An Electricity Market Game using Agent-based Gaming Technique for

Understanding Energy Transition

Setsuya Kurahashi

and Wander Jager

Graduate School of Business Sciences, University of Tsukuba, 3-29-1 Otsuka, Bunkyo, Tokyo, Japan

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

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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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

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,

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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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

, 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

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

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

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Figure 5: Left: Trend of energy source rate, Right: Trend of CO

and blackout rate.

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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 30’s, 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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