CasaOS能源管理：智能家居能耗监控与优化
项目地址: https://gitcode.com/GitHub_Trending/ca/CasaOS 引言：家庭能源管理的迫切需求
随着智能家居设备的普及，家庭能源消耗问题日益凸显。据统计，一个普通家庭中智能设备的待机功耗可能占到总电费的10%-15%。你是否遇到过以下痛点：
- 无法实时监控家中各个设备的能耗情况
- 不清楚哪些设备是"电老虎"，消耗大量电力
- 缺乏智能化的节能策略和自动化控制
- 电费账单居高不下，却不知道问题出在哪里
CasaOS作为一款开源个人云系统，通过其强大的扩展能力和丰富的应用生态，为家庭能源管理提供了完美的解决方案。本文将深入探讨如何利用CasaOS构建智能家居能耗监控与优化系统。
CasaOS能源管理架构设计
系统架构概览
核心技术组件
| 组件名称 | 功能描述 | 在能源管理中的作用 |
|---|---|---|
| HomeAssistant | 智能家居集成平台 | 设备连接、数据采集、自动化控制 |
| InfluxDB | 时序数据库 | 存储能耗历史数据，支持时间序列分析 |
| Grafana | 数据可视化平台 | 创建丰富的能耗监控仪表板 |
| Node-RED | 流编程工具 | 构建节能自动化流程 |
| MQTT Broker | 消息代理 | 设备间通信和数据传输 |
环境搭建与配置
硬件要求
为了有效实施能源管理，建议使用以下硬件配置：
# 推荐硬件配置
- 主机：ZimaBoard/Raspberry Pi 4/Intel NUC
- 内存：4GB RAM（最低），8GB RAM（推荐）
- 存储：64GB eMMC/SSD（系统盘），额外硬盘用于数据存储
- 网络：千兆以太网，支持WiFi 6（可选）
- 传感器：智能插座、环境传感器、电力监测设备
CasaOS安装与基础配置
# 一键安装CasaOS
wget -qO- https://get.casaos.io | sudo bash
# 检查安装状态
casaos -v
# 访问Web界面
# 默认地址：http://<设备IP>:80
能源管理应用安装
通过CasaOS应用商店安装必要的能源管理应用：
# docker-compose.yml 示例 - 能源管理套件
version: '3'
services:
homeassistant:
image: homeassistant/home-assistant:stable
container_name: homeassistant
volumes:
- ./homeassistant:/config
ports:
- "8123:8123"
restart: unless-stopped
influxdb:
image: influxdb:2.7
container_name: influxdb
volumes:
- ./influxdb2:/var/lib/influxdb2
ports:
- "8086:8086"
environment:
- DOCKER_INFLUXDB_INIT_MODE=setup
- DOCKER_INFLUXDB_INIT_USERNAME=admin
- DOCKER_INFLUXDB_INIT_PASSWORD=energy2024
- DOCKER_INFLUXDB_INIT_ORG=casaos
- DOCKER_INFLUXDB_INIT_BUCKET=energy_data
restart: unless-stopped
grafana:
image: grafana/grafana:latest
container_name: grafana
volumes:
- ./grafana:/var/lib/grafana
ports:
- "3000:3000"
environment:
- GF_SECURITY_ADMIN_PASSWORD=energy2024
restart: unless-stopped
nodered:
image: nodered/node-red:latest
container_name: nodered
volumes:
- ./nodered:/data
ports:
- "1880:1880"
restart: unless-stopped
设备接入与数据采集
智能设备配置
1. 智能插座配置示例
# HomeAssistant configuration.yaml
sensor:
- platform: template
sensors:
living_room_power:
friendly_name: "客厅插座功率"
unit_of_measurement: "W"
value_template: "{{ states('sensor.living_room_plug_power') | float }}"
device_class: power
switch:
- platform: template
switches:
living_room_plug:
friendly_name: "客厅智能插座"
value_template: "{{ states('switch.living_room_plug') }}"
turn_on:
service: switch.turn_on
target:
entity_id: switch.living_room_plug
turn_off:
service: switch.turn_off
target:
entity_id: switch.living_room_plug
2. 电力监测设备集成
# energy_monitor.py - 电力数据采集脚本
import requests
import json
from datetime import datetime
class EnergyMonitor:
def __init__(self, device_ip, device_type):
self.device_ip = device_ip
self.device_type = device_type
self.base_url = f"http://{device_ip}/api"
def get_power_consumption(self):
"""获取实时功耗数据"""
try:
response = requests.get(f"{self.base_url}/energy/current")
data = response.json()
return {
'timestamp': datetime.now().isoformat(),
'power_watt': data['power'],
'voltage': data['voltage'],
