IEEE Power & Energy Magazine - May/June 2014 - 64

or force its valuable assets (in this case, its communication
systems) to haul time-sensitive data back and forth across
various layers of the iCt hierarchy, thereby risking system
inefficiency and "by design" failure.
another example of how critical forward-looking smart
grid integration maps are arises out of the requirement to
achieve tighter and more meaningful interfaces with customer-based assets. it is believed that in the not very distant
future, substation-based VVo and CVr functions will need
to extend their reach beyond smart meters and include some
coordination (or even command and control of) customerside generation assets and loads.
as depicted in Figure 9, such assets will include rooftop
PV modules and electric cars. in fact, recent reports about
the negative impact of uncoordinated rooftop solar cells on
the stability of feeder voltage levels are quite discouraging.
the unpredictable and intermittent behavior of such distributed generation assets cannot be entirely mitigated with utility field assets (e.g., capacitor banks). and even if such costly
assets could be effectively used to help stabilize voltage levels, their useful life spans (and health) could be considerably
compromised by these frequent anomalies (e.g., by voltage
levels' pushing outside the anSi band due to intermittent
generation from customer rooftop PV modules).
the voltage stability issues caused by electric cars used in
their vehicle-to-grid (V2g) mode may be far less severe than
those from rooftop PV modules, but this is still a problem for
which utilities need to make adequate provision. even though
electric car manufacturers may not enable V2g functionality
for their cars for the foreseeable future due to their concerns
about the cost of battery warranties, utilities need to plan and
be ready for such issues should V2g become a reality.
what is interesting is that both of these threats could be
converted into opportunities for the utility if appropriate
provisions are made in the utility's smart grid integration
map to take advantage of the availability of such downstream assets and integrate them with future substationbased emSs. as depicted in Figure 9, such an emS would
incorporate various command, control, and processing functions, using global system attributes and local feeder data to
configure all of its assets (inside and outside the substation)
so as to achieve its energy management goals.
obviously, the demands such a level of integration would
place on the ami system are even heavier than in the previous example. Here, the ami system would work as the
conduit of communication and coordination between the
substation-based emS engine and customer-owned cogeneration resources placed behind the meter. as such, it would
be critical to ensure that smart grid integration maps require
ami systems to support such functionalities without major
engineering and overhaul.

Litmus Test
as discussed earlier, a forward-looking smart grid integration
map is critical for the realization of a smart grid. and given the
64

ieee power & energy magazine

cost involved in integrating new technologies and functionalities into the existing grid, the smart grid integration map could
prove to be either the savior or the achilles' heel of a utility's
smart grid program. in making that judgment, every utility
has to review the operational requirements of its medium- and
long-term smart grid functions and determine if its smart grid
integration map supports a seamless transition from where it is
now to where it would like to be in the future.
in addition to the examples discussed at length above,
there are several other commonly identified smart grid capabilities that may be considered as a "litmus test" for ascertaining the suitability of a utility's smart grid integration
map. these include:
✔ Distributed generation: as discussed earlier, concerns about cogeneration synchronization, var control,
voltage stability, and so on have convinced utilities of
the need to achieve a level of integration (notwithstanding the regulatory impediments that exist in
various jurisdictions across north america) between
feeder assets and behind-the-meter, customer-owned
equipment. given the fact that the point of common
coupling between the utility and the customer is the
smart meter, such a level of integration must be facilitated by the utility's smart grid integration map.
✔ Sensor networks on the low-voltage (LV) side of the
distribution system: although such sensory data on the
lV side (such as those from phasor measurement units)
have not yet been established as a critical requirement,
one should assume that should that become a necessity,
the ami infrastructure could be the primary means of
supporting such real-time data (through an auxiliary
channel) and transporting them to the substation. the
alternative to using the existing ami assets for such
data would be to construct a dedicated, low-latency
communication system with a universal communication
protocol and mission-critical availability and resilience,
together with secure and intrusion-resistant multitier
access, as the carrier of such data for the upper layers of
the system. that could be quite costly. again, no matter
what the chosen architecture for the implementation of
sensor networks, a utility's smart grid integration map
must include provisions for supporting additional data
networks going forward.
✔ Customer-side EMS: emSs on the customer side
of distribution systems are often regarded as "killer
apps" enabling accurate, reliable, real-time, and endto-end energy management functions. given the
trend toward designing distribution substations as
"energy hubs" in charge of achieving cost-effective
management of power and services transactions
between producers and consumers (prosumers),
it is paramount to move away from a broadcastbased, global utility pricing and tariff-signaling
system to a real-time, substation-based, local pricing signal. Just as the price of gas is never the same
may/june 2014



Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - May/June 2014

IEEE Power & Energy Magazine - May/June 2014 - Cover1
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IEEE Power & Energy Magazine - May/June 2014 - Cover3
IEEE Power & Energy Magazine - May/June 2014 - Cover4
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