Sioshansi F.P. Smart Grid: Integrating Renewable, Distributed & Efficient Energy
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a role in energy decision-making not unlike like that obtained
in the earliest days of the industry.
Smart grids and distributed energy options have a key role to
play in this, but this chapter has argued that the facilitation of
such smart energy use requires attending to far more than
matters such as technology and pricing, which currently focus
thinking about end-user engagement. These emphases assume
an economistic model of human behavior that is out of sync
not only with the commonly complementary information
campaigns focused by collective civic or environmental
concerns, but also with the complexity of real-world
consumer behavior. Some of the more dynamic and
promising decarbonization initiatives have resulted from
citizens taking matters into their own hands because of what
they regard as the inertia characteristic of more mainstream
market-driven approaches. Good examples include Danish
wind coops and the Transition Towns movement. Simply
mobilizing less carbon-intensive end-use by conventional
means, such as via smart meters, therefore risks overlooking a
far vaster potential repository of energy savings and is
unlikely to be adequate to the scale of change demanded by
the imperative to rapidly address climate change.
Facilitating smart energy use is far from straightforward,
however, ultimately requiring that the industry revisit its
organizational structures so as to turn away from what has
become a systemic supply-side bias. It will require attention
to technical, commercial, and regulatory matters and a
significant re-engineering of governance arrangements. A
notable near term opportunity likely exists in retail markets
where the facilitation of energy service companies
established, resourced, regulated, and governed with end-user
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interests in mind has the potential to put this agenda into
practice. However, in addition to the more common emphasis
on load, and, more broadly behavior, control via price, and
technology, it will be imperative that these are structured to
facilitate end-user choices regarding DE and EE options, in
particular, and the synergies they offer. Ultimately, if the ESI
does become smart, the notions of supply and demand “sides”
will become anachronistic as the system becomes more
complex in ways involving both existing categories of
consumers and providers and a variety of new ones, many of
which transcend these conventional categories.
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Chapter 3. The Ethics of Dynamic Pricing
Ahmad Faruqui[1]
The views in this chapter are those of the author and not
necessarily those of the Brattle Group. The chapter is adapted
from an article of the same title that appeared originally in
the July 2010 issue of The Electricity Journal with
permission.
Chapter Outline
Introduction 61
Background 63
Distributional Effects of Dynamic Pricing 65
Barriers to Dynamic Pricing 69
Unfairness of Flat Rate Pricing 71
Dynamic Pricing in Other Industries 73
Overcoming the Barriers to Dynamic Pricing 74
The Effect of Dynamic Pricing on Low-Income
Consumers 75
Accommodating Potential Objections 77
Conclusions 78
Appendix: Quantifying the Hedging Cost Premium 78
Traditional Cost of Service 79
Competitive Market Pricing 79
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Estimating the Hedging Cost Premium in Flat Electricity
Rates 81
Simulated Distribution of Hedging Cost Premium 82
References 82
This chapter addresses a major objection to dynamic pricing that surfaces regularly in regulatory
circles: that it is not ethical to charge prices that vary with the time of day The chapter argues that
equity requires that prices reflect costs, and thus customers who cost more to serve—such as those who
have peakier-than-average load shapes—should pay more and those who cost less to serve—such as
those with flatter-than-average load shapes—should pay less Efficiency requires that price signals
convey the scarcity value of electricity to all customers and encourage curtailment of peak loads and
their possible shifting to off-peak hours
Dynamic pricing, demand-side management, demand response
Introduction
The smart grid has the potential for bringing an immense
amount of innovation to the consumption and production of
electricity. On the consumption side, it can enable efficient
use of energy that can lower societal costs. A key enabler of
efficiency is the accurate, cost-based pricing of electricity. In
this chapter, we focus on dynamic pricing, which conveys the
time-varying nature of electricity costs to consumers.
While the idea of time-variable pricing has been widely
practiced in many markets for large commercial and industrial
customers, its application to residential and small commercial
and industrial customers is in the nascent stage. Since the
latter group of customers typically have lower load factors
than the system average, the ability to modify their load
profiles through dynamic pricing can provide substantial
benefits to customers, utilities, and society as a whole.
However, two conditions have to be met before dynamic
pricing can be successfully implemented in this market
segment.
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• First, the appropriate type of metering and
communication technology—called advanced metering
infrastructure or AMI—has to be in place. This is further
discussed in Chapter 11 by King and Strapp.
• Second, concerns about the equity of dynamic pricing
have to be resolved. It is this second condition, which
forms the focus of this chapter and also Chapter 4 by
Felder.
Concerns about equity issues have always been associated
with changes to the status quo when it comes to any form of
energy policy. Nowhere is this more evident than in the
pricing of electricity. Under prevailing rates, virtually all
small customers typically pay the same flat rate per unit of
electricity consumed regardless of the quantity or time-of-use.
But since load profiles vary by customer, the cost of serving
customers varies. It is more expensive to serve those
customers who use relatively more energy in the peak period,
and relatively less in the off-peak period, than those who use
relatively less electricity in the peak period. In other words,
the peakier-than-average customers are subsidizing the less
peakier-than-average customers, often without knowing it.
Over a period of time, for a utility with a million customers,
the amount of the subsidy can run into the hundreds of
millions of dollars. Thus, any attempt to introduce more
cost-reflective price schemes, such as dynamic pricing, would
result in the elimination of these cross-subsidies. The
beneficiaries will be delighted but those who are no longer
subsidized will be upset. The latter will find a way to their
local regulators and file a complaint. It is the nature of the
regulatory process that the complainers who show up get a
seat at the table while those who benefit but never show up
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don't. In the United States, and in fact around the world, in
places as far afield as Australia and Britain, opponents of
dynamic pricing have filed complaints that the practice is
unethical and should not be rolled out. This chapter argues the
contrary position—that flat-rate pricing is unethical and it
should be pulled back.
The chapter is organized as follows. The section
“Background” provides some key definitions, section “The
Distributional Effects of Dynamic Pricing” introduces the
distributional effects of dynamic pricing, section “The
Barriers to Dynamic Pricing” discusses the barriers to
dynamic pricing, section “The Unfairness of Flat Rate
Pricing” discusses the unfairness of flat rate pricing, section
“Dynamic Pricing in Other Industries” discusses dynamic
pricing in other industries, section “Overcoming the Barriers
to Dynamic Pricing” discusses ways of overcoming the
barriers to dynamic pricing, section “The Effect of Dynamic
Pricing on Low-Income Consumers” discusses the impact of
dynamic pricing on low-income customers, section
“Accommodating Potential Objections” reviews potential
objections to dynamic pricing, and section “Conclusions”
provides the conclusions of the chapter.
Background
Dynamic pricing is a form of time-of-use (TOU) pricing
where prices during the peak period on a limited number of
days can vary to reflect market conditions on a day-ahead or
day-of basis. One popular variant of dynamic pricing is
critical-peak pricing (CPP) in which prices during the top
40–150 hours of the year rise to previously specified levels
designed to recover the full capacity and energy cost of power
plants that run primarily during those hours. During all other
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