State utility regulators begin to question the benefits of smart grid technology, and customers take to the streets in public protests and demonstrations to oppose installation of smart meters....
AMI: Smart Enough?
Metering potential and limitations for smart-grid design.
of devices are available today to produce data from a power grid, all of which can be used to help build a smart grid and enable the observability capability. These devices include substation devices (microprocessor relays and associated tranducers), line sensors, smart line devices (switches, reclosers and capacitor bank controllers that can also capture measurements and waveforms), faulted circuit indicators (simple devices for fault detection/location), and various kinds of meters.
Many strategies for how to deploy and use sensing capabilities on a distribution grid are possible. The determination of which sensor types, where to locate them, how they should communicate, and how to manage the data they can produce ultimately depends on requirements for the smart grid that each utility must derive from business needs. Depending on business requirements, quite a range of technical requirements are possible, with significant implications for smart-grid communications in terms of bandwidth, latency, and related characteristics. Consequently, it’s always important to have a clear definition of the specific smart-grid capabilities to be supported before selecting sensors and related infrastructure. Such requirements definition then will make it clear as to how much the meter system can support smart-grid functionality.
If the meter system is to be used as an element of the sensing strategy for a smart grid, then the types and locations of the meters in the AMI system should be included in the process of allocating grid sensors for the smart grid. The sensor allocation process can consider capabilities of residential meters, the more advanced capabilities of C&I meters, and the capabilities of various types of grid sensors to determine number and placement of smart grid measurement points.
The observability of a smart grid through the meter system might be improved by including some number of another type of meter—the feeder meter. These devices attach to medium voltage (MV) feeders, but operate much like C&I meters in terms of communications, interface to meter communications systems, and interface to meter data-collection engines. Such devices have revenue-grade accuracy ratings (0.2 percent), and can provide advanced measurements similar to those typically available from C&I meters. The key here is that they measure parameters on MV feeders, and measure operational data including power flows, energy, and various operational and non-operational parameters at the MV feeder level without having to use communication and data-collection infrastructure separate from that of the meter system.
In this approach, it’s necessary to extract the data generated by these meters and to provide that data to various applications besides the standard meter-to-cash applications. Given this need, the data management and integration architecture to make use of the feeder meters necessarily will include some elements that would not be needed for a standard AMI system. Also, since most of these devices will generate asynchronous event messages, the system must provide the means to process these messages, which often occur in bursts and floods.
Commercial and residential meters have their shortcomings in capturing the array of electrical parameters needed for a smart grid. Feeder meters can help mitigate this weakness. To incorporate these meters into a smart-grid configuration,