WHITE PAPER
Achieving Decentralized Coordination
In the Electric Power Industry
Using dynamic pricing and digital technology to move from centralized
control to decentralized coordination. www.UtilitiesProject.com/10827
F
or the past century, the dominant
business and regulatory paradigms
in the electric power industry have
been centralized economic and physical
control. The ideas presented here and
in my forthcoming book, Deregulation,
Innovation, and Market Liberalization:
Electricity Restructuring in a Constantly
Evolving Environment (Routledge, 2008),
comprise a different paradigm – decen
tralized economic and physical coordi
nation – which will be achieved through
contracts, transactions, price signals
and integrated intertemporal wholesale
and retail markets. Digital communica
tion technologies – which are becom
ing ever more pervasive and afford
able – are what make this decentralized
coordination possible. In contrast to
the “distributed control” concept often
invoked by power systems engineers (in
which distributed technology is used to
enhance centralized control of a system),
“decentralized coordination” repre
sents a paradigm in which distributed
agents themselves control part of the
system, and in aggregate, their actions
produce order: emergent order. [1]
Dynamic retail pricing, retail product
differentiation and complementary end
use technologies provide the foundation
for achieving decentralized coordination
in the electric power industry. They bring
timely information to consumers and
enable them to participate in retail market
processes; they also enable retailers to
discover and satisfy the heterogeneous
preferences of consumers, all of whom
have private knowledge that’s unavailable
to firms and regulators in the absence of
such market processes. Institutions that
facilitate this discovery through dynamic
pricing and technology are crucial for
achieving decentralized coordination.
Thus, retail restructuring that allows
dynamic pricing and product differentia
tion, doesn’t stifle the adoption of digital
technology and reduces retail entry bar
riers is necessary if this value-creating
decentralized coordination is to happen.
This paper presents a case study – the
“GridWise Olympic Peninsula Testbed
Demonstration Project” – that illustrates
how digital end-use technology and
dynamic pricing combine to provide value
to residential customers while increasing
network reliability and reducing required
infrastructure investments through
decentralized coordination. The availabil
ity (and increasing cost-effectiveness)
of digital technologies enabling consum
ers to monitor and control their energy
use and to see transparent price signals
has made existing retail rate regulation
WRITTEN BY
Lynne Kiesling, Northwestern University
Lynne Kiesling is a senior lecturer in the Department of Economics and the Kellogg School of Man
agement at Northwestern University, a faculty member at the Northwestern Institute on Complex
Systems and a faculty affiliate at the Center for the Study of Industrial Organization. She is also a
member of the GridWise Architecture Council and has written or co-written numerous academic
journal articles and policy studies.
obsolete. Instead, the policy recommen
dation that this analysis implies is that
regulators should reduce entry barriers
in retail markets and allow for dynamic
pricing and product differentiation, which
are the keys to achieving decentralized
coordination.
THE KEYS: DYNAMIC PRICING,
DIGITAL TECHNOLOGY
Dynamic pricing provides price signals
that reflect variations in the actual costs
and benefits of providing electricity at
different times of the day. Some of the
more sophisticated forms of dynamic pric
ing harness the dramatic improvements
in information technology of the past 20
years to communicate these price signals
to consumers. These same technological
developments also give consumers a tool
for managing their energy use, in either
manual or automated form. Currently,
with almost all U.S. consumers (even
industrial and commercial ones) paying
average prices, there’s little incentive for
consumers to manage their consumption
and shift it away from peak hours. This
inelastic demand leads to more capital
investment in power plants and transmis
sion and distribution facilities than would
occur if consumers could make choices
based on their preferences and in the face
of dynamic pricing.
Retail price regulation stifles the eco
nomic processes that lead to both static
and dynamic efficiency. Keeping retail
prices fixed truncates the information flow
between wholesale and retail markets,
and leads to inefficiency, price spikes and
price volatility. Fixed retail rates for elec
tric power service mean that the prices
www.UtilitiesProject.com
U8_Ch2_final.indd 79
p79
5/2/08 9:12:21 AM
CHAPTER 2
OPERATIONS
individual consumers pay bear little or
no relation to the marginal cost of provid
ing power in any given hour. Moreover,
because retail prices don’t fluctuate, con
sumers are given no incentive to change
their consumption as the marginal cost
of producing electricity changes. This
severing of incentives leads to inefficient
energy consumption in the short run and
also causes inappropriate investment in
generation, transmission and distribu
tion capacity in the long run. It has also
stifled the implementation of technologies
that enable customers to make active
consumption decisions, even though com
munication technologies have become
ubiquitous, affordable and user-friendly.
