The complex process of selecting an AMI system takes considerable time, goes through distinct phases, and is subject to outside influences that will interrupt progress. The authors list several...
AMI: Smart Enough?
Metering potential and limitations for smart-grid design.
of meters and sensors produce corresponding levels of grid intelligence enablement (see Figure 1) . The choice of what combination of technology is right for a utility depends on the degree of intelligence desired.
When using AMI as a smart-grid entry point, it’s important to understand and plan for the communication system underpinning the smart grid, as well as the architecture of the data-handling system. Doing so will enable these components to be better able to support smart-grid functionality when an organization is ready. These requirements will change the economics of the AMI deployment because the utility will be building in future capability. And, planning for these requirements may mean that a utility finds itself implementing some capabilities or capacities that are not strictly required for the meter-only system. Yet, such planning is imperative; incorporating the capacity to support new capabilities down the line may prove too costly to implement.
When thinking about building a smart grid from a meter system, a utility needs to think about specifying the communication system in order to accommodate the speed requirements of a smart grid, as opposed to just the residential meter system. Meter systems generally don’t require high performance if they are to be used for the meter-to-cash process only. If the goal is to use the meter communication system as the basis for a smart-grid implementation, then it’s wise to consider the range of smart-grid functionality to be supported, the associated technical requirements and performance factors—such as bandwidth, latency, burst/flood response and average response time as a function of number of active nodes. Otherwise the utility runs the risk of either stranding an expensive asset, being forced to build additional communication assets that could have been avoided, or effectively being cut off from some types of smart-grid capabilities. If the meter communication network also will be used to carry control messages for grid devices, then significant cyber-security concerns must be addressed as well.
Another issue that should be considered at the AMI planning stage if the goal is to also support smart-grid capability is the system connectivity model. If the utility wishes to use meters as sensors, it will need a complete connectivity model to provide context for interpretation of grid sensor data. This model includes meter-to-feeder phase connectivity (via the distribution transformer). The problem with using AMI for smart-grid support is that utilities may not have good connectivity models. In fact, utility connectivity databases may be only 50 to 80 percent accurate, and many have no meter-to-phase information at all. To use the meter system as a sensor network, this information must be corrected (or obtained if it never existed) and kept up to date.
Capturing meter-to-phase information can be extremely expensive, especially if it must be done after meters already are rolled out. It’s much better, therefore, to capture this information during smart-meter deployment. Once established, the connectivity data must be kept accurate, which typically involves additional new utility processes because meter connectivity can change over time—when transformers are switched from one phase to another, for example.