The Changing Decision Patterns of the Consumer in a Decentralized Smart Grid

Abstract

The well-regulated Swiss electricity market is subject to far-reaching transitions towards an intelligent network. These include a shift of responsibility, as the consumer comes to play an active role in electricity management. While previous re-search suggests that the consumer acts according to rational choice or non-cooperative game theory, this is not a sufficient justification for consumer decision-making in a socio-techno-logical environment. To this end, this empirical research elabo-rates on the decision-making patterns supported by the techno-logical change. The findings suggest that to a certain extent, diffusion of decentralized generation and storage create new responsibilities for a micro trader apart from consumption. Central for trading is the “security of supply” value and any perceived gains and losses in the value outcome entails switching between risk-averse and risk-seeking behavior.

Full text

The Changing Decision Patterns of the Consumer in a
Decentralized Smart Grid
Mario Gstrein, Stephanie Teufel
{mario.gstrein, stephanie.teufel}@unifr.ch
iimt, University of Fribourg, Switzerland
Abstract—The well-regulated Swiss electricity market is subject
to far-reaching transitions towards an intelligent network. These
include a shift of responsibility, as the consumer comes to play
an active role in electricity management. While previous re-
search suggests that the consumer acts according to rational
choice or non-cooperative game theory, this is not a sufficient
justification for consumer decision-making in a socio-techno-
logical environment. To this end, this empirical research elabo-
rates on the decision-making patterns supported by the techno-
logical change. The findings suggest that to a certain extent,
diffusion of decentralized generation and storage create new
responsibilities for a micro trader apart from consumption.
Central for trading is the “security of supply” value and any
perceived gains and losses in the value outcome entails switching
between risk-averse and risk-seeking behavior.
Index Terms—smart grid management, economic behavior,
decision making pattern.
I. INTRODUCTION
Currently, the Swiss electricity market is host to a violent
debate regarding the topics of energy efficiency, electricity
supply, sustainability, and optimization of electricity utiliza-
tion. The trigger for deliberations consist of new guiding prin-
ciples (exit of nuclear power, influx of renewable sources),
design criteria (request of an intelligent network) or other
requirements (increase in consumption through demographic
changes, electrification) [1, 2]. To meet the requirements, the
sector is undergoing a transformation, the outcome of which is
not yet known. Standards are missing and multiple new play-
ers are emerging the field [3]. Furthermore, the transformation
path inherits a great deal of uncertainty and ambiguity, which
leads to different directions and clashing opinions [4]. Scenar-
ios are useful to reduce the uncontrolled speculations and to
support the collaboration of actors, but smart grids scenarios
exhibit more decentralized architecture and the integration of
manifold small units where the end-consumer (later called the
consumer) actively influences the overall electricity manage-
ment [5, 6]. Currently, the electricity producer and distributors
(later called suppliers) enter the discussion with their “tradi-
tional” perspective and mind-set of consumers as passive
receivers as an inconvenient factor for electricity management.
Suppliers argue the overwhelming management efforts of such
units are difficult and can cause a loss of stability. Additional-
ly, extra communication infrastructure to control the grid is
expensive. Further arguments are the leverage reduction and
the profit loss through lower quantity sales. So, suppliers are
not necessarily interested in advanced consumer influences
within the supply chain as it disrupts their current business
models. However, the continuous growth of decentralized
generation and storage units provides additional opportunities
to optimize the distribution of electricity, and suppliers are
accustomed to the idea of the electricity grid decentralizing
towards individual or micro grids [7].
Some demand side management models (DSM) focus on
managing consumer loads, e.g., control of consumer devices
[8], where other models are advanced and profoundly inte-
grate the consumer [9, 10]. These models still impose the
subordinated consumer role and assume a rational human that
avoids risky options, prefer selfishness and react primarily to
monetary incentives. Studies have shown that humans behave
inconsequentially and adapt their choices violating the ration-
ality axiom [11]. To generate improved simulation models,
consumers need to be defined with other assumptions as well
as need to handle adaption of choices to determine the load
but also the price of electricity [12]. A challenge is the defini-
tion of consumer decision patterns which means dealing with
a large number of independent users with various behaviors
[13]. Therefore, this paper aims to utilize the prospect theory
[11] to determine an underlying consumer decision pattern
within a socio-technological smart grid. This paper also con-
siders the effects of consumers becoming a non-business-
driven trader and evaluates the gains and losses in the prospec-
tive value, specifically the security of supply.
II. BACKGROUND
Traditional DSM concepts are similar to well-known con-
sumer integration paradigms to reduce costs, e.g., arranging
furniture or customizing cars. Single steps, mostly at the end
or beginning of a value chain, are made the consumer’s re-
sponsibility. Though the control is still on the supplier’s side,
a smart grid goes beyond and extends the idea of a prod-user
[14]. Within a smart grid, the consumer abruptly influences
the consumption behavior, contributes to the production and
supports the stability of the grid. Electricity management hap-
pens in the masses rather than at a few isolated points [15].
Consequently, the management becomes a dispute between
EEM14 - 11th International Conference "European Energy Market", 28-30 May, 2014, Kraków, Poland
EEM14 - 11th International Conference "European Energy Market", 28-30 May, 2014, Kraków, Poland

supplier, government and consumer. However, the consumer
role experiences a major shift and still the attitudes of which
consumers enter the market are not well defined.
A. The Fourfold Pattern
The gambling metaphor following conclusions based on
elementary axioms of rationality is a popular example of deci-
sion-making; a preference for one choice outweighs the other
to maximize the benefits and minimize the costs [11]. In re-
cent years, intelligent rational decision-makers give rise to
doubts as people adapt their risk choices, which violate the
rational choice axiom [11]. People act risk-averse in some
instances and risk-seeking in others. The shortcoming leads to
the development of more sophisticated models where deci-
sion-making is applied in the matrix of the prospect changes
and probability of occurrence (Fig. 1) [11].
Figure 1. Fourfold pattern (adapted [11])
To explain the change of choice, an understanding of the
values of gains and losses is necessary [11]. According to
[11], the prospect value (also called utility) of gains and losses
are in a relation of 1:2 and hence the expected responses for
gains are weaker than for losses. Thus, people normally exhib-
it loss aversion and defend their status quo. Secondly, the
evaluation of positive or negative alterations requires a refer-
ence point distinguishing between the same utility.
On the other axis, the probability of occurrence can be
separated in possibility and certainty effects. Normally, a 5%
change of probability to win a gamble would be expected
equally regardless of whether the probability increases from
0% to 5% or from 95% to 100%, but, as shown by [11], the
decision weights are disproportional to the probability of
change and hence do not depend solely on quantitative proba-
bilities [11].The prospect of unlikely outcomes influences
someone to weight higher the change as it exists in reality.
This possibility effect explains lotteries where people pay
higher prices for a small chance to win a large prize. Another
example is paying insurance for rare events such as fire to
cover losses. On the other hand, the certainty effect causes
lower decision weights as the probability justifies. This is
attributed to the fact that people are risk-averse in the prospect
of a certain gain (Bernoulli’s expected utility) and accept less
risk to avoid disappointment. By contrast, in certain loss situa-
tions (deciding between bad options) a risk-seeking behavior
occurs in a bid to avoid losses. The negative prospect of a sure
loss is less desirable than the gamble. Overall, the diminishing
sensitivity under high probability promotes risk aversion for
gains and risk-seeking for losses. However, low probability
outweighs the sensitivity and produces the pattern of risk-
seeking for gains and risk aversion for losses (Fig. 1).
