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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: