Principle of remote meter reading for smart meters

The remote meter reading function of smart metering meters is achieved through five major links: data collection, transmission, processing and storage, analysis and statistics, and data presentation. Combined with the Internet of Things, communication, and encryption technologies, an efficient and secure automated meter reading system is formed. The following is the specific implementation principle:

1、 Data Collection: Collaborative Work of Sensors and Metrology Chips

The smart meter is equipped with high-precision sensors that can collect real-time electrical parameters such as voltage, current, and power factor. These parameters are processed by a dedicated metering chip, converted into pulse signals proportional to electrical energy, and then digitized by a microcontroller to ultimately generate electricity consumption data. For example, electronic meters obtain signals through current transformers and voltage transformers, and after A/D conversion, calculate the energy value with an accuracy of within ± 1%, which is much higher than traditional mechanical meters.

2、 Data transmission: Multi mode communication technology covers all scenarios

The collected data needs to be transmitted to a remote server through a communication module, and common transmission methods include:

wired transmission

RS485 bus: connects the electricity meter and collector through twisted pair cables, supports long-distance (1.2km) and multi node (32 units) transmission, suitable for industrial parks or large buildings.

Power Line Carrier (PLC): Using existing power lines to transmit data without additional wiring, low cost, but susceptible to power grid noise interference, with a transmission rate of approximately 500bps.

Network cable/fiber optic cable: directly connects the electricity meter to the local area network, with high transmission speed (100Mbps+), but high deployment cost, mostly used in data centers or high-end commercial scenarios.

wireless transmission

IoT network card (4G/NB IoT): The meter has a built-in SIM card that uploads data through a mobile network, covering a wide range (nationwide), but requires payment for data usage fees. NB IoT modules have low power consumption and are suitable for remote areas or battery powered scenarios.

LoRa/WiFi: LoRa is suitable for long-distance (5-15km), low-power scenarios, such as rural power grids; WiFi is used for short distance (within 100m) scenarios such as apartments and hotels, and relies on existing wireless networks.

Micro power wireless: such as 433MHz frequency band, with a transmission distance of about 1km, low cost, but susceptible to interference, mostly used in residential areas.

3、 Data processing and storage: combination of cloud and edge computing

edge processing

The data concentrator (such as connecting 500-1000 electricity meters) performs preliminary verification, deduplication, and compression on the raw data to reduce transmission volume. For example, the concentrator can store data for 7 days, avoiding data loss caused by network interruptions.

cloud storage

The data is uploaded to the cloud database through encrypted channels (such as SSL/TLS) and stored according to dimensions such as time and user ID. The database supports high concurrency writes (such as 100000 per second) to ensure real-time performance.

4、 Data Analysis and Statistics: From Raw Data to Decision Support

Basic Statistics

The system calculates indicators such as electricity consumption, peak power, and load rate on a daily, monthly, and annual basis, and generates user bills and energy consumption reports. For example, a certain factory found through analysis that the power consumption of idle equipment at night accounts for 30%, and after optimization, the annual electricity cost is saved by 500000 yuan.

anomaly detection

Identify anomalies such as electricity theft and equipment failures through machine learning algorithms. For example, the system detected that a user's nighttime electricity consumption suddenly increased by three times the daily average, triggering an alarm and sending personnel to check, and found that it was a leakage in the circuit behind the meter.

load forecasting

Based on historical data and factors such as weather and holidays, predict regional electricity load and assist in power grid dispatch. For example, before the high temperature in summer, the system predicts that the air conditioning load in a certain area will increase by 20%, and the transformer capacity will be adjusted in advance.

5、 Data presentation: Real time interaction among multiple terminals

client side

Users can query real-time power consumption, fees, and power consumption suggestions (such as "avoid high-power equipment during peak hours") through APP, webpage or WeChat official account, and can recharge online and apply for repair.

admin side

The power company monitors the status of electricity meters across the entire network through a management platform, generates reports (such as a list of overdue users and line loss analysis), and can remotely control electricity meters (such as overdue tripping and power restoration).

6、 Security mechanism: Data lifecycle protection

transmission encryption

Encrypt data using national encryption algorithms (such as SM4) to prevent man in the middle attacks. For example, NB IoT modules communicate with base stations through AES-128 encrypted communication.

Identity Authentication

The electricity meter, concentrator, and platform are mutually authenticated through digital certificates to ensure the legality of the equipment. For example, when the electricity meter is first connected to the platform, the platform certificate needs to be verified to prevent pseudo base station attacks.

Data Integrality Check 

Ensure that data has not been tampered with through techniques such as CRC verification and digital signature. For example, the concentrator uploads data with a hash value, which is verified by the platform and stored.

7、 Typical application scenarios

residential electricity

After promoting smart meters in a certain city, the meter reading efficiency has increased by 90%, and the arrears rate has decreased by 60%. Users can view the electricity consumption ranking in real time through the APP, promoting energy conservation.

industrial electricity

A certain steel plant analyzed high energy consuming equipment (such as electric furnaces) through a remote meter reading system, optimized production plans, and saved 2 million yuan in electricity bills annually.

New energy access

Distributed photovoltaic power stations upload power generation data to the platform through smart meters, achieving "self use and surplus electricity grid connection" settlement and improving the utilization rate of new energy.