When the vision of a smart grid first appeared over a decade ago, it was revolutionary and broadly recognized as being so. Yet even an informal
assessment of the facility and technology development
necessary to realize that vision made it clear smart grids
would require a lengthy evolution.
Of course the smart grid concept didn’t just pop up like toast, a notion fully formed between a pair of ears. Many of the intellectual and
technological underpinnings date back at least to the ’90s. Operational challenges to large-scale electric-power generation, transmission,
and distribution date back much further.
One of the early underpinning developments was the electronic
energy meter, which predated submicron semiconductor processes.
These first electronic meters merely had to measure, totalize, and
report energy use — a direct replacement for their electro-mechanical
predecessors, which they were almost immediately poised to replace.
Originally, the most obvious rationale for switching to electronic
metering was it would reduce utilities’ reading costs. Since the deployment of smart meters began, however, they have allowed utilities
to make fine-grained, geographically and temporally distributed measurements of grid utilization and grid performance throughout their
networks. That data stream supports both infrastructure management
efforts and grid-modernization investments. These activities make
use of smart-grid devices that are less visible to individual customers,
but more critical to the realization of smart-grid benefits: Robustness
in the face of growing load, environmental, and equipment-aging
stresses; capacity management; and flexibility to exploit distributed
— often renewables-based — generating facilities.
Over 37 years, the CAGR (compound annual growth rate) in elec-
tric-energy use worldwide has outpaced increases in both population
and overall energy use by more than two to one, according to the
World Bank. Electric grids have not enjoyed proportional growth in
their power-delivery capability so, in many regions, electric-power
infrastructure is under increasing capacity stress. This growing strain
manifests, for example, in transformers operating at or beyond their
nameplate current ratings, which can lead to overheating and a reduc-
tion in the equipment’s useful operating life. In severe cases of load
outpacing capacity, utilities have had to resort to rolling blackouts at
great inconvenience to their residential customers and great cost to
their commercial and industrial ones.
The development of smart grids has provided a smooth path for
integrating distributed generating facilities into transmission and
distribution networks designed for traditional generating plants.
Distributed generation can help reduce capacity stresses in two ways:
Large-scale generating facilities — both traditional plants and those
operating from renewable sources — help reduce transmission distances and provide greater sourcing flexibility. Small-scale generation,
like diesel-electric, solar-array, or wind turbine, sites power sources
adjacent to their loads, effectively taking load current off transmission and distribution networks.
One of the surprising consequences of smart grid technologies is
the enormous scalability of coexisting energy resources. On the large
end of the spectrum are the mammoth generating facilities, the largest
of which is currently the 18. 2 GW China Yangtze Three Gorges Project
hydroelectric plant in Xilingxia gorge, China, according to China
Three Gorges Corporation. On the other end of the generating spectrum are small solar arrays and wind generators with capacities in the
range of 10 k W or so,
appropriate for individual residences
and small businesses
(Figure 1). That’s a
seven order of magnitude range — the
ratio of, say, the weight of a car (1000 kg or so) to that of a flea (0.1 g).
I mention that range, not because it’s instructive by itself, but because of what’s behind it. Once you get past the transduction method
— the means of converting energy from its available form to electric
— there are few architectures in use that make that energy available
through the smart grid. Monitoring and control architectures also
tend to be quite similar, in gross, over most if not all of the scale. As
you descend the design hierarchy through topology and underlying
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One of the surprising consequences
of smart grid technologies is the
enormous scalability of coexisting