'current': data['current'],
'device_type': self.device_type
}
except Exception as e:
print(f"Error fetching data: {e}")
return None
def send_to_influxdb(self, data):
"""发送数据到InfluxDB"""
influx_data = f"energy,device={self.device_type} power={data['power_watt']},voltage={data['voltage']}"
requests.post("http://localhost:8086/write?db=energy_data", data=influx_data)
数据采集流程
能耗数据分析与可视化
InfluxDB数据模型设计
-- 创建能耗数据存储策略
CREATE RETENTION POLICY "energy_30days" ON "energy_data" DURATION 30d REPLICATION 1
-- 创建连续查询，计算每小时平均功耗
CREATE CONTINUOUS QUERY "energy_hourly_mean" ON "energy_data"
BEGIN
SELECT MEAN("power") AS "mean_power"
INTO "energy_data"."autogen"."energy_hourly"
FROM "energy"
GROUP BY time(1h), "device"
END
-- 创建设备耗电排名查询
SELECT MEAN("power")
FROM "energy"
WHERE time > now() - 7d
GROUP BY "device"
ORDER BY MEAN("power") DESC
Grafana仪表板配置
1. 总体能耗监控面板
{
"dashboard": {
"title": "家庭能源监控",
"panels": [
{
"title": "实时总功耗",
"type": "stat",
"targets": [{
"query": "SELECT mean(\"power\") FROM \"energy\" WHERE $timeFilter GROUP BY time(1m)",
"rawQuery": true
}],
"fieldConfig": {
"defaults": {
"unit": "watt",
"colorMode": "value",
"thresholds": {
"steps": [
{"value": null, "color": "green"},
{"value": 1000, "color": "yellow"},
{"value": 2000, "color": "red"}
]
}
}
}
}
]
}
}
2. 设备能耗对比图表
// 设备能耗对比查询
const deviceComparisonQuery = `
SELECT MEAN("power")
FROM "energy"
WHERE time > now() - 24h
GROUP BY "device", time(1h)
ORDER BY time DESC
`;
// 生成设备能耗排名
const deviceRanking = `
SELECT MEAN("power") as avg_power, "device"
FROM "energy"
WHERE time > now() - 7d
GROUP BY "device"
ORDER BY avg_power DESC
`;
能耗数据分析指标
| 指标名称 | 计算公式 | 说明 |
|---|---|---|
| 日平均功耗 | SUM(功率) / 24 | 反映日常用电水平 |
| 峰值功耗 | MAX(功率) | 识别用电高峰时段 |
| 谷值功耗 | MIN(功率) | 识别节能潜力时段 |
| 设备占比 | 设备功耗 / 总功耗 | 分析各设备贡献度 |
| 用电成本 | 总功耗 × 电价 | 计算实际电费支出 |
智能节能策略实现
基于规则的节能自动化
1. Node-RED节能流程
[
{
"id": "energy-saver-flow",
"type": "tab",
"label": "节能自动化",
"nodes": [
{
"id": "power-monitor",
"type": "influxdb in",
"z": "energy-saver-flow",
"influxdb": "casaos-influx",
"query": "SELECT mean(\"power\") FROM \"energy\" WHERE time > now() - 5m",
"name": "监控实时功耗",
"output": "payload"
},
{
"id": "threshold-check",
"type": "switch",
"z": "energy-saver-flow",
"name": "功耗阈值检查",
"property": "payload[0].mean",
"rules": [
{"t": "gt", "v": "1500", "vt": "num"},
{"t": "lt", "v": "500", "vt": "num"}
],
"checkall": "true",
"outputs": 2
},
{
"id": "high-power-action",
"type": "function",
"z": "energy-saver-flow",
"name": "高功耗处理",
"func": "// 关闭非必要设备\nmsg.payload = {\n service: 'switch.turn_off',\n entity_id: 'switch.non_essential_devices'\n};\nreturn msg;",
"outputs": 1
}
]
}
]
2. 时间表节能策略
# automation.yaml - 时间表节能
- alias: "夜间节能模式"
trigger:
- platform: time
at: "22:00:00"
action:
- service: switch.turn_off
target:
entity_id:
- switch.living_room_tv
- switch.office_computer
- service: light.turn_off
target:
entity_id: light.all_lights
- alias: "工作日节能"
trigger:
- platform: time
