Merge commit '026c837b919ab4380e8a6e6c052364bbf9bbe8a3' as 'core'

core/scripts/backfill_data.py

@@ -0,0 +1,399 @@
+"""回填历史模拟能耗数据 - 过去30天逐小时数据，含碳排放记录
+
+Uses the shared weather_model for physics-based solar, temperature, and load
+generation.  Deterministic seed (42) ensures reproducible output across runs.
+"""
+import asyncio
+import math
+import os
+import random
+import sys
+from datetime import datetime, timedelta, timezone
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "backend"))
+
+DATABASE_URL = os.environ.get(
+    "DATABASE_URL",
+    "postgresql+asyncpg://tianpu:tianpu2026@localhost:5432/tianpu_ems",
+)
+
+from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker, AsyncSession
+from sqlalchemy import text, select
+
+from app.services.weather_model import (
+    set_seed, reset_cloud_model,
+    pv_power, pv_electrical_at, get_pv_orientation,
+    heat_pump_data, building_load, indoor_sensor,
+    heat_meter_data, outdoor_temperature, outdoor_humidity,
+    get_hvac_mode,
+)
+from app.models.device import Device
+
+# ---------------------------------------------------------------------------
+# Device definitions — will be populated from DB at runtime
+# ---------------------------------------------------------------------------
+PV_IDS = []
+PV_CODES = ["INV-01", "INV-02", "INV-03"]
+HP_IDS = []
+HP_CODES = ["HP-01", "HP-02", "HP-03", "HP-04"]
+METER_IDS = []
+METER_CODES = ["METER-GRID", "METER-PV", "METER-HP", "METER-PUMP"]
+HEAT_METER_ID = None
+SENSOR_IDS = []
+SENSOR_CODES = ["TH-01", "TH-02", "TH-03", "TH-04", "TH-05"]
+
+
+async def _load_device_ids(session: AsyncSession):
+    """Load actual device IDs from DB by code."""
+    global PV_IDS, HP_IDS, METER_IDS, HEAT_METER_ID, SENSOR_IDS
+    result = await session.execute(select(Device.id, Device.code).order_by(Device.id))
+    code_to_id = {row[1]: row[0] for row in result.all()}
+
+    PV_IDS = [code_to_id[c] for c in PV_CODES if c in code_to_id]
+    HP_IDS = [code_to_id[c] for c in HP_CODES if c in code_to_id]
+    METER_IDS = [code_to_id[c] for c in METER_CODES if c in code_to_id]
+    HEAT_METER_ID = code_to_id.get("HM-01")
+    SENSOR_IDS = [code_to_id[c] for c in SENSOR_CODES if c in code_to_id]
+    print(f"  Loaded device IDs: PV={PV_IDS}, HP={HP_IDS}, Meters={METER_IDS}, HeatMeter={HEAT_METER_ID}, Sensors={SENSOR_IDS}")
+
+EMISSION_FACTOR = 0.8843  # kgCO2/kWh - North China grid
+
+DAYS = 30
+HOURS_PER_DAY = 24
+TOTAL_HOURS = DAYS * HOURS_PER_DAY
+
+
+# ---------------------------------------------------------------------------
+# Main backfill
+# ---------------------------------------------------------------------------
+
+async def backfill():
+    # Set deterministic seed for reproducibility
+    set_seed(42)
+
+    engine = create_async_engine(DATABASE_URL, echo=False, pool_size=5)
+    session_factory = async_sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
+
+    # Load actual device IDs from DB
+    async with session_factory() as session:
+        await _load_device_ids(session)
+
+    now = datetime.now(timezone.utc).replace(minute=0, second=0, microsecond=0)
+    start = now - timedelta(days=DAYS)
+
+    print(f"Backfill range: {start.isoformat()} -> {now.isoformat()}")
+    print(f"Total hours: {TOTAL_HOURS}")
+
+    # ---- Collect rows ----
+    energy_rows = []
+    carbon_rows = []
+    daily_buckets: dict[int, dict[str, dict]] = {}
+
+    all_power_ids = PV_IDS + HP_IDS + METER_IDS
+    for did in all_power_ids:
+        daily_buckets[did] = {}
+
+    print("Generating hourly energy_data rows (realistic models) ...")
