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>
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Du Wenbo
261
backend/app/services/cost_calculator.py
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261
backend/app/services/cost_calculator.py
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from datetime import datetime, timedelta, timezone
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy import select, func, and_
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from app.models.pricing import ElectricityPricing, PricingPeriod
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from app.models.energy import EnergyData, EnergyDailySummary
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from app.models.device import Device
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async def get_active_pricing(db: AsyncSession, energy_type: str = "electricity", date: datetime | None = None):
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"""获取当前生效的电价配置"""
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q = select(ElectricityPricing).where(
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and_(
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ElectricityPricing.energy_type == energy_type,
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ElectricityPricing.is_active == True,
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)
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)
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if date:
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q = q.where(
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and_(
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(ElectricityPricing.effective_from == None) | (ElectricityPricing.effective_from <= date),
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(ElectricityPricing.effective_to == None) | (ElectricityPricing.effective_to >= date),
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)
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)
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q = q.order_by(ElectricityPricing.created_at.desc()).limit(1)
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result = await db.execute(q)
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return result.scalar_one_or_none()
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async def get_pricing_periods(db: AsyncSession, pricing_id: int, month: int | None = None):
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"""获取电价时段配置"""
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q = select(PricingPeriod).where(PricingPeriod.pricing_id == pricing_id)
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result = await db.execute(q)
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periods = result.scalars().all()
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if month is not None:
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periods = [p for p in periods if p.applicable_months is None or month in p.applicable_months]
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return periods
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def get_period_for_hour(periods: list, hour: int) -> PricingPeriod | None:
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"""根据小时确定所属时段"""
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hour_str = f"{hour:02d}:00"
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for p in periods:
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start = p.start_time
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end = p.end_time
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if start <= end:
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if start <= hour_str < end:
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return p
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else: # crosses midnight, e.g. 23:00 - 07:00
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if hour_str >= start or hour_str < end:
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return p
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return periods[0] if periods else None
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async def calculate_daily_cost(db: AsyncSession, date: datetime, device_id: int | None = None):
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"""计算某天的用电费用"""
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pricing = await get_active_pricing(db, "electricity", date)
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if not pricing:
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return 0.0
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if pricing.pricing_type == "flat":
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# 平价: 直接查日汇总
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q = select(func.sum(EnergyDailySummary.total_consumption)).where(
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and_(
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EnergyDailySummary.date >= date.replace(hour=0, minute=0, second=0),
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EnergyDailySummary.date < date.replace(hour=0, minute=0, second=0) + timedelta(days=1),
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EnergyDailySummary.energy_type == "electricity",
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)
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)
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if device_id:
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q = q.where(EnergyDailySummary.device_id == device_id)
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result = await db.execute(q)
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total_energy = result.scalar() or 0.0
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periods = await get_pricing_periods(db, pricing.id)
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flat_price = periods[0].price_per_unit if periods else 0.0
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cost = total_energy * flat_price
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else:
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# TOU分时: 按小时计算
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periods = await get_pricing_periods(db, pricing.id, month=date.month)
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if not periods:
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return 0.0
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cost = 0.0
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day_start = date.replace(hour=0, minute=0, second=0, microsecond=0)
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for hour in range(24):
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hour_start = day_start + timedelta(hours=hour)
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hour_end = hour_start + timedelta(hours=1)
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q = select(func.sum(EnergyData.value)).where(
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and_(
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EnergyData.timestamp >= hour_start,
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EnergyData.timestamp < hour_end,
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EnergyData.data_type == "energy",
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)
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)
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if device_id:
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q = q.where(EnergyData.device_id == device_id)
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result = await db.execute(q)
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hour_energy = result.scalar() or 0.0
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period = get_period_for_hour(periods, hour)
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if period:
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cost += hour_energy * period.price_per_unit
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# Update daily summary cost
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q = select(EnergyDailySummary).where(
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and_(
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EnergyDailySummary.date >= date.replace(hour=0, minute=0, second=0),
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EnergyDailySummary.date < date.replace(hour=0, minute=0, second=0) + timedelta(days=1),
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EnergyDailySummary.energy_type == "electricity",
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)
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)
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if device_id:
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q = q.where(EnergyDailySummary.device_id == device_id)
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result = await db.execute(q)
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for summary in result.scalars().all():
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summary.cost = cost
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return round(cost, 2)
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async def get_cost_summary(
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db: AsyncSession, start_date: datetime, end_date: datetime,
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group_by: str = "day", energy_type: str = "electricity",
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):
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"""获取费用汇总"""
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q = select(
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EnergyDailySummary.date,
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func.sum(EnergyDailySummary.total_consumption).label("consumption"),
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func.sum(EnergyDailySummary.cost).label("cost"),
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).where(
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and_(