at: "08:30:00"
days_of_week:
- mon
- tue
- wed
- thu
- fri
action:
- service: climate.set_temperature
target:
entity_id: climate.thermostat
data:
temperature: 18
机器学习能耗分析
# energy_analyzer.py - 能耗分析模型
import pandas as pd
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import train_test_split
class EnergyAnalyzer:
def __init__(self):
self.model = RandomForestRegressor(n_estimators=100)
def prepare_data(self, historical_data):
"""准备训练数据"""
df = pd.DataFrame(historical_data)
df['hour'] = pd.to_datetime(df['timestamp']).dt.hour
df['day_of_week'] = pd.to_datetime(df['timestamp']).dt.dayofweek
df['is_weekend'] = df['day_of_week'].isin([5, 6]).astype(int)
return df
def train_model(self, X, y):
"""训练分析模型"""
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
self.model.fit(X_train, y_train)
return self.model.score(X_test, y_test)
def analyze_consumption(self, features):
"""分析能耗模式"""
return self.model.predict([features])
实战案例：典型家庭节能方案
案例一：客厅娱乐区节能优化
案例二：厨房设备智能管理
# kitchen_energy_optimization.yaml
- id: kitchen_energy_optimization
alias: "厨房设备节能"
trigger:
- platform: state
entity_id: binary_sensor.kitchen_motion
to: "off"
for:
minutes: 10
action:
- service: switch.turn_off
target:
entity_id:
- switch.kitchen_exhaust_fan
- switch.kitchen_light
- service: climate.set_preset_mode
target:
entity_id: climate.kitchen_ac
data:
preset_mode: "eco"
- service: notify.mobile_app
data:
message: "厨房设备已进入节能模式，节省电力消耗"
案例三：季节性用电调整
# seasonal_adjustment.py
class SeasonalEnergyManager:
def __init__(self):
self.seasonal_profiles = {
'summer': {
'ac_temperature': 26,
'water_heater_temp': 45,
'lighting_schedule': {'on': '19:00', 'off': '23:00'}
},
'winter': {
'heating_temperature': 20,
'water_heater_temp': 55,
'lighting_schedule': {'on': '17:00', 'off': '22:00'}
},
'spring_autumn': {
'ac_temperature': 24,
'water_heater_temp': 50,
'lighting_schedule': {'on': '18:00', 'off': '22:30'}
}
}
def adjust_for_season(self, current_season):
"""根据季节调整设备设置"""
profile = self.seasonal_profiles[current_season]
# 调整空调温度
self.set_ac_temperature(profile['ac_temperature'])
# 调整热水器温度
self.set_water_heater_temp(profile['water_heater_temp'])
# 调整照明时间表
self.adjust_lighting_schedule(profile['lighting_schedule'])
return f"已切换到{current_season}季节节能模式"
性能优化与故障排除
系统性能监控
# 监控CasaOS系统资源使用情况
docker stats casaos
# 检查能源管理服务状态
docker ps --filter "name=energy"
# 查看服务日志
docker logs homeassistant
docker logs influxdb
docker logs grafana
# 监控数据库性能
influx -execute "SHOW STATS"
常见问题解决方案
| 问题现象 | 可能原因 | 解决方案 |
|---|---|---|
| 数据采集中断 | 网络连接问题 | 检查设备网络连接，重启MQTT服务 |
| 数据库存储满 | 数据保留策略不当 | 调整InfluxDB数据保留策略 |
| 可视化图表不更新 | Grafana配置错误 | 检查数据源连接，更新面板查询 |
| 自动化规则不触发 | Node-RED流程错误 | 检查流程逻辑，查看调试信息 |
| 设备响应延迟 | 系统资源不足 | 优化容器资源配置，增加系统内存 |
资源优化建议
# docker-compose.override.yml - 资源限制
version: '3'
services:
homeassistant:
deploy:
resources:
limits:
memory: 512M
cpus: '0.5'
reservations:
memory: 256M
cpus: '0.25'
influxdb创作声明：本文部分内容由AI辅助生成（AIGC），仅供参考