+    for h_offset in range(TOTAL_HOURS):
+        ts = start + timedelta(hours=h_offset)
+        beijing_dt = ts + timedelta(hours=8)
+        date_str = beijing_dt.strftime("%Y-%m-%d")
+
+        # Reset cloud model each day for variety
+        if h_offset % 24 == 0:
+            reset_cloud_model()
+            # Re-seed per day for reproducibility but day-to-day variation
+            set_seed(42 + h_offset // 24)
+
+        # --- PV inverters ---
+        for i, did in enumerate(PV_IDS):
+            code = PV_CODES[i]
+            orientation = get_pv_orientation(code)
+            val = pv_power(ts, rated_power=110.0, orientation=orientation,
+                           device_code=code)
+            val = round(val, 2)
+
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "power", "value": val, "unit": "kW", "quality": 0,
+            })
+
+            # Also generate electrical details for richer data
+            elec = pv_electrical_at(val, ts, rated_power=110.0)
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "dc_voltage", "value": elec["dc_voltage"], "unit": "V", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "ac_voltage", "value": elec["ac_voltage"], "unit": "V", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "temperature", "value": elec["temperature"], "unit": "℃", "quality": 0,
+            })
+
+            daily_buckets[did].setdefault(date_str, {"values": [], "cops": []})
+            daily_buckets[did][date_str]["values"].append(val)
+
+        # --- Heat pumps ---
+        hp_total_power = 0.0
+        hp_cop_sum = 0.0
+        hp_count = 0
+        for i, did in enumerate(HP_IDS):
+            code = HP_CODES[i]
+            data = heat_pump_data(ts, rated_power=35.0, device_code=code)
+            val = data["power"]
+            cop = data["cop"]
+
+            hp_total_power += val
+            if cop > 0:
+                hp_cop_sum += cop
+                hp_count += 1
+
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "power", "value": val, "unit": "kW", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "cop", "value": cop, "unit": "", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "inlet_temp", "value": data["inlet_temp"], "unit": "℃", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "outlet_temp", "value": data["outlet_temp"], "unit": "℃", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "flow_rate", "value": data["flow_rate"], "unit": "m³/h", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "outdoor_temp", "value": data["outdoor_temp"], "unit": "℃", "quality": 0,
+            })
+
+            daily_buckets[did].setdefault(date_str, {"values": [], "cops": []})
+            daily_buckets[did][date_str]["values"].append(val)
+            daily_buckets[did][date_str]["cops"].append(cop)
+
+        # --- Meters ---
+        for i, did in enumerate(METER_IDS):
+            code = METER_CODES[i]
+            data = building_load(ts, base_power=50.0, meter_code=code)
+            val = data["power"]
+
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "power", "value": val, "unit": "kW", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "voltage", "value": data["voltage"], "unit": "V", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "current", "value": data["current"], "unit": "A", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": did, "timestamp": ts,
+                "data_type": "power_factor", "value": data["power_factor"], "unit": "", "quality": 0,
+            })
+
+            daily_buckets[did].setdefault(date_str, {"values": [], "cops": []})
+            daily_buckets[did][date_str]["values"].append(val)
+
+        # --- Heat meter (correlated with heat pump totals) ---
+        avg_cop = hp_cop_sum / hp_count if hp_count > 0 else 3.0
+        hm_data = heat_meter_data(ts, hp_power=hp_total_power, hp_cop=avg_cop)
+        energy_rows.append({
+            "device_id": HEAT_METER_ID, "timestamp": ts,
+            "data_type": "heat_power", "value": hm_data["heat_power"], "unit": "kW", "quality": 0,
+        })
+        energy_rows.append({
+            "device_id": HEAT_METER_ID, "timestamp": ts,
+            "data_type": "flow_rate", "value": hm_data["flow_rate"], "unit": "m³/h", "quality": 0,
+        })
+        energy_rows.append({
+            "device_id": HEAT_METER_ID, "timestamp": ts,
+            "data_type": "supply_temp", "value": hm_data["supply_temp"], "unit": "℃", "quality": 0,
+        })
+        energy_rows.append({
+            "device_id": HEAT_METER_ID, "timestamp": ts,
+            "data_type": "return_temp", "value": hm_data["return_temp"], "unit": "℃", "quality": 0,
+        })
+
+        # --- Temperature/humidity sensors ---
+        for i, sid in enumerate(SENSOR_IDS):
+            code = SENSOR_CODES[i]
+            is_outdoor = (code == "TH-05")
+            data = indoor_sensor(ts, is_outdoor=is_outdoor, device_code=code)
+            energy_rows.append({
+                "device_id": sid, "timestamp": ts,
+                "data_type": "temperature", "value": data["temperature"], "unit": "℃", "quality": 0,
+            })
+            energy_rows.append({
+                "device_id": sid, "timestamp": ts,
+                "data_type": "humidity", "value": data["humidity"], "unit": "%", "quality": 0,
+            })
+
+    print(f"  Generated {len(energy_rows)} energy_data rows")
+
+    # ---- Build daily summary rows ----
+    print("Computing daily summaries ...")