Dynamic pricing can include time-of-use
(TOU) rates, which are different prices in
blocks over a day (based on expected
wholesale prices), or real-time pricing
(RTP) in which actual market prices are
transmitted to consumers, generally in
increments of an hour or less. A TOU rate
The 2007 Galvin Electricity Initiative
report “The Path to Perfect Power: New
Technologies Advance Consumer Control”
catalogs a variety of end-user technolo
gies (from price-responsive appliances to
wireless home automation systems) that
can communicate electricity price signals
to consumers, retain data on their con
sumption and be programmed to respond
automatically to trigger prices that the
consumer chooses based on his or her
preferences. [2] Moreover, the two-way
communication advanced metering infra
structure (AMI) that enables a retailer and
consumer to have that data transparency
is also proliferating (albeit slowly) and
declining in price.
Dynamic pricing and the digital tech
nology that enables communication of
price information are symbiotic. Dynamic
pricing in the absence of enabling technol
ogy is meaningless. Likewise, technology
without economic signals to respond to
is extremely limited in its ability to coor
ances that can be programmed to behave
differently based on changes in the retail
price of electricity, these products and
services provide customers with an oppor
tunity to make better choices with more
precision than ever before. In aggregate,
these choices lead to better capacity utili
zation and better fuel resource utilization,
and provide incentives for innovation to
meet customers’ needs and capture their
imaginations. In this sense, technological
innovation and dynamic retail electricity
pricing are at the heart of decentralized
coordination in the electric power network.
EVIDENCE
Led by the Pacific Northwest National
Laboratory (PNNL), the Olympic Peninsula
GridWise Testbed Project served as a dem
onstration project to test a residential net
work with highly distributed intelligence
and market-based dynamic pricing. [4]
Washington’s Olympic Peninsula is an area
of great scenic beauty, with population
FIXED RETAIL RATES for electric power service mean
that the prices consumers pay bear little or no relation
to the marginal cost of providing power in any given hour.
typically applies predetermined prices to
specific time periods by day and by season.
RTP differs from TOU mainly because RTP
exposes consumers to unexpected varia
tions (positive and negative) due to
demand conditions, weather and other
factors. In a sense, fixed retail rates and
RTP are the end points of a continuum of
how much price variability the consumer
sees, and different types of TOU systems
are points on that continuum. Thus, RTP is
but one example of dynamic pricing. Both
RTP and TOU provide better price signals
to customers than current regulated aver
age prices do. They also enable companies
to sell, and customers to purchase, electric
power service as a differentiated product.
TECHNOLOGY’S ROLE
IN RETAIL CHOICE
Digital technologies are becoming increas
ingly available to reduce the cost of send
ing prices to people and their devices.
p80
U8_Ch2_final.indd 80
dinate buyers and sellers in a way that
optimizes network quality and resource
use. [3] The combination of dynamic pric
ing and enabling technology changes the
value proposition for the consumer from
“I flip the switch, and the light comes on”
to a more diverse and consumer-focused
set of value-added services.
These diverse value-added services
empower consumers and enable them to
control their electricity choices with more
granularity and precision than the envi
ronment in which they think solely of the
total amount of electricity they consume.
Digital metering and end-user devices
also decrease transaction costs between
buyers and sellers, lowering barriers to
exchange and to the formation of particu
lar markets and products.
Whether they take the form of building
control systems that enable the consumer
to see the amount of power used by each
function performed in a building or appli
centers concentrated on the northern
edge. The peninsula’s electricity distribu
tion network is connected to the rest of
the network through a single distribution
substation. While the peninsula is experi
encing economic growth and associated
growth in electricity demand, the natural
beauty of the area and other environ
mental concerns served as an impetus for
area residents to explore options beyond
simply building generation capacity on the
peninsula or adding transmission capacity.
Thus, this project tested how the com
bination of enabling technologies and
market-based dynamic pricing affected
utilization of existing capacity, deferral
of capital investment and the ability of
distributed demand-side and supply-side
resources to create system reliability.
Two questions were of primary interest:
1) What dynamic pricing contracts do
consumers find attractive, and how does
enabling technology affect that choice?