B. The Socio-Technological Environment
The described decision pattern of a simple gamble exam-
ple allows for understanding individual behavior, but for a
more elaborate discussion it is necessary to transfer these
patterns into a socio-technological system like the Swiss elec-
trical grid. The electrical grid consists of agents (e.g., suppli-
ers, distributors or consumers), the grid network (e.g., plants,
wires, transformers) and ruling (e.g., policy, mindsets, behav-
ior) which are in dynamic mutual interactions (Fig. 2) [4].
Agents adapt dynamically to the new context through a con-
tinuous process of combining rules to seek benefits [16]. In
certain situations, they act more selfishly than in others. At a
given time point a consumer follows a set of successful rules
that provide strategic scope. The different strategic patterns
allow for moving through the rugged landscape [17].
Figure 2. Three interrelated analytic dimensions (adapted [4])
There are different regimes involved that are distinguished
by social groups and related rules [4]. For example, traditional
suppliers with their artefacts (e.g., plants) operate according to
certain policies and mind-sets in a technological regime (cov-
ering demand in real-time). The transition to a smart grid
entails the entrance of new technology and agents (ICT sector)
changing existing rules and enforcing the development of new
artefacts and standards. Technological innovation not only
creates new artefacts causing alteration of the own regime but
also induces reactions in other regimes [4]. For example, the
availability of cheaper and more efficient solar panels supports
the decentralization of production [18] and permits to establish
a consumer regime in the electricity industry following their
own mind-set, beliefs and values. A consumer regime is
bounded by regulative rules (e.g., laws, sanctions) defining the
scope of decision options for individuals. For example, the
context for decentralization is supported through policy initia-
tives by regulating the barriers [19–21]. Furthermore, up to the
present defined normative rules specify that the expected
consumer’s role and actions would be seen as demand for
electricity while the supplier’s role and actions are to make
profit. Nevertheless, both parties require stability of the net-
work, and in a realistic scenario, neither party can conform to
these simple rules one hundred percent effectively nor can
parties be viewed in isolation. There is a definitive link
through supply and demand that postulates the need to culti-
vate a symbiotic relationship. In the future, the consumer will
produce and store electricity spanning both roles (producer
and consumer) and provide a closer link among actors in their
dedicated role. For example, the adoption of decentralized
storage to balance surpluses is an act of the consumer giving
up his own benefit for the grid. This is not limitless and an
expected equilibrium is reached at 38% [10].
EEM14 - 11th International Conference "European Energy Market", 28-30 May, 2014, Kraków, Poland
EEM14 - 11th International Conference "European Energy Market", 28-30 May, 2014, Kraków, Poland

How this symbiotic relation is defined depends strongly on
the evolved social norms in a smart grid. Social norms will
influence the decision processes of individuals and organiza-
tions. Therefore, the key question is how do we as a society
define the social norms for the electricity in the smart grid, in
the context of the following question. Is it a fundamental right
or can it be treated as a traded market good? The act of con-
formity to norms is to match attitudes, beliefs, and behaviors
to superior norms and thinking [22]. Social response to con-
formity is a continuum from assimilation (conversion) to ne-
glecting of norms (anti-conformity) [23] and depends strongly
on available technology which allows reaching a certain de-
gree of self-sustainability. Besides that the size of majority
following specific norms influence private values [23], and is
distinctive for regional specified norms rather national-wide
ones. Which impact these factors have is object for further
research, but the individuality provides groups of conformists
and anti-conformists.
III. THE DECENTRALIZED SMART GRID SCENARIO
A. The Consumer’s Gains and Losses of Value
Recent smart grid discussions promote money as the pri-
mary value for consumer decisions. The prospect of cheaper
electricity and the saving potential of consumption dominate
the debates. For an explanation of consumer motivations,
these points are arbitrary due to the bounded rationality of
consumers to compare prices and since the saving potential
only affects the energy price, which is one-third of the elec-
tricity bill [20]. Moreover, the feed-in compensation is a driver
for diffusion of production, but in the long term, the subven-
tion is insufficient because the consumer regards electricity
management a as non-core functionality. Thus, money is more
the result of actions rather than the driver, and the quality of
the smart grid is a cultural and ethical rather economic and
technical question [24].