+    summary_rows = []
+    for did, dates in daily_buckets.items():
+        is_pv = did in PV_IDS
+        for date_str, bucket in dates.items():
+            values = bucket["values"]
+            cops = bucket["cops"]
+            total = round(sum(values), 2)
+            peak = round(max(values), 2) if values else 0
+            min_p = round(min(values), 2) if values else 0
+            avg_p = round(sum(values) / len(values), 2) if values else 0
+            op_hours = sum(1 for v in values if v > 0.5)
+            cost = round(total * 0.85, 2)
+            carbon = round(total * EMISSION_FACTOR, 2)
+            avg_cop = round(sum(cops) / len(cops), 2) if cops else None
+
+            summary_rows.append({
+                "device_id": did,
+                "date": datetime.strptime(date_str, "%Y-%m-%d").replace(tzinfo=timezone.utc),
+                "energy_type": "electricity",
+                "total_consumption": 0.0 if is_pv else total,
+                "total_generation": total if is_pv else 0.0,
+                "peak_power": peak,
+                "min_power": min_p,
+                "avg_power": avg_p,
+                "operating_hours": float(op_hours),
+                "avg_cop": avg_cop,
+                "cost": cost,
+                "carbon_emission": carbon,
+            })
+
+    print(f"  Generated {len(summary_rows)} daily summary rows")
+
+    # ---- Build carbon emission daily rows ----
+    print("Computing daily carbon emissions ...")
+    daily_consumption: dict[str, float] = {}
+    daily_pv_gen: dict[str, float] = {}
+    daily_hp_consumption: dict[str, float] = {}
+
+    for did, dates in daily_buckets.items():
+        for date_str, bucket in dates.items():
+            total = sum(bucket["values"])
+            if did in PV_IDS:
+                daily_pv_gen[date_str] = daily_pv_gen.get(date_str, 0) + total
+            elif did in HP_IDS:
+                daily_hp_consumption[date_str] = daily_hp_consumption.get(date_str, 0) + total
+                daily_consumption[date_str] = daily_consumption.get(date_str, 0) + total
+            else:
+                daily_consumption[date_str] = daily_consumption.get(date_str, 0) + total
+
+    all_dates = sorted(set(list(daily_consumption.keys()) + list(daily_pv_gen.keys())))
+    for date_str in all_dates:
+        dt = datetime.strptime(date_str, "%Y-%m-%d").replace(tzinfo=timezone.utc)
+
+        # Grid electricity emission (Scope 2)
+        grid_kwh = daily_consumption.get(date_str, 0)
+        carbon_rows.append({
+            "date": dt, "scope": 2, "category": "electricity",
+            "emission": round(grid_kwh * EMISSION_FACTOR, 2),
+            "reduction": 0.0,
+            "energy_consumption": round(grid_kwh, 2),
+            "energy_unit": "kWh",
+            "note": "园区用电碳排放",
+        })
+
+        # PV generation reduction (Scope 2 avoided)
+        pv_kwh = daily_pv_gen.get(date_str, 0)
+        if pv_kwh > 0:
+            carbon_rows.append({
+                "date": dt, "scope": 2, "category": "pv_generation",
+                "emission": 0.0,
+                "reduction": round(pv_kwh * EMISSION_FACTOR, 2),
+                "energy_consumption": round(pv_kwh, 2),
+                "energy_unit": "kWh",
+                "note": "光伏发电碳减排",
+            })
+
+        # Heat pump saving (COP-based reduction vs electric heating)
+        hp_kwh = daily_hp_consumption.get(date_str, 0)
+        if hp_kwh > 0:
+            avg_cop_day = 3.2