Innovating for the Future
5/2/08 9:12:23 AM
WHITE PAPER
2) To what extent will consumers choose
to automate energy use decisions?
The project – which ran from April
2006 through March 2007 – included
130 broadband-enabled households with
electric heating. Each household received
a programmable communicating ther
mostat (PCT) with a visual user interface
that allowed the consumer to program
the thermostat for the home – specifically
to respond to price signals, if desired.
Households also received water heaters
equipped with a GridFriendly appliance
(GFA) controller chip developed at PNNL
that enables the water heater to receive
price signals and be programmed to
respond automatically to those price sig
nals. Consumers could control the sensi
tivity of the water heater through the PCT
settings.
These households also participated in a
market field experiment involving dynamic
pricing. While they continued to purchase
energy from their local utility at a fixed,
discounted price, they also received a
cash account with a predetermined bal
ance, which was replenished quarterly.
The energy use decisions they made
would determine their overall bill, which
was deducted from their cash account,
and they were able to keep any difference
as profit. The worst a household could do
was a zero balance, so they were no worse
off than if they had not participated in the
experiment. At any time customers could
log in to a secure website to see their cur
rent balances and determine the effective
ness of their energy use strategies.
On signing up for the project, the
households received extensive informa
tion and education about the technologies
available to them and the kinds of energy
use strategies facilitated by these technol
ogies. They were then asked to choose a
retail pricing contract from three options:
a fixed price contract (with an embed
ded price risk premium), a TOU contract
with a variable critical peak price (CPP)
component that could be called in periods
of tight capacity or an RTP contract that
would reflect a wholesale market-clearing
price in five-minute intervals. The RTP was
determined using a uniform price double
auction in which buyers (households and
commercial) submit bids and sellers sub
mit offers simultaneously. This project
represented the first instance in which a
double auction retail market design was
tested in electric power.
The households ranked the contracts
and were then divided fairly evenly among
the three types, along with a control group
that received the enabling technologies
and had their energy use monitored but
did not participate in the dynamic pric
ing market experiment. All households
received either their first or second
choice; interestingly, more than two-thirds
of the households ranked RTP as their first
choice. This result counters the received
wisdom that residential customers want
only reliable service at low, stable prices.
According to the 2007 report on the
project by D.J. Hammerstrom (and others),
on average participants saved 10 percent
on their electricity bills. [5] That report
also includes the following findings about
the project:
Result 1. For the RTP group, peak con
sumption decreased by 15 to 17 percent
relative to what the peak would have
been in the absence of the dynamic pric
ing – even though their overall energy
consumption increased by approximately
4 percent. This flattening of the load dura
tion curve indicates shifting some peak
demand to nonpeak hours. Such shifting
increases the system’s load factor, improv
ing capacity utilization and reducing the
need to invest in additional capacity, for a
given level of demand. A 15 to 17 percent
reduction is substantial and is similar in
magnitude to the reductions seen in other
dynamic pricing pilots.
After controlling for price response,
weather effects and weekend days, the
RTP group’s overall energy consumption
was 4 percent higher than that of the fixed
price group. This result, in combination
with the load duration effect noted above,
indicates that the overall effect of RTP
dynamic pricing is to smooth consumption
over time, not decrease it.
Result 2. The TOU group achieved both
a large price elasticity of demand (-0.17),
based on hourly data, and an overall
energy reduction of approximately 20 per
cent relative to the fixed price group.
After controlling for price response,
weather effects and weekend days,
the TOU group’s overall energy con
sumption was 20 percent lower than
that of the fixed price group. This result
indicates that the TOU (with occasional
critical peaks) pricing induced overall
conservation – a result consistent with
the results of the California SPP proj
ect. The estimated price elasticity of
demand in the TOU group was -0.17,
which is high relative to that observed
in other projects. This elasticity suggests
that the pricing coupled with the enabl
ing end-use technology amplifies the
price responsiveness of even small resi
dential consumers.
Despite these results, dynamic pricing
and enabling technologies are proliferat
ing slowly in the electricity industry.
Proliferation requires a combination of
formal and informal institutional change
to overcome a variety of barriers. And
while formal institutional change (pri
marily in the form of federal legislation)
is reducing some of these barriers, it
remains an incremental process. The
traditional rate structure, fixed by state
regulation and slow to change, presents
a substantial barrier. Predetermined load
profiles inhibit market-based pricing by
ignoring individual customer variation
and the information that customers can
communicate through choices in response
to price signals. Furthermore, the per
sistence of standard offer service at a
discounted rate (that is, a rate that does
not reflect the financial cost of insurance
against price risk) stifles any incentive
customers might have to pursue other
pricing options.
