Smart Meter (SM) deployment is an essential pillar of the Smart Grid having an increased market penetration around the world. Electricity providers can leverage the automated reporting system of residential metres through data concentrator (DC) nodes and a central analytics and control system called the Head-End-System (HES), or simply control entity hereinafter.
Today a wide-spread communication technology is the Power Line Communication (PLC) between SM's and DC's, which is a cost-effective solution using the already available electricity network infrastructure.
The PLC technology suffers from several limitations, since the power line networks were not designed for communication purposes. It is considered a harsh environment as the signal-to-noise ratio (SNR) is significantly limited by interference effects and noise of other electric devices connected to the network. Furthermore, communication signals transform the power line into a radio antenna representing a potential threat to the radio communication channels in its proximity, thus minimizing the number of messages used is preferable. Narrow-band PLC devices can follow the solution of open standards, where risk of interference effects is minimized. There are a number of methods for optimizing PLC, but their main purpose is out of scope of this invention, e.g. to regulate frequency use inhibiting the radio interference or adapting existing control algorithms to the large delays accepted to be present in the system.
There are more advanced technologies on the market, e.g. Point-to-Point (P2P) and RF mesh, which enable more reliable communication and better quality. However, due to financial and security constraints, typically only a small number of advanced devices complement the PLC SM's for increased reliability of the reporting system.
Typical use of such technology is the remote reading of meters for automatic billing purposes. This scenario is enabled by the currently used process: the control entity sends signal to meters during a pre-fixed period of time daily and recalls only meters where reporting was not successful, checking periodically until next pull cycle is started.
The scheduling of smart meter event transmission (‘transmit window’) is based on global optimum search in which the reporting time is preconfigured to a fixed time of the day. This fixed reporting time is set to the time when the global communication quality offers the highest probability on average to successfully transmit the meter events.
In connection with FIGS. 1 to 3 the drawbacks of the fixed reporting times is shown. The results shown in FIGS. 1 to 3 are based on measurements collected from smart meters using PLC technology during a period of several weeks. FIG. 1 shows a mean measurement quality over time defined by the hourly success ratio of ping messages sent by each data concentrator to its corresponding smart meter.
FIG. 2 shows the time series of number of event recordings at the smart meters indicated by graph 20 in FIG. 2. Graph 21 shows the total number of events processed by the control entity. It can be deduced from FIG. 2 that the reporting times correspond to periods when least of the events are recorded. The processing of the events shown by graph 21 also indicates how the repeated queries reach the blocked smart meters in attenuated waves until the next daily cycle begins.
FIG. 3 shows cumulative distribution function of delays measured between recording of a measurement event at the smart meter and processing of the same event at the control entity. It can be deduced that some of the events are processed within half day of delay and there are events which are not processed within a day following recording. This behavior is the main obstacle of further functionalities of a smart grid, where control processes would rely on the near real-time monitoring of the system.