Smart Meter Challenges: Data Processing

Data processing has always been the top priority for smart meters, and this article also briefly introduces the data processing of smart meters.

As systems/solutions introduce more and more functions, the tasks that instruments need to control and the data they need to process also increase significantly. Therefore, depending on the application and the load on the SoC core, designers may decide to migrate to a 32-bit core or use a powerful DSP core so that the application (communication, etc.) and the metering part do not affect each other.

The computational workload of the core can also be offloaded by using additional hardware in the SoC, where the additional hardware is only responsible for various computational tasks, as metering applications are highly computationally intensive applications.

Data concentrators and metering gateways are most affected by the system data processing capabilities because they need to process large amounts of data. At the same time, they need to support user interfaces, further increasing the associated data processing complexity and corresponding requirements. Therefore, multi-core SoCs may be introduced in the future to support large networks.

Measuring consumption is only part of the problem (see Figure 2). To date, most meters around the world require manual reading. This is because traditional meters are not capable of supporting networked solutions. This manual reading not only increases operating costs, but is also prone to human error.

Therefore, for an effective solution, the meter should also provide the ability to support networking solutions and transmit data to the meter network for automatic meter reading. A major problem with meter reading transmission is the presence of electrical noise.

Figure: Schematic diagram of the various instrument networking options for the solution.

Therefore, the communication mode should be able to withstand noise without corrupting the data. Therefore, the instrument should be able to generate output in a format that supports error detection and cleanup, and be able to recover from the received data packet even if the data is distorted due to noise. At the same time, all such encryption increases the size of the data to be transmitted.

Therefore, data transmission speed is also important. Currently, there are many data transmission modes. The most common ones include GPRS, Ethernet, power line communication, ZigBee, infrared transceivers, etc.

The communication mode will be selected based on the end application, for example, a ZigBee/IR (infrared) transceiver may be more suitable for a meter network where meters interact wirelessly with a base station to transmit data, and the base station sends data collected from many meters (100 meters in complex cases) to a central station using wired communications.