The purpose of a smart grid is the optimization of electrici-
ty, and each player would have to behave according the rules
of the game [4] as a derivation jeopardizes the stability and
performance. The rules derive from the pursued targets of a
consumer and each decision is made to support the goal. So, it
becomes an intrinsic motivation. Within a smart grid five
targets exist [25]: economic performance, technical perfor-
mance, environmental friendliness, safety and product quality.
Generally, all targets should be achieved, but, agents are more
focused on some targets than others. Additionally, some tar-
gets are contradistinctive, e.g., environmental friendliness and
technical performance. For the consumer, product quality is
important; in particular, the security of supply and each gain
or loss is evaluated against it. Other targets (e.g., environmen-
tal friendliness) might also be important, especially in the
Swiss electricity market, which is characterized by stable
networks, environmental stewardship, high economic stand-
ards, trust in supplier and deep poverty rate; however, the
security of electricity originates from the basic instinct of
supplying a need [26]. Furthermore, several scenarios claim a
higher demand and reliance on electricity due to geographical,
electrification and lifestyle trends [27,28]. A shortage of elec-
tricity and the subsequent consequences in the areas of indus-
trial production, hospital, or public transport would lead to
undesirable benefit loss. For a common private user, there
might not be life-threatening reasons; rather, it likely depends
on an egocentric, comfortable attitude, e.g., the luxury of
devices being available twenty-four hours a day.
B. The Consumer Regime in a Smart Grid System
The consumer regime displays different mind-sets, beliefs,
and values and competes in the market following other param-
eters than suppliers do. Decentralized production and storage
allow for the manipulation of electricity accessibility (Fig. 3)
and support a certain degree of self-sustainability.
The decentralized electricity production offers a direct and
close source with tremendous implications for the demand,
and it directly influences the security of supply. Associated
risk averseness and risk-seeking are linked to performance of
production and the inherent limitations
1
. Production and usage
distance is tighter, and the advantage is the increasing auton-
omy of supply and prevention of interferences. The extension
of capacity, either through installing new elements or in-
creased efficiency, is regarded as a gain in the security of
supply. To determine the capacity, not only is the performance
of PV critical, but also the natural load diversity of renewa-
bles, especially in adversity periods like winter. Additionally,
inherent system limitations like sun irradiation and available
surface restrict the capacity [2, 29]. Limitations or other dis-
turbances (e.g., maintenance) foster the losses of value. Addi-
tionally, the probability between certainty and possibility
changes during the day as well as during the season due to
mentioned performance and limitation settings. Thus, it is still
necessary to interact with the grid to ensure security. Eventu-
ally, the decision pattern is strongly coupled with the charac-
teristic production curve of PV where risk averse behavior is
observed when there are surpluses and risk-seeking behavior
is observed when there are shortages of electricity.
Figure 3. Schemata of decentralized production and storage.
The idea of storage is to transfer current electrical capacity
through time for future use. The storage symbolizes for the
consumer the scarification of demand in favor of postponing
the benefit of electricity; similarly to saving money in a bank-
ing account. A decoupling of simultaneous production and
consumption occurs. Saving electricity can be achieved by
consumption reduction or by producing a surplus. The poten-
tial for additional available electricity is higher in the produc-
tion expansion than in the decrease of electricity demand. By
absorbing the surplus, storage size strongly correlates with the
1
For further discussion, we only consider a photovoltaic (PV) solution as a
potential application to install in small locations. Therefore, we assume that
the production follows the characteristic bell curve shape. The potential for
integrated PV production in Swiss buildings is estimated to be 18.410
terawatt hour per year which would cover 34.6% of the total Swiss consump-
tion [18].
