The smart grid is poised for a tremendous rollout of new and revised technology standards in the next few years, but that’s just the beginning. IEEE Standards Association President Charlton Adams...
Going Smart at Scale
Your smart grid rollout should go live everywhere, right from the start.
Most utilities will conduct a cost-benefit analysis before making any major investment in the grid. Therefore, this analysis should recognize two key strategies for a commitment of this magnitude - a smart grid project, for example.
First, any smart grid rollout will gain the greatest benefits if applied at scale right from the start, to the maximum number of feeders, if not all of them. Second, each smart grid application delivers different benefits, such as cost reduction, improved reliability, greater power quality, or enhanced renewable deployment. The whole exceeds the sum of the parts. Thus, the accumulation of benefits established by layers of multiple smart grid technologies will only enhance the justification analysis. And, the quicker these applications can be implemented, the greater the benefits to be gained.
Yet utilities typically will fail to exploit either of these two strategies. Instead, utilities usually will implement smart grid automation according to a much different, though faulty set of guidelines - much to their disadvantage.
First, utilities typically will seek to minimize complexity, treating a primary smart grid technology as a solo deployment, aimed at meeting a single specific business objective, such as improved reliability through self-healing, cost reduction through loss minimization, or deploying a greater share of renewables. Unfortunately, however, the payback doesn't keep pace. Nor do the engineers gain the experience of understanding the interaction between the technologies.
Second, to minimize the cost of the evaluation, utilities often will select a limited pilot area to represent all feeders over which the anticipated results can be assessed. However, due to myriad feeder configurations and load types, it may not be possible to find a pilot area diverse enough to fully evaluate all the conditions that could be encountered across the network.
Third, a basic staff often is trained to support and maintain the new automation. Their job is to "own" its implementation and to perform the evaluation, but at the cost of project delay. The support staff's engagement may be lengthy, since the pilot is deployed on operational feeders. It could take years before meaningful data generated by an extreme fault or weather condition arises where the technology's performance can be evaluated under stress. Fourth, utilities typically will enable a new automation function only one feeder at a time, such that the benefits will likely fall short of promised effectiveness.
The drawbacks to such a strategy are considerable, not the least of which involve cost and delay. The ability to layer smart grid applications with multiple operational objectives is not just an issue of economic justification, it is critical to delivering quality power.
A better approach would run as follows:
- Maximize automation across technologies and networks.
- Expand the scope of deployment beyond a narrow pilot area.
- Use simulators to minimize involvement of personnel.
- Go live now, and everywhere.
For example, fully automated, self-healing solutions solve one problem but can sometimes create others. The sudden transfer of unfaulted loads