An Electricity Market Game using Agent-based Gaming Technique for
Understanding Energy Transition
Setsuya Kurahashi
1
and Wander Jager
2
1
Graduate School of Business Sciences, University of Tsukuba, 3-29-1 Otsuka, Bunkyo, Tokyo, Japan
2
University College Groningen, Hoendiepskade 23/24, 9718 BG Groningen, The Netherlands
Keywords:
Electricity Market, Two-sided Market, Agent-based Gaming.
Abstract:
The Electricity Market in Japan has been an oligopolistic market since the previous century, but it will be
a liberalised competitive market soon due to a policy change. It is supposed to provide wholesale power
markets. Therefore, it has high possibilities to become two-sided markets with strong wholesalers. The goal
of this study is to clarify decisive factors for making decision of energy selection based on human competitive
and collaboration behaviour to be helpful for an incentive design of energy markets. For the purpose, two
hypotheses were set in the experiment. First is that energy transition to renewable source is achieved by
players while keeping their profit. Second is that aggregators have ability to control the energy market through
the share of consumers’ power market as well as other two-sided markets. Our experiment confirmed that
the energy orientation of electric power consumers could give a significant influence on power generation
investment of electric power suppliers, and the risk of nuclear energy was underestimated. And the first
hypothesis was adopted and the second was rejected by the experiments through the agent-based gaming.
1 INTRODUCTION
The electricity crisis caused by the huge earthquake
in Japan 2011, clarified that traditional electricity sys-
tems on a one-sided energy market are inadequate for
maintaining safe and stable electricity supply at low
cost. Given such an issue, the government of Japan
has clearly announced that it would realise liberation
for participation of power operators into small con-
sumers such as general households in 2016. It would
launch unbundling of power generation and distribu-
tion during the period around 2018 to 2020. These
policies might bring about advancement of innovation
with a wide variety of enterprises participating and in-
creasing the use of renewable energy.
This attempt can encourage a wide variety of en-
terprises into this market; however, it also entails
some risks such as instability of electricity markets
and market monopolies or oligopolies. These are due
to a two-sided energy-market on a de facto standard
platform as well as e-tailer and e-marketplaces.
The purpose of this research is to achieve an ef-
ficient market while taking into consideration elec-
tricity market liberalisation. Additionally, this re-
search studies incentivemechanisms for a competitive
electricity markets for enabling energy transformation
from fossil energy to renewable energy. In this re-
search, social systems and infrastructures are referred
to as the electricity market platform. Here, the fo-
cus is placed on aggregators that bring electricity con-
sumers together as a community. And it is also fo-
cused on imbalance settlement which is implemented
among power distribution operators and power pro-
ducers/retailers for the purpose of supply and demand
adjustments for renewable energy.
Through this research, by applying the agent-
based gaming method, our goal is to propose an in-
centive design. It promotes innovation such as elec-
tricity supply and demand adjustments, stable sup-
ply, and dissemination of renewable energy through
free decision-making by market participants includ-
ing consumers and power operators. In a new lib-
eralised energy market old and new energy compa-
nies will base their actions and plans on the behaviour
of their competitors as well as on the (expected) re-
sponses of the consumer market. We propose using
an agent based simulation of a market of consumers
as a laboratory setting to study the behaviour of hu-
man decision-makers in an energy transition game.
314
Kurahashi S. and Jager W.
An Electricity Market Game using Agent-based Gaming Technique for Understanding Energy Transition.
DOI: 10.5220/0006247703140321
In Proceedings of the 9th International Conference on Agents and Artificial Intelligence (ICAART 2017), pages 314-321
ISBN: 978-989-758-219-6
Copyright
c
2017 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
2 RESEARCH BACKGROUND
As clearly demonstrated by examples of the com-
munications and Internet markets, the liberalisation
of participation by many enterprises can create new
markets while bringing about many benefits such as
increase in business opportunities, diversification of
services, and lowering of fees. On the other hand,
leaving everything to free market competition pre-
vents products and services with higher transaction
cost from being transacted. It results in causing mar-
ket failure. Renewable energy is easily affected by the
natural environment, making the supply-and-demand
balance difficult to adjust, while power generation
cost at the same time is expensive. This increases
transaction costs. Therefore, it is overly optimistic to
believe that the price mechanisms within the market
could for sure promote and disseminate these above-
described power sources.
On the other hand, in the ICT market which has
two sides, consumers and suppliers, platform compe-
titions are being developed on a global basis. These
are attractive on the price side, the supply side, and
the service side. This two-sided market mechanism
has been analysed by using mathematical models
(Boudreau and Hagiu, 2009)(Unno and Xu, 2012).
In addition, recently, studies regarding real-time dy-
namic pricing based on agent modeling and studies
regarding incentive mechanisms (Bacon, 2012) have
been made.
Smart grid is expected to gain profits from real-
time dynamic pricing. This pricing system enables
both power consumers and power companies to re-
flect changes in wholesale prices on the demand side
(Samadi et al., 2011). Conversely, auction-based
power pricing is not an uncommon concept. How-
ever, the demand side which participates in auction
sessions is based on renewable energy such as solar
energy. Therefore, electricity generated is very vari-
able.
Required studies include those of electricity plat-
form design which maximises social welfare while
considering the electricity market as a two-sided mar-
ket, and those focusing not on a single market, but on
multiple competitive electricity markets. Mechanism
design in dynamical systems and agent-based gaming
models are considered to be the best and suitable in
order to optimise participation incentives under such
circumstances.
Traditional economic models describing changes
in markets are less suitable to understand the dynam-
ics of interaction in a two-sided market. This is be-
cause these models do not account for the emergent
processes that can happen when multiple actors are
interacting. Agent based simulation is a suitable tool
to study the dynamics in markets with many interact-
ing actors. When the agent based model is suitable for
policy makers to experiment with managing the sys-
tem, a serious game context can be created to study
both the impact of decisional strategies as well as the
decision making process of the managers. They can
be confronted with different situation, and it can be
systematically studied what type of management and
which policies are the most effective in guiding such
a transition in the energy market.
An important challenge here is the valid modelling
of the population of agents in the model. Realistic
agent behaviour is important to make an agent based
game a tool that provides applicable insights(Jager
and Vegt, 2015).
In two-sided markets with consumers and suppli-
ers, platform competitions are being developed on a
global basis which are attractive on the price side,
the supply side, and the service side. This two-sided
market mechanism has been analysed by using math-
ematical models. However, mathematical models
were applied to analyse market mechanisms with only
one or two players(Rochet and Tirol, 2003)(Rochet
and Tirol, 2006)(Sannikov, 2008). Therefore, mathe-
matical models have limitations in analysing mecha-
nisms with multiple diversified players such as con-
sumers. In addition, studies regarding ABM-based
dynamic pricing and incentive mechanisms have been
in progress. In these studies, however, the decision-
making process of agents was controlled by an algo-
rithm. For this reason, there are limitations in these
studies to analyse complicated decision-making pro-
cesses taking into account movements of actual envi-
ronments, human behaviour and complex energy con-
sumers markets, and corporate management condi-
tions. Based on these traditional models, in this re-
search, we made an attempt to build a two-sided mar-
ket model for electricity markets by applying agent-
based gaming.
Serious game sessions have been held in re-
cent conferences regarding social simulation (ESSA,
2015). As for the traditional approaches of serious
games, however, societies and environments which
served as backgrounds were defined by game design-
ers. Therefore, they often tend to have determinis-
tic characteristics. Real societies, where participat-
ing agents are actually thrown into interactions with
other agents or a non-linear process, have the prop-
erty of complex adaptive systems. Electricity markets
are expected to be such a circumstance as mentioned
above. This requires gaming with an assumption of
complex adaptive systems.
Afterward, section 3 describes the research objec-
An Electricity Market Game using Agent-based Gaming Technique for Understanding Energy Transition
315
tives, and section 4 explains the outline of the energy
conversion model. Section 5 gives a description of
experimental environment and section 6 discusses the
experimental results, while section 7 summarises this
research.
3 RESEARCH OBJECTIVES
The objective is to analyse what players can obtain
market ascendancy under what kind of conditions in
an electricity market. In order to achieve electricity
platform design which maximises social welfare, this
research focuses on aggregators and imbalance ad-
justment. Currently, utilisation of market functions
associated with electricity supply and demand adjust-
ment has been considered, with a proposal for estab-
lishing a new one-hour-ahead market and a real-time
market in order for electricity distribution operators,
power producers and retailers to procure the most ef-
ficient regulated power supplies from these markets
(Ministry of Economy, Trade and Industry, 2013).
Use of these market prices in imbalance settlement for
renewable energy can secure transparency and fair-
ness. This should have positive influence on the ef-
ficiency of electricity markets and the promotion of
renewable energy dissemination (Fig.1).
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Figure 1: Imbalance settlement and the electricity market.
Market participants are diverse agents and the
market itself also consists of multiple competitive
platforms; therefore, these things are considered to
be multi-agent and multi-purpose optimisation prob-
lems. Solving such problems requires a multi-agent
incentive mechanism, while an appropriate approach
is agent-based modelling (ABM). On the other hand,
when the decision-making process of power suppli-
ers and aggregators is left to machine agents, the al-
gorithm’s capability could affect the decision-making
results. However, a human-agent participatory gam-
ing method which has been used for serious games
is more likely to obtain the decision-making results
that are close to the actual results when human agents
as players organically connect and consider informa-
tion which they obtain from models. In traditional se-
rious games, however, environmental changes as the
background are determined in a deterministic manner.
This fact makes it difficult to reproduce the compli-
cated movements of an electricity market.
Given that, through this paper, progress has been
made in our present research based on the follow-
ing two points while connecting ABM and seri-
ous games and introducing an agent-based gaming
method which makes it possible to design multi-agent
and multi-purpose models.
3.1 Analysis of Market Structure which
Brings about Energy Conversion
System design in electricity markets have a significant
influence on generation of market rulers. Our addi-
tional goal is to design a system which is effective
for energy conversion to renewable energy. Design
of a mechanism for achieving stable electricity sup-
ply equilibrium based on utilisation of a wide variety
of energy sources needs to play the role of a platform
for maximising the utility for both electricity suppli-
ers and consumers. In order to analyse these struc-
tures, we use ABM.
3.2 Comparative Analysis of
Decision-making Structures
While expanding electricity consumers and power
producers to multiple agents, their behaviour is ex-
pressed by using a multi-agent model. With that,
we conducted comparative analysis on the decision-
making results obtained by introducing participa-
tory agent-based gaming. By analysing differences
brought by each individual agent, we evaluated strate-
gies of imbalance adjustment incentives for electric-
ity, and government subsidies and tax rate policies. In
addition, observing the targeted phenomenonnot only
from a single viewpoint, but from several different
viewpoints, in order that each phenomenon can be ex-
pressed accurately by using only one model (Grimm,
2005).
4 ENERGY CONVERSION
GAMING MODEL
In energy conversion gaming models based on agent-
based gaming models (Fig.2), in an electricity market
ICAART 2017 - 9th International Conference on Agents and Artificial Intelligence
316
where power producer players and aggregator play-
ers participate, power producers make their decisions
based on electricity sale prices, advertising invest-
ments, and plans for power-generation facilities. Sale
prices are adjusted based on imbalance settlement in
supply and demand with electricity distribution oper-
ators.
On the other hand, we can expect that mar-
keters, brokers, local public organisations, and non-
profit groups which organise electric needs of con-
sumers in order to provide energy management ser-
vices effectively will participate in electricity mar-
kets. They play their roles as aggregators which serve
as a bridge between retail players and general house-
holds/operators. Aggregators are expected to provide
a wide variety of services based on advanced energy
management systems by using smart meters, while
developingdemand responses and negawatt
1
services.
This might allow aggregators to dominate market cir-
culation in a two-sided market, and to have the power
to determine not only the price, but also to profit allo-
cation. This possibility brings the same structure as IT
markets including music distribution and smartphone
app markets, where fierce competition for dominating
markets can be caused. Therefore, it is extremely im-
portant to study on market system design which can
promote development of renewable energy and sound
market competition.
The proposed agent-based gaming model is based
on the government plan of energy market reform in
Japan(NRE, 2015).In this gaming model, the actual
participants participate in the game playing the roles
of power producers, electricity retailers, and aggrega-
tors. In addition, computer agents also participate in
the market autonomously as a number of consumer
agents. The government agents conduct imbalance
settlement based on the predetermined market rules.
Based on this gaming model, the game participants
can experience the complexity of this market and they
can design a market system while verifying the effec-
tiveness of the system designed. Our ultimate goal is
to verifywhether real-time characteristics are satisfied
by conducting simulation based on the actual climate
data in order to develop further verification.
4.1 Model Outline
According to the ODD protocol, the section be-
low describes the outline of the model. The ODD
(Overview, Design concepts, and Details) proto-
col was proposed to standardise the published de-
scriptions of individual-based and ABMs(Grimm,
1
Negawatt power is a theoretical unit of power repre-
senting an amount of energy (measured in watts) saved.
2005). The primary objectives of ODD are to make
model descriptions more understandable and com-
plete, thereby making ABMs less subject to criticism
for being irreproducible.
In this model, ’Entities’ are electricity suppliers,
aggregators, the government, and consumers. ’State
variables’ are defined as follows:
Electricity suppliers
Sale prices, discount rates for major clients, in-
vestments (advertising, thermal, nuclear, and re-
newable energy), costs (thermal, nuclear, and re-
newable energy), carbon generation rates (ther-
mal, nuclear, and renewable energy), power gen-
eration amounts (thermal, nuclear, and renewable
energy), operator attractiveness, carbon gas gen-
erated, and rate of power failure occurrences
Aggregators
Sale prices, advertising investment, the number
of operators that purchase electricity, and energy
proportions (thermal, nuclear, and renewable en-
ergy)
Government
Imbalance prices, business tax rates, carbon tax
rates, and renewable energy investments
Consumers
Norm effect parameters, information effect pa-
rameters, network generation parameters, and the
number of consumers
’Process overview and scheduling’ are as below.
Suppliers generate power, and sell it to consumers and
aggregators. While taking into account the environ-
ment of consumers and their intentions toward prices,
suppliers determine the power generation proportions
of thermal power generation, nuclear power gener-
ation, and renewable energy, electricity prices (dis-
counts for general/major clients), and advertising in-
vestments in order to maximise their own profits. In-
crease in the proportion of renewableenergy increases
the power failure probability, resulting in paying the
imbalance cost. Additionally, their own competitive-
ness declines in proportion to the power failure prob-
ability.
Aggregators purchase electricity with discounts
for major clients from suppliers, while re-selling the
electricity to consumers. While taking into account
the environment of consumers and their intentions to-
ward prices, aggregators determine the power gener-
ation proportions of thermal power generation, nu-
clear power generation, and renewable energy, elec-
tricity prices (for general clients), and advertising in-
vestments.
While considering their own preferences for elec-
tric power and electric power charges, consumers pur-
An Electricity Market Game using Agent-based Gaming Technique for Understanding Energy Transition
317
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)'*$#(*+',$-%,$(.%#/$&(
Imbalance
adjustment
(
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Supply plan
Discount price
Two-sided market
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Business tax
Carbon tax
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Consumers
Selling price
Advertisement
Power plant investment
(Thermal/nuclear/renewable)
Blackout probability
Selling price
Advertisement
Balance between
environment and cost
Figure 2: Energy conversion gaming model.
chase electric power from appropriate suppliers. Con-
sumers are network-linked with their acquaintances
receiving the norm effect. The government deter-
mines imbalance prices, business taxes, carbon taxes,
and renewable energy subsidies. Based on these, the
total amount of carbon gas generated and the entire
probability of power failure are determined. The goal
of the government is to optimise these variables.
Within the game, the degree of market domi-
nance by players and decision-making of consumers
on neighbouring networks are generated as ’Emer-
gence’.
In gaming models, motivations of players are
defined that supplier and aggregator human players
make their decisions so that they maximise their prof-
its while referring to decision-making status of other
participants as ’Adaptation’ processes. Alternatively,
their attitudes to their own environment could be re-
flected. Controlling the amount of CO
2
, government
players make their decisions so that tax revenues can
be secured and the power failure probability is main-
tained at a lower level. The players in gaming models
are expected to discuss and learn as a team.
Agent players interact with other suppliers, con-
sumers, and the government through the market in the
following points. Agent players develop competition
by receiving orders from consumers, establishing the
regulations on CO
2
emission based on carbon taxes
with the government, implement environmental mea-
sures based on renewable subsidies with the govern-
ment, establish the restrictions on renewable energy
based on imbalance adjustment prices with the gov-
ernment, compete with other companies for attrac-
tiveness based on stable electric power supply (power
failure probability) with consumers, and secure profits
and compete for receiving orders through discounted
prices with aggregators.
The initial electric power preferences of con-
sumers are stochastically determined in a uniform dis-
tribution, while the environmental preferences vary
depending on the period. The electric power propor-
tions are determined in uniform random numbers ex-
pressed by the base proportion +/-10%. Based on the
synthesised attractiveness of prices and electric power
preferences, suppliers and aggregators are determined
by using roulette selection. The power failure proba-
bility is an exponential function based on the renew-
able energy proportions.
Decisions made by consumers as realistic agents
are determinedbased on the norm effect of neighbour-
ing market shares on consumer network models(Delre
et al., 2007)(Toivonen et al., 2006). As for the norm
effect of consumers, the threshold model which is in-
fluenced by neighbouring market shares is adopted.
Consumers also have information effect functions in
which they make decision to purchase electricity from
suitable power suppliers stochastically based on price
and energy sources such as thermal, nuclear and re-
newable energy(Kurahashi and Saito, 2013).
ICAART 2017 - 9th International Conference on Agents and Artificial Intelligence
318
5 EXPERIMENT
An electricity gaming model was implemented by the
agent programmingenvironments, NetLogo and Hub-
Net, which was operated from each terminal con-
nected to the local network. Fig.3 shows the screen
displayed for players, while Fig.4 shows that for op-
erators.
Figure 3: Player Panel: Networks of consumers and mar-
ket shares are graphically observed. Decision-making and
management conditions of other players, including the pref-
erences of consumers, are observed on a panel. Decision-
making and management condition of all players are able to
be observed on a panel in every period.
Figure 4: Operator Panel: A game operator could confirm
the condition of consumers allocated on the network and the
condition of suppliers on the panel.
From any of these screens, the condition of con-
sumers allocated on the network and the condition
of suppliers could be confirmed. Consumers were
able to identify order destinations in different colours,
so that they could intuitively understand the current
share condition of suppliers. Electric power prices,
investment for power generation facilities, and man-
agement information including surplus funds could be
confirmed as supplier conditions. From this player
screen, each supplier player entered necessary infor-
mation such as the electric power prices, advertising
investments, investments for thermal power genera-
tion, investments for nuclear power generation, in-
vestments for renewable energy power generation,
and the discount rates for major clients. Aggregate
players determined the price and the energy source
weight, in addition to the electric power price and
advertising investments, as factors for deciding order
destinations.
In this experiment, four supplier players, one ag-
gregator agent, 500 consumer agents and the govern-
ment agent made their decisions for 18 periods. The
threshold level of norm effect is 0.5. Information ef-
fect which indicates price and energy balance of sup-
pliers is 0.3. Business tax rate is 35%. Carbon tax rate
is 10%. Thermal energy cost is 10 unit / kW, nuclear
energy cost is 5 unit / kW, and renewable energy cost
is 8 unit / kW, imbalance price is 3 unit / kW, and a
preference level between price and energy source of
aggregators is 50%.
The goal of this study is to clarify decisive fac-
tors for making decision of energy selection based
on human competitive and collaboration behaviour
to be helpful for an incentive design of energy mar-
kets. For the purpose, two hypotheses were set in
the experiment. First is that energy transition to re-
newable source is achieved by players while keeping
their profit. Second is that aggregators have ability
to control the energy market through the share of con-
sumers’ power market as well as other two-sided mar-
kets.
6 RESULTS AND DISCUSSION
The left chart of Fig.5 shows the proportion of each
energy source, the amount of CO
2
emissions, and the
transition of the power failure probability. In the ini-
tial stage, the proportion of thermal power generation
exceeded 60%; however, it declined gradually, finally
going down to less than 40%. This also reduced the
amount of carbon emissions (The right chart of Fig.5).
The first hypothesis, which energy transition to re-
newable source is achieved by players while keeping
their profit, has been adopted with this result.
On the other hand, the proportions of nuclear
power generation and renewable energy power gen-
eration increased. This is because of the influence
given by the energy orientation of consumers. In par-
ticular, the proportion of renewable energy gradually
increased in tune with the orientation of consumers,
while it declined in the later stages. This result might
be because whereas the power generation proportion
of each electric power supplier was inclined toward
the use of thermal power generation in the initial
stage, the energy orientation of consumers was about
1/3. Therefore, there must have been an incentive that
worked where the order volume increased by chang-
ing the power generation investment according to this
An Electricity Market Game using Agent-based Gaming Technique for Understanding Energy Transition
319
!"#"$%&'"
()*'"%+
,-"+.%'
,"+.
!%/012132"'"*/+0*241$"+
5'%*61)/
789
7892".0::01#
5'%*61)/24+1&%&0'0/;
,"+.
Figure 5: Left: Trend of energy source rate, Right: Trend of CO
2
and blackout rate.
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()%'*&$
+%,%-&.$%
+&/012132#1,4"*%'452
%,%'6728'%3%'%,#%
(%'*
(%'*
9'130/
:66'%6&/1'2
9$&7%'2;
9$&7%'2<
9$&7%'2=
9$&7%'2>
Figure 6: Left: Trend of consumers’ energy preference, Right: Trend of players’ sales in the power market.
proportion (The left chart of Fig.6).
However, the situation, which was originally ex-
pected that the proportion of nuclear power genera-
tion decreased, was not observed, while nuclear en-
ergy with lower cost and carbon gas emissions con-
tinue to be relied on. This result shows that the man-
agement of electric power suppliers gave the first pri-
ority to maximising their profits, while giving almost
no consideration to risks of nuclear power generation
accidents. On the other hand, the aggregator agent
made profit as well as suppliers players, but it could
not monopolise the electric consumer market because
one possibility is that the supplier players learnt how
to keep their market share in competition from the
aggregator(The right chart of Fig.6). The second hy-
pothesis, which aggregators have ability to control the
energy market through the share of consumers’ power
market as well as other two-sided markets, was re-
jected with the result.
All of the four players participating in this experi-
ment were business people in their 30s, who might
have had a custom to make decisions to maximise
business profits as corporate managers. They were at
the same time consumers, however, this experiment
suggests that their concepts of accident risks might
significantly change when they play a social role as
entities to make corporate decisions.
7 CONCLUSION
In this research, based on agent-based models, seri-
ous games, design of electricity market platforms, and
social network models, we built a model having the
items below as purposes.
1. Feature analysis on electric power imbalance ad-
justment for achieving new system designs
2. Design of competitive electricity market plat-
forms
3. Design of incentive mechanisms for imbalance
adjustment
4. Evaluation and examination of mechanism design
based on agent-based gaming models
The goal of this study is to clarify decisive fac-
tors for making decision of energy selection based
on human competitive and collaboration behaviour
to be helpful for an incentive design of energy mar-
kets. For the purpose, two hypotheses were set in
the experiment. First is that energy transition to re-
newable source is achieved by players while keeping
ICAART 2017 - 9th International Conference on Agents and Artificial Intelligence
320
their profit. Second is that aggregators have ability
to control the energy market through the share of con-
sumers’ power market as well as other two-sided mar-
kets.
Our experiment confirmed that the energy orien-
tation of electric power consumers could give a sig-
nificant influence on power generation investment of
electric power suppliers, and the risk of nuclear en-
ergy was underestimated. And the first hypothesis
was adopted and the second was rejected by the exper-
iments through the agent-based gaming. These find-
ings enabled us to analyse the decision-making pro-
cess of people and operators, while being able to ob-
tain effective knowledge regarding social ecosystems
which disseminate renewable energy and adaptive be-
haviour.
In the future, we are going to examine combined
models with autonomous and human agents to com-
pare with them. The autonomous agent-based model
will show behaviour and attitude as a control group to
validate the hypotheses more thoroughly. We will also
conduct several games including autonomous agents
and human players and compare with other models
such as an equilibrium model and so on.
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