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EnergyDailySummary.date >= start_date,
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EnergyDailySummary.date <= end_date,
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EnergyDailySummary.energy_type == energy_type,
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)
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)
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if group_by == "device":
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q = select(
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EnergyDailySummary.device_id,
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Device.name.label("device_name"),
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func.sum(EnergyDailySummary.total_consumption).label("consumption"),
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func.sum(EnergyDailySummary.cost).label("cost"),
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).join(Device, EnergyDailySummary.device_id == Device.id, isouter=True).where(
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and_(
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EnergyDailySummary.date >= start_date,
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EnergyDailySummary.date <= end_date,
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EnergyDailySummary.energy_type == energy_type,
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)
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).group_by(EnergyDailySummary.device_id, Device.name)
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result = await db.execute(q)
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return [
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{"device_id": r[0], "device_name": r[1] or f"Device#{r[0]}",
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"consumption": round(r[2] or 0, 2), "cost": round(r[3] or 0, 2)}
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for r in result.all()
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]
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elif group_by == "month":
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from app.core.config import get_settings
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settings = get_settings()
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if settings.is_sqlite:
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group_expr = func.strftime('%Y-%m', EnergyDailySummary.date).label('period')
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else:
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group_expr = func.to_char(EnergyDailySummary.date, 'YYYY-MM').label('period')
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q = select(
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group_expr,
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func.sum(EnergyDailySummary.total_consumption).label("consumption"),
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func.sum(EnergyDailySummary.cost).label("cost"),
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).where(
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and_(
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EnergyDailySummary.date >= start_date,
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EnergyDailySummary.date <= end_date,
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EnergyDailySummary.energy_type == energy_type,
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)
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).group_by(group_expr).order_by(group_expr)
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result = await db.execute(q)
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return [
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{"period": str(r[0]), "consumption": round(r[1] or 0, 2), "cost": round(r[2] or 0, 2)}
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for r in result.all()
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]
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else: # day
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q = q.group_by(EnergyDailySummary.date).order_by(EnergyDailySummary.date)
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result = await db.execute(q)
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return [
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{"date": str(r[0]), "consumption": round(r[1] or 0, 2), "cost": round(r[2] or 0, 2)}
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for r in result.all()
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]
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async def get_cost_breakdown(db: AsyncSession, start_date: datetime, end_date: datetime, energy_type: str = "electricity"):
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"""获取峰谷平费用分布"""
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pricing = await get_active_pricing(db, energy_type, start_date)
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if not pricing:
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return {"periods": [], "total_cost": 0, "total_consumption": 0}
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periods = await get_pricing_periods(db, pricing.id)
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if not periods:
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return {"periods": [], "total_cost": 0, "total_consumption": 0}
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# For each period, calculate the total energy consumption in those hours
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breakdown = []
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total_cost = 0.0
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total_consumption = 0.0
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for period in periods:
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start_hour = int(period.start_time.split(":")[0])
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end_hour = int(period.end_time.split(":")[0])
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if start_hour < end_hour:
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hours = list(range(start_hour, end_hour))
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else: # crosses midnight
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hours = list(range(start_hour, 24)) + list(range(0, end_hour))
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period_energy = 0.0
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current = start_date.replace(hour=0, minute=0, second=0, microsecond=0)
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end = end_date.replace(hour=23, minute=59, second=59, microsecond=0)
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# Sum energy for all matching hours in date range using daily summary approximation
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q = select(func.sum(EnergyDailySummary.total_consumption)).where(
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and_(
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EnergyDailySummary.date >= start_date,
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EnergyDailySummary.date <= end_date,
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EnergyDailySummary.energy_type == energy_type,
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)
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)
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result = await db.execute(q)
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total_daily = result.scalar() or 0.0
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# Approximate proportion based on hours in period vs 24h
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proportion = len(hours) / 24.0
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period_energy = total_daily * proportion
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period_cost = period_energy * period.price_per_unit
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total_cost += period_cost
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total_consumption += period_energy
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period_name_map = {
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"peak": "尖峰", "sharp": "尖峰",
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"high": "高峰", "shoulder": "高峰",
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"flat": "平段",
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"valley": "低谷", "off_peak": "低谷",
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}
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breakdown.append({
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"period_name": period.period_name,
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"period_label": period_name_map.get(period.period_name, period.period_name),
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"start_time": period.start_time,
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"end_time": period.end_time,
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"price_per_unit": period.price_per_unit,
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"consumption": round(period_energy, 2),
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"cost": round(period_cost, 2),
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"proportion": round(proportion * 100, 1),
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})
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return {
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"periods": breakdown,
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"total_cost": round(total_cost, 2),
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"total_consumption": round(total_consumption, 2),
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"pricing_name": pricing.name,
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"pricing_type": pricing.pricing_type,
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}
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