IEEE Power & Energy Magazine - May/June 2016 - 42

Inf
lue

nc

e"

Input
Incentive
or Price

Control
Signals for
Node's Assets

Transactive Node
* Aggregate Incentive or Quantity Estimate Inputs
from Multiple Nodes
* Calculate Output Incentive and Load Estimate
for Adjacent Nodes
* Implement Local Control of Assets at the Node

"G
lob

Local
Data and Info

al

Output
Quantity

Output
Incentive
or Price
Input
Quantity
(a)

(b)

figure 7. The PNWSGD transactive node communicating with electrical neighboring nodes.

nodes interact with electrically connected neighboring
nodes to exchange information about the quantity of energy
estimated to be produced or consumed and the cost of that
energy. a time series of information is exchanged so that the
nodes negotiate operation not only in the next interval but
optimize their operation over the time horizon of the time
series. internally, the node manages the resources under
its purview to see that their needs and flexibility are properly reflected in the negotiation. the system of nodes iterates exchanging information for each operation's time step
until the difference in incentive price and energy exchange
between each neighbor converges.
the transactive system revealed a continuum of incentives to the utilities and asset systems and engaged assets
dynamically according the each asset's capabilities and
the flexibility of the asset's owner. in addition, the project
used a simulation model of the regional system to assess the
impact of a scaled-up deployment of the transactive system.
this simulation showed that the region's peak load might
be reduced by about 8% if 30% of the region's loads were
responding to the transactive system.

TE Systems Implementations in Europe
the major european te-based coordination mechanism,
PowerMatcher, has been installed in approximately 1,000
households and industrial sites to integrate numerous small
electricity-consuming and -producing devices in the operation of the electricity infrastructure. Since its incarnation in
2004, the PowerMatcher has been implemented in five major
software versions. in a spiral approach, each version was
implemented almost from scratch and tested in simulations
and field experiments. the first three versions were research
42

ieee power & energy magazine

implementations written in the c# programming language.
the second Java version, PowerMatcher 2.0, is industrialstrength software and is open source available through the
flexiblepower alliance network (fan).
PowerMatcher puts the end customer in a central position in the smart grid. it is the end customer who owns the
domestic appliance, electrical car, and/or industrial installation that is potentially able to offer the operational flexibility
needed for a smart and sustainable electricity grid. PowerMatcher empowers the end customer to sell this flexibility to
the parties interested. this selling is completely automatic
using a piece of intelligent software installed at the premises
of, and running under the authority of, this end customer.
this so-called intelligent agent trades on behalf of the end
customer. for this trading activity on behalf of the device
owner, the uniformed data messages exchanged are stripped
of specific local information. only aggregated information
regarding power levels and prices is exchanged, protecting
the privacy of the customer.
With the european electricity sector highly unbundled
into a market subsystem trading the electricity commodity
and a network subsystem dealing with operation of the physical transmission and distribution networks, the two main
application fields of the PowerMatcher technology are found
in market operations and in active distribution network management. as the operations of these two subsystems are
highly separated in europe, PowerMatcher approaches these
as two separate control objectives. the intelligence at the
level of the customer premises, regardless of whether it is a
household, business, or industry, delivers the available flexibility as a service to both sides. this leads to the multigoal
optimization model depicted in figure 8.
may/june 2016



Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - May/June 2016

IEEE Power & Energy Magazine - May/June 2016 - Cover1
IEEE Power & Energy Magazine - May/June 2016 - Cover2
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IEEE Power & Energy Magazine - May/June 2016 - Cover3
IEEE Power & Energy Magazine - May/June 2016 - Cover4
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