EEM14 - 11th International Conference "European Energy Market", 28-30 May, 2014, Kraków, Poland
EEM14 - 11th International Conference "European Energy Market", 28-30 May, 2014, Kraków, Poland

maximum capacity of distributed generation. Any increase in
production leads to an extension of space as long as empty
storage space does not grow proportionally. In the end, an
equilibrium state is reached and any short-term alteration will
be avoided. Thus, the risk-averse or risk-seeking behavior
primarily depends on the factors of storage size and the proba-
bility of filling it.
Considering the both factors in interplay, the consumer
acts risk-aversely at high production rates when maintaining
security and options of wasting electricity or feeding it in to
the grid are unfavorable. In other words, selling electricity at
low prices during overproduction period is less beneficial as
saving it for future references. The certainty to bet on sure
thing of electricity availability outweighs the monetary reve-
nues. Any fear of loss during that time caused by unlikely
events as malfunctions may be assuaged either through back-
up solutions or by covering financial damages. Contrarily,
risk-seeking behavior is dominant mostly at low production
and low storage capacity – this implies low electricity availa-
bility. The consumer is willing to gamble for security due to a
high probability of a shortage leading to immense losses.
Avoiding sure losses the consumer investigates in different
price options. On a lower probability the market offers prom-
ising greater prospects to increase security prevail.
Risk behavior differs with the new functionality of short-
term buffer memory. The concept is to reserve a certain de-
centralized storage space exclusively to fill and empty it. For
distributors, the extra space provides possibilities to stabilize a
network’s fluctuations, whereas for producers, it is an addi-
tional possibility to transfer cheap produced electricity into
expensive periods. Several studies prove the applicability and
the potential uses, e.g., hybrid cars [30], electrical batteries
[31]. The buffer is a reduction of security from the individual
viewpoint and the object is to keep the space at a minimum.
Conversely, the short-term buffer is primarily grid-oriented
and is subject to social norms that do not consider individual-
ism. Community-related issues are treated with priority. Con-
sidering the equilibrium state and that storage cannot extend
limitlessly in the short term, the grid shows risk-seeking be-
havior at prosperity times; e.g., gambling for space is pre-
ferred as wasting cheap electricity is a loss in the future securi-
ty. Conversely, the grid behaves risk-aversely in low produc-
tion periods and neglects unnecessary supply to sustain securi-
ty for potentially graver incidents, e.g., shutdowns. How far
the consumer incorporates these considerations into decision-
making is subject to further research, but there is a conflict
between autonomy of consumer and grid requirements. In the
end, the consumer becomes a non-profit micro trader extend-
ing responsibilities. The industry thus must consider consum-
ers’ decision patterns in new pricing strategies.
C. Pricing Strategies Under Decision Patterns
Current pricing debates proclaim that “time of use”, “de-
mand bidding” or “auction-based” are adequate techniques for
smart grids [13]. Traditionally, these are based on economic
mechanisms where the price originates from production costs
or trading. So far only suppliers are involved in the price find-
ing process [20], but the consumer’s possibilities of produc-
tion and storage allow participating in this process.
The day-time demand of electricity is high at lunchtime
and lower at nighttime (Fig. 4). At prosperity phases, the de-
centralized production adds to the overall electricity volume
and replaces supplier units. Additional generated electricity
and decentralized storage bolsters security, and risk aversion is
dominant as the stored electricity is a guarantee for adversity
times. Temporarily the demand increases and causes no extra
marginal costs due to different consumer investment approach.
The consumer neglects invested costs and associated return of
investment as self-sustainability is egoistic motivated. A “no
cost” mentality takes root. Thus, already installed infrastruc-
ture is regarded as paid off and decentralized, produced elec-
tricity illustrates a zero price being favorable versus paying the
real production price.
Figure 4. Decoupling of demand and production
The changing situation creates a new competition para-
digm. First, suppliers compete on price and capture benefits
through strong divergent marginal production costs [2]. Any
response from suppliers to cover the request by activating
expensive dispatchable units must be compensated by in-
creased prices. This is unacceptable for the consumer except
if the occupancy rate of the storage is insufficient. The fear of
losses increases the acceptance of paying prices to guarantee
security, for example an insurance service to avoid electricity
shortage. Those value added services provide a new revenue
stream for suppliers and become stronger and diversified in
the future. Eventually, preferred sources for storage are either
self-produced surplus or very cheap electricity and the con-
sumer is only willing to pay higher external prices due to fear
of large losses in the prospect of a failure.
The extraction of cheap electricity from the storage occurs
during the offline period of decentralized renewables; hence
storage temporarily becomes a “production” unit. Storage
extends low electricity prices horizontally through time and
prolongs the period into high price segments. At the adversity
phase, paying higher premiums with a full storage is not op-
tional. This situation occurs when the storage bridges the
renewable offline period when production starts again. Con-
versely, partial coverage and the prospect of losses in security
support risk-seeking leading to a gamble between options.
During offline phases, the consumer accepts the market price
or value added services that guarantee security. Those services
are offered on a higher premium which attracts other suppliers
causing a different competition field. Meanwhile, insufficient
services or a boost of market prices creates a stimulus to invest
in more decentralized units [32] and augments the production-
storage capacity. This can lead to consumers investing in more
storage as the decentralized generation performs solely to
EEM14 - 11th International Conference "European Energy Market", 28-30 May, 2014, Kraków, Poland
EEM14 - 11th International Conference "European Energy Market", 28-30 May, 2014, Kraków, Poland

absorb cheap external production. A counter effect on storage
capacity is the short-term buffer memory. Any agreement to
allocate size for the system purposes expects a reimbursement
at least high as the transportation fee.
Eventually, the electricity market will undergo a transfor-
mation similar to the telecommunication sector where the
basic element (calls) was not profitable and services like data
exchange became lucrative. Therefore, the pricing strategy
depends strongly on the success of service definitions and the
understanding of consumer’s requirements for supporting risk-
averse and risk-seeking behavior.
IV. CONCLUSION
Decentralized units represent many challenges for electric-
ity suppliers. A major challenge is the adoption of novel per-
spectives, skills and capabilities in response to the changing
consumer role. The consumer acts like a micro trader and
evaluates gains and losses of value outcome. The value is
strongly related to security of supply and hence in certain
situations the consumer shows risk averseness and can shift to
risk-seeking behavior in another moment. By understanding
the mechanism of decision-making and a consumer-centric
focus, suppliers have the ability to create new tariff structures
and value added services, e.g., carefree packages. Such ser-
vices offer the opportunity to replace the financial losses, as
quantity will be decoupled from profit. Another opportunity
for business is the integration of numerous small units, and
companies can distinguish themselves by the quality of effi-
cient electricity distribution with the grid. Additionally, the
management of cooperation among consumers in micro grids,
providing the infrastructure for generation and exchange of
electricity among the members [9, 33, 34] is another area
where opportunities exist.
This article demonstrates that the decision-making patterns
of consumers depend on probability and the perceived gains or
losses of the outcome. The outcome is contingent on the most
important consumer value, security of supply, rather than on
economic factors. In conclusion, the consumer behaves in a
risk-averse manner in times of electricity prosperity and in a
risk-seeking manner in times of electricity scarcity. Such be-
havior is strongly influenced by the technological diffusion of
generation and storage. This article provides a first step to
understand consumer decision-making and is a direction to
improve smart grid simulation models. However, future re-
search is still necessary to inquire a more detailed approach.
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[34] ABB Schweiz and Elektrizitätswerk Zürich, EKZ und ABB nehmen
grösste Batterie der Schweiz in Betrieb. Zürich, Switzerland, March
21st 2012.
EEM14 - 11th International Conference "European Energy Market", 28-30 May, 2014, Kraków, Poland
EEM14 - 11th International Conference "European Energy Market", 28-30 May, 2014, Kraków, Poland