Variablegrid - a subset of
the electrical grid defined by automated demand control
Abstract: The portion
of the electrical grid dealing with EV charging can be virtualized and separated
from the remainder, because - unlike the loads currently on the grid - its
loads can be automatically controlled. This control entails three co-operating
processes: J1772 charger modulation, current load sensing and a feedback
consumption indicator signal. The interface to the existing grid is defined
by a final, feedforward command signal within the same hierarchical network.
It can be issued from a transformer substation point, but location is discretionary.
Variablegrid is a tool
to enable users of standardized electric vehicle (EV) chargers to maximize
EV charge rates and reduce charging times. It is also a tool to allow providers
of multi-point charging facilities to reduce equipment costs. And finally,
it is a tool that gracefully integrates these new large-scale demands for
electricity into the existing electrical grid.
Until now, it would
have been reckless for an EV user with a 100A electrical service to install
an 80A charging circuit. This is no longer true. Of even greater importance,
it is now possible to connect multiple charging circuits to a central distributor
when the aggregate rating of these circuits exceeds the rating of the central
distributor, on a deterministic rather than probabilistic basis.
This second point is
particularly significant to condominium developers offering EV charging
facilities, to centralized commercial EV charging facilities and to electric
There is a reason why
we have to consider these features now - any growing technology-based market
is sooner or later subject to demands for increased capabilities. It is
very likely that some catalytic event will precipitate increasing demand
for EV's. History has shown this to be true of the microcomputer in the
late 70's. To somebody who has experienced that phenomenon firsthand, the
current EV market gives the impression that it is a market waiting for something
to happen. It is also likely that with increasing demand will come technological
gains that lead to more powerful batteries. EV charging loads can be expected
to be both continuous and concurrent - unlike most loads on the electrical
grid - and therefore pose new challenges. Variablegrid is designed to meet
these challenges, primarily by taking measures that allow existing infrastructure
to change in an evolutionary rather than revolutionary way.
The basic concept behind
variablegrid is very simple: it carries out current sensing at the customer
load point. It then computes the difference between the instantaneous measured
current flow and the load point's current rating and assigns that value
to the EV charger. The amount of current allocated to an active charger
never exceeds its demand, because variablegrid measures its consumption.
However simple this idea is, it has significant consequences.
By using a small amount
of electronics and some software to realize the above technique, variablegrid
can provide pinpoint variable (modulated) control over each charger - this
is more desirable and in sharp contrast to on-off control over a whole region.
This feature makes use of the J1772 standard and basically prioritizes EV
chargers relative to other loads in a graceful way.
In defining control
at the customer load point, variablegrid is able to provide very precise
EV load control integration with existing equipment and without the need
to resort to identification of, and feedback from, individual EV chargers
to a remote central control.
As a result of its
simple algorithm, variablegrid provides an adaptive load control mechanism:
most of the current will be allocated to the EV charger during off-peak
consumption times. This provides a fairly elegant and unique load-leveling
mechanism over large service areas.
Since EV charging rates
are inversely dependent on any concurrent loads on the measured distributor,
the variablegrid adaptive control strategy directly (sooner or later) will
influence customer consumption patterns without any need for specific customer
education. The customer will learn automatically that turning on his hot
tub will lengthen the charging time for his electric car, or that leaving
on his plasma TV with the sound turned off will do the same.
consists of standard, low cost equipment, a simple strategy and a deterministic
control algorithm, it can be brought online quickly and without the need
for regional load simulation studies.
However, the implementation
of variablegrid does carry a serious responsibility. By potentially driving
current distributors to their limits it can overload equipment feeding these
distributors. This equipment typically consists of a distribution transformer
node. Because the current rating for these nodes is based on historical
consumption patterns - which assume that not all customers drive all their
loads at the same time - their rating is lower than the aggregate ratings
of the load points they support. As a result, they could become overloaded.
However, distribution transformers are merely (larger) current distributors
and can be handled as just another load point by variablegrid.
Up to this point everything
that was said about variablegrid seems to make it simple, adaptive, automatic
and self-contained. Nevertheless, variablegrid must be integrated with one
final current distributor - the distribution substation. Here, although
variablegrid cannot play any direct role, it does serve two functions: reporting
and throttling EV consumption.
Please recall that
above we said there are 2 parameters associated with a distributor: its
current flow and its capacity (or rating.) Reporting EV consumption is a
relatively simple task, but throttling it depends on a feature of variablegrid
called virtual (or allocated) capacity. In essence, variablegrid does not
use the load point's actual rating in its calculation, but rather its allocated
rating. This is a software value that can vary from 0 to 100% of actual
capacity. By sending a (very short) signal to any of the distributor nodes
sensed by variablegrid, a central administration can reduce the EV consumption
for that node, or bring it back up from some reduced level; the signal effectively
changes the value of allocated capacity at the node. This method adds supply-side
control to the already shown demand-side control.