+            heat_delivered = hp_kwh * avg_cop_day
+            electric_heating_kwh = heat_delivered  # COP=1 for electric heating
+            saved_kwh = electric_heating_kwh - hp_kwh
+            carbon_rows.append({
+                "date": dt, "scope": 2, "category": "heat_pump_saving",
+                "emission": 0.0,
+                "reduction": round(saved_kwh * EMISSION_FACTOR, 2),
+                "energy_consumption": round(saved_kwh, 2),
+                "energy_unit": "kWh",
+                "note": "热泵节能碳减排(相比电加热)",
+            })
+
+    print(f"  Generated {len(carbon_rows)} carbon emission rows")
+
+    # ---- Bulk insert ----
+    BATCH = 2000
+
+    async with session_factory() as session:
+        # Insert energy_data
+        print("Inserting energy_data ...")
+        insert_energy = text("""
+            INSERT INTO energy_data (device_id, timestamp, data_type, value, unit, quality)
+            VALUES (:device_id, :timestamp, :data_type, :value, :unit, :quality)
+        """)
+        for i in range(0, len(energy_rows), BATCH):
+            batch = energy_rows[i : i + BATCH]
+            await session.execute(insert_energy, batch)
+            done = min(i + BATCH, len(energy_rows))
+            if done % 10000 < BATCH:
+                print(f"  energy_data: {done}/{len(energy_rows)}")
+        await session.commit()
+        print("  energy_data done.")
+
+        # Insert daily summaries
+        print("Inserting energy_daily_summary ...")
+        insert_summary = text("""
+            INSERT INTO energy_daily_summary
+                (device_id, date, energy_type, total_consumption, total_generation,
+                 peak_power, min_power, avg_power, operating_hours, avg_cop, cost, carbon_emission)
+            VALUES
+                (:device_id, :date, :energy_type, :total_consumption, :total_generation,
+                 :peak_power, :min_power, :avg_power, :operating_hours, :avg_cop, :cost, :carbon_emission)
+        """)
+        for i in range(0, len(summary_rows), BATCH):
+            batch = summary_rows[i : i + BATCH]
+            await session.execute(insert_summary, batch)
+        await session.commit()
+        print(f"  daily_summary done. ({len(summary_rows)} rows)")
+
+        # Insert carbon emissions
+        print("Inserting carbon_emissions ...")
+        insert_carbon = text("""
+            INSERT INTO carbon_emissions
+                (date, scope, category, emission, reduction,
+                 energy_consumption, energy_unit, note)
+            VALUES
+                (:date, :scope, :category, :emission, :reduction,
+                 :energy_consumption, :energy_unit, :note)
+        """)
+        for i in range(0, len(carbon_rows), BATCH):
+            batch = carbon_rows[i : i + BATCH]
+            await session.execute(insert_carbon, batch)
+        await session.commit()
+        print(f"  carbon_emissions done. ({len(carbon_rows)} rows)")
+
+    await engine.dispose()
+    print("=" * 60)
+    print("Backfill complete!")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    asyncio.run(backfill())

core/scripts/init_db.py

@@ -0,0 +1,18 @@
+"""数据库初始化 - 创建所有表"""
+import asyncio
+import sys
+sys.path.insert(0, "../backend")
+
+from app.core.database import engine, Base
+from app.models import *  # noqa: F401, F403
+
+
+async def init():
+    async with engine.begin() as conn:
+        await conn.run_sync(Base.metadata.create_all)
+    print("All tables created successfully!")
