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Archives of Business Research – Vol. 11, No. 1

Publication Date: January 25, 2023

DOI:10.14738/abr.111.13768.

Takahashi, K. and Sun, J. (2023). A Study of Integrated Model for Electricity Supply Chain Considering Renewable Energy Fraction

and Demand Variation, 11(1). 12-21.

Services for Science and Education – United Kingdom

A Study of Integrated Model for Electricity Supply Chain

Considering Renewable Energy Fraction and Demand Variation

Kosuke Takahashi and Jing Sun

Department of Civil Engineering and Systems Management,

Nagoya Institute of Technology, Japan

ABSTRACT

This paper aims to derive integrated model for electricity supply chain considering

renewable energy fraction and demand variation. Currently, attention is being paid

to increasing the ratio of renewable energy generation in the electric power market

which called Green Energy Coefficient (GEC). This paper aims to derive an

integrated model of electricity supply chain considering renewable energy fraction

and demand variation using multi-agent reinforcement learning. The subjects of

the models are the consumption market model, the electricity market model, and

the production market model. Also, the pricing process in electricity supply chain

is analyzed using the proposed multi-agent simulations.

Keywords: Green Energy Coefficient (GEC), Electricity Supply Chain, Renewable

Energy

INTRODUCTION

With the liberalization of electricity retailing in Japan in April 2016, and the liberalization of the

transmission and distribution sectors in April 2020, consumers will be able to freely choose the

electricity company they contract with. As a result, more and more companies are offering

electricity at lower prices than ever before, increasing the benefits for consumers. On the other

hand, power companies need to strategically set appropriate supply volumes and prices based

on market prices and electricity demand trends in order to ensure profits in the face of

numerous competitors. In addition, it is necessary to consider all aspects of the impact on

power companies, power retailers, and consumers. In addition, we are facing many challenges,

such as expanding the use of renewable energy, which is generated from natural energy and

reusable resources with less impact on the global environment and reducing the number of

nuclear power plants. According to data from the Agency for Natural Resources and Energy of

the Ministry of Economy Trade and Industry (METI), the goal is to increase the share of

renewable energy in total electricity generation to 22-24% by 2030.

Under these circumstances, Koie [1] modeled carbon tax and emissions trading schemes using

a multi-agent model and conducted research to analyze their impact on the electricity market.

In this model, Q-learning is used as a reinforcement learning method for the agents.

Watanabe.[2] conducted a multi-agent model simulation of the Japanese electricity industry,

which is undergoing major changes due to electricity deregulation, and constructed an

electricity supply-demand model focusing on dynamic capital investment strategies across

multiple time points.

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Takahashi, K. and Sun, J. (2023). A Study of Integrated Model for Electricity Supply Chain Considering Renewable Energy Fraction and Demand

Variation, 11(1). 12-21.

URL: http://dx.doi.org/10.14738/abr.111.13768

Kanetaka [3] used Q-learning to examine the impact of each pricing strategy of electric power

companies based on failures in the pooled market in the United States.

Inagaki [4] found that deregulation was implemented for many utilities, including the

electricity market, as the cost of regulation and the inefficiency of regulation itself were pointed

out, although it was conventionally believed that regulation was necessary for utilities such as

electricity. The dynamic factors such as the entry and exit of different types of power generators

into and out of the market were added to the multi-agent model to analyze the movements of

power generators and the market.

As described above, there are some studies that model the electricity market under

deregulation and some that consider carbon dioxide emissions, but there are few studies that

consider the share of renewable energy. Therefore, in a previous study [9], we extended the

multi-agent electricity market model of Kanetaka [3] and developed an electricity trading

model that takes into account the share of renewable energy.

In a previous study [9], an electricity market simulation model was developed to quantitatively

analyze and evaluate price fluctuations in the electricity market for electric power companies.

However, in the previous study [9], consumers and electricity retailers were not linked, and the

model could not be viewed as a consistent electricity supply system.

Based on the above background, in this study, we first propose an integrated model including

consumer market model, production model and electricity market model. After that, using

multi- agent simulation we analyze the pricing process in electricity supply chain.

INTEGRATED MODEL DESCRIPTION

In this study section, we propose an integrated model of electricity supply chain considering

renewable energy fraction and demand variation using multi-agent reinforcement learning.

The subjects of the models are the consumption market model, the electricity market model,

and the production market model.

The consumption market model is a simulation model of electricity price plan selection. Due to

the liberalization of electricity retailing, consumers are now free to choose new electricity

companies and plans and need to select the most appropriate plan depending on the number

of household members and their lifestyles. Therefore, this model is designed to provide

electricity plans that are suitable for different household characteristics.

The electricity market model is a model that represents the flow of electricity generated at

power plants to the market. The production market model is a relative trading model between

power generation companies and the electricity market. We perform reinforcement learning

on this model to quantitatively analyze and evaluate the price fluctuations in the electricity

market considering the percentage of renewable energy.

Furthermore, the amount of demand in each of these three model elements is integrated around

an axis to form a single electricity supply model. Figure 1 shows the overall image of the

electricity supply model.

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Archives of Business Research (ABR) Vol. 11, Issue 1, January-2023

Services for Science and Education – United Kingdom

Figure 1 - Diagram of integrated electric power supply

ELECTRICITY MARKET MODEL

A wide variety of liberalization models have emerged in the electricity market transactions in

the deregulation of electric power. Among these, there is a model called a pool market, which

is not familiar in Japan but is typical in Europe and the United States. In this study, we assume

a pool market as the mechanism of the electricity market. In a pool market, the power

generation division of an electric power company or an independent power producer (IPP)

sends all of its electricity to the market once and then trades in the market to supply electricity.

Figure 2 - Example of a transaction in a pool market

power market

consumer

generation

electricity retail

Electricity:

Demand:

electricity plan:

electricity price: