptimizationSchedule(Base):
+    """AI优化调度建议"""
+    __tablename__ = "optimization_schedules"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    device_id = Column(Integer, ForeignKey("devices.id"))
+    date = Column(DateTime(timezone=True), nullable=False, index=True)
+    schedule_data = Column(JSON)  # hourly on/off + setpoints
+    expected_savings_kwh = Column(Float, default=0)
+    expected_savings_yuan = Column(Float, default=0)
+    status = Column(String(20), default="pending")  # pending, approved, executed, rejected
+    approved_by = Column(Integer, ForeignKey("users.id"))
+    approved_at = Column(DateTime(timezone=True))
+    created_at = Column(DateTime(timezone=True), server_default=func.now())