+    await engine.dispose()
+
+
+if __name__ == "__main__":
+    asyncio.run(init())

core/scripts/quick-start.sh

@@ -0,0 +1,145 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+# 天普零碳园区智慧能源管理平台 - 快速启动脚本
+
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+RED='\033[0;31m'
+NC='\033[0m'
+
+log_info()  { echo -e "${GREEN}[INFO]${NC} $1"; }
+log_warn()  { echo -e "${YELLOW}[WARN]${NC} $1"; }
+log_error() { echo -e "${RED}[ERROR]${NC} $1"; }
+
+# 检查前置依赖
+check_prerequisites() {
+    log_info "检查前置依赖..."
+
+    if ! command -v docker &> /dev/null; then
+        log_error "未找到 Docker，请先安装 Docker: https://docs.docker.com/get-docker/"
+        exit 1
+    fi
+
+    if ! docker compose version &> /dev/null && ! docker-compose version &> /dev/null; then
+        log_error "未找到 Docker Compose，请先安装 Docker Compose"
+        exit 1
+    fi
+
+    log_info "前置依赖检查通过"
+}
+
+# 确定 docker compose 命令
+get_compose_cmd() {
+    if docker compose version &> /dev/null; then
+        echo "docker compose"
+    else
+        echo "docker-compose"
+    fi
+}
+
+# 初始化环境变量
+init_env() {
+    if [ ! -f .env ]; then
+        log_warn ".env 文件不存在，从模板创建..."
+        if [ -f .env.example ]; then
+            cp .env.example .env
+            log_warn "已创建 .env 文件，请根据实际情况修改配置"
+            log_warn "当前使用默认配置启动，生产环境请务必修改密码和密钥"
+        else
+            log_error "未找到 .env.example 模板文件"
+            exit 1
+        fi
+    else
+        log_info ".env 文件已存在"
+    fi
+}
+
+# 启动服务
+start_services() {
+    local compose_cmd
+    compose_cmd=$(get_compose_cmd)
+
+    log_info "启动服务..."
+    $compose_cmd up -d
+
+    log_info "等待服务就绪..."
+
+    # 等待数据库就绪
+    local retries=30
+    while [ $retries -gt 0 ]; do
+        if docker exec tianpu_db pg_isready -U tianpu -d tianpu_ems &> /dev/null; then
+            log_info "数据库已就绪"
+            break
+        fi
+        retries=$((retries - 1))
+        sleep 2
+    done
+
+    if [ $retries -eq 0 ]; then
+        log_error "数据库启动超时"
+        exit 1
+    fi
+
+    # 等待后端就绪
+    retries=30
+    while [ $retries -gt 0 ]; do
+        if docker exec tianpu_backend curl -sf http://localhost:8000/health &> /dev/null; then
+            log_info "后端服务已就绪"
+            break
+        fi
+        retries=$((retries - 1))
+        sleep 2
+    done
+
+    if [ $retries -eq 0 ]; then
+        log_error "后端服务启动超时"
+        exit 1
+    fi
+}
+
+# 初始化数据
+init_data() {
+    log_info "初始化数据库..."
+    docker exec tianpu_backend python scripts/init_db.py || {
+        log_warn "数据库初始化跳过（可能已初始化）"
+    }
+
+    log_info "写入种子数据..."
+    docker exec tianpu_backend python scripts/seed_data.py || {
+        log_warn "种子数据写入跳过（可能已存在）"
+    }
+}
+
+# 打印访问信息
+print_info() {
+    echo ""
+    echo "============================================="
+    echo " 天普零碳园区智慧能源管理平台 启动完成"
+    echo "============================================="
+    echo ""
+    echo " 前端页面:     http://localhost:3000"
+    echo " 后端 API:     http://localhost:8000"
+    echo " API 文档:     http://localhost:8000/docs"
+    echo ""
+    echo " 默认账号:     admin"
+    echo " 默认密码:     admin123"
+    echo ""
+    echo " 请在首次登录后修改默认密码"
+    echo "============================================="
+    echo ""
+}
+
+# 主流程
+main() {
+    log_info "天普零碳园区智慧能源管理平台 - 快速启动"
+    echo ""
+
+    check_prerequisites
+    init_env
+    start_services
+    init_data
+    print_info
+}
+
+main "$@"