This mechanism does
not affect any other equipment deriving power from that distributor.
One final feature of
variablegrid is worth mentioning. EV loads will represent a substantial
demand on the grid. After a regional power failure there are tense moments
during the so-called blackstart recovery phase, when large reactive currents
flowing during low-voltage startup conditions can cause equipment to trip
or fail. Variablegrid measures reactive currents in exactly the same way
as it does resistive currents. Excessive current flows at a measured distributor
will cause variablegrid to delay EV charging on that distributor until its
current flows are once again nominal. This feature will apply not just to
a utility, but also to residential or industrial sites that combine the
use of motorized heavy equipment (such as air conditioners) with EV charging.
In order to implement
all of the above, variablegrid relies on a single printed circuit board
(PCB) with removable system-on-chip (SOC) electronic components and function-dependent
software. This approach was taken to reduce production costs. Each board
has the same number of discrete components, but the specific complement
of SOC electronics on the board depends on the board's function as a node.
The software depends on both the functions of the board and the network
architecture it supports. A single node can be a sensor, a J1772 signal
generator (control node) or a communications supervisor. A sensor node can
support AC, DC and current or voltage output sensors. The J1772 control
node also implements the J1772 safety protocols to prevent current flow
to EV's that are either not plugged in, not demanding charge or that have
non-standard, damaged or altered interfaces. The communications supervisor
can be used as a single-node monitor or as a regional network control node.
It uses an RJ45 plug into an SOC module that can connect over TCP/IP to
a local variablegrid program, or to the same program running remotely over
the Internet. Each board is optionally fitted with an SOC wireless communications
unit. A sensor or a control node can be addressed locally with a USB connection
to set its actual rating (actual ratings cannot be set remotely) or to monitor
Before discussing network
architecture it should be clear that variablegrid can discharge its current
sensing and EV charger control functions locally, without the use of a network.
This form of operation disregards any existing infrastructure considerations
and - within limits - only serves individual EV users. The phrase within
limits here means that any degree of clustering by such independent users
around the same load point may eventually cause it to trip or fail.
The simplest node possible
combines both sensing and control in the same board. This is applicable
to a single EV garage that also houses the main circuit breaker. A slightly
more complex arrangement, where the EV charge station is separated from
the main breaker location by obstructions that do not permit signal wiring,
requires a wireless connection between two nodes. A user that wishes to
monitor operation of the nodes remotely may add a TCP/IP communications
node to either of the above. This covers all possible arrangements at a
single user location. In an industrial or multi-unit residential setting,
each EV service equipment (EVSE) or EV charger location requires one control
node with wireless capabilities; each load point feeding multiple chargers
or in turn feeding multiple sensors, requires a sensor node with a wireless
feature. If the separation between the EVSE's and the sensor is significant
or spatially complex (concrete or cement/steel obstructions) or if the number
of EVSE's per sensor is large, there will have to be one or more intermediate
communications nodes. Finally there is one communications node attached
to a central processor that can execute a Java program - a 1 GHz net book
machine executing Windows, Unix or OSx would be typical. It is this program
that allows control over the allocated ratings described above. In a typical
regional configuration each distribution transformer is assigned a sensor
node, as is each residential customer load point; each customer also has
an EVSE control node. The regional distribution substation employs one communication
node, separated from the distribution transformer sensors by intermediate
A final note about
communications in regional networks. Although variablegrid is being tested
with only wireless communications, there may be challenges implementing
this when distribution transformers are either underground or radio frequency
(RF) shielded. A better form of communications would be power line carrier
(PLC) based. However, this technology has in the past encountered difficulties
in bridging transformer equipment. A promising new form of PLC called orthogonal
frequency division multiplexing (OFDM) may be a solution, but low-cost chips
and ancillary support seem to be still nebulous at present. Utilities have
a great degree of experience in this area. Utilities are also planning a
smart grid - if this plan includes Internet connections, then regional variablegrid
nodes could be accessed as part of smart grid services.
We have presented a
new way of matching nascent electrical grid loads to existing plant and
equipment using simple but elegant techniques with a relatively flat learning
curve and a short planning horizon. We believe that the EV's representing
these loads will soon become a large market. History has shown that such
a technology-driven market could be subject to sudden unexpected shifts
to the upside, given just one major catalytic event. We believe that the
shorter the planning horizon applied to it, the lower are the chances that
such an event will cause market dislocations in regard to existing infrastructure.
2010 IBX datasystems ltd Vancouver Canada