The most significant – yet also most
intangible and difficult-to-overcome –
obstacle to dynamic pricing and enabling
technologies is inertia. All of the primary
stakeholders in the industry – utilities,
regulators and customers – harbor status
quo bias. Incumbent utilities face incen
tives to maintain the regulated status quo
as much as possible (given the economic,
technological and demographic changes
surrounding them) – and thus far, they’ve
been successful in using the political pro
cess to achieve this objective.
www.UtilitiesProject.com
U8_Ch2_final.indd 81
p81
5/2/08 9:12:23 AM
CHAPTER 2
OPERATIONS
Customer inertia also runs deep
because consumers have not had to think
about their consumption of electricity or
the price they pay for it – a bias consumer
advocates generally reinforce by arguing
that low, stable prices for highly reliable
power are an entitlement. Regulators and
customers value the stability and predict
ability that have arisen from this vertically
integrated, historically supply-oriented and
reliability-focused environment; however,
what is unseen and unaccounted for is the
opportunity cost of such predictability
– the foregone value creation in innovative
services, empowerment of customers to
manage their own energy use and use of
including consumer surplus? In aggregate,
do these distributed actions create emer
gent order in the form of system reliability?
Answering these questions requires
thinking about the diffuse and private
nature of the knowledge embedded in the
network, and the extent to which such a
network becomes a complex adaptive sys
tem. Technology helps determine whether
decentralized coordination and emergent
order are possible; the dramatic transfor
mation of digital technology in the past
few decades has decreased transaction
costs and increased the extent of feasible
decentralized coordination in this industry.
Institutions – which structure and shape
ENDNOTES
1. Order can take many forms in a complex sys
tem like electricity – for example, keeping the
lights on (short-term reliability), achieving
economic efficiency, optimizing transmission
congestion, longer-term resource adequacy
and so on.
2. Roger W. Gale, Jean-Louis Poirier, Lynne
Kiesling and David Bodde, “The Path to Perfect
Power: New Technologies Advance Consumer
Control,” Galvin Electricity Initiative report
(2007). www.galvinpower.org/resources/
galvin.php?id=88
3. The exception to this claim is the TOU con
tract, where the rate structure is known in
advance. However, even on such a simple
DYNAMIC PRICING in the absence of enabling
technology is meaningless. Likewise, technology
without economic signals to respond to is
extremely limited in its ability to coordinate
buyers and sellers in a way that optimizes net
work quality and resource use.
double-sided markets to enhance market
efficiency and network reliability. Compare
this unseen potential with the value cre
ation in telecommunications, where even
young adults can understand and adapt to
cell phone-pricing plans and benefit from
the stream of innovations in the industry.
CONCLUSION
The potential for a highly distributed,
decentralized network of devices auto
mated to respond to price signals creates
new policy and research questions. Do
individuals automate sending prices to
devices? If so, do they adjust settings, and
how? Does the combination of price effects
and innovation increase total surplus,
p82
U8_Ch2_final.indd 82
the contexts in which such processes
occur – provide a means for creating this
coordination. And finally, regulatory insti
tutions affect whether or not this coordi
nation can occur.
For this reason, effective regulation
should focus not on allocation but rather
on decentralized coordination and how to
bring it about. This in turn means a focus
on market processes, which are adaptive
institutions that evolve along with tech
nological change. Regulatory institutions
should also be adaptive, and policymakers
should view regulatory policy as work in
progress so that the institutions can adapt
to unknown and changing conditions and
enable decentralized coordination. ■
dynamic pricing contract, devices that allow
customers to see their consumption and
expenditure in real time instead of waiting for
their bill can change behavior.
4. D.J. Hammerstrom et. al, “Pacific Northwest
GridWise Testbed Demonstration Projects,
volume I: The Olympic Peninsula Project”
(2007). http://gridwise.pnl.gov/docs/op_
project_final_report_pnnl17167.pdf
5. Ibid.
WEBLINK
>>>>>>
More information and additional
material can be found online at
www.UtilitiesProject.com/10827
Innovating for the Future
5/2/08 9:12:25 AM