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Chapter 5
Finding and Conclusion
This chapter presents the conclusions of the major findings of this work. Also, it provides
the suggested recommendation that may help to achieve a more precise perception of
customer satisfaction with the IBDRP, allowing for better implementation of the program in
a large-scale society. This thesis included three main parts. The first part discussed how DPRs
could improve market efficiency through maximizing the social welfare of the wholesale
market actors, considering the impact of customer risk aversion and dynamic price elasticity
of demand. The second part proposed a region-wise modeling approach based on maximizing
end-users' social welfare in the wholesale electricity market. Finally, the third part examined
the impact of customer satisfaction on the social welfare and profitability of the market actors.
The main finding of the thesis is that customers with high-risk aversion can benefit from
effectively participating in demand response programs (DRPs) by obtaining higher expected
utility. Thus, although the reduction in consumption results in lower utility, the risk-averse
CUs decide to decrease electricity consumption more rapidly with the price increment during
the period when the absolute values of the elasticity are higher. Additionally, the research
highlights that real-time pricing (RTP) performs better in satisfying customers' electricity
consumption needs compared to other DRP options. This is because RTP provides customers
with greater flexibility and responsiveness, leading to higher expected utility values.
Furthermore, in a customer-oriented demand response market, customers' preferences
regarding DRP choices are influenced by their satisfaction levels based on their consumption
patterns. This satisfaction can be reflected in their expected utility function. Therefore, by
considering customer satisfaction during the implementation of DRPs, the social welfare of
customers can be maximized, and these programs can be implemented more efficiently.
Moreover, the research emphasizes the importance of understanding regional
characteristics in implementing DRPs. Each region has unique aspects, such as supplydemand equilibrium, wholesale prices, variable renewable energy (VRE) penetration, and
load profiles. These regional characteristics influence the response and effectiveness of
implemented RTP-DRPs, which can be classified into three categories: regions with excess
supply, regions with high demand burden, and regular suppliers to inter-regional connections.
Considering these findings, the study contributes to a better understanding of how DRPs
can be operated in Japan's wholesale electricity spot market. It highlights the benefits of
implementing DRPs, such as improving resource efficiency, decreasing electricity prices,
enhancing load flexibility, and increasing security through customer and market engagement.
103
5.1.Summary and major findings
Price-based demand response modeling in a day-ahead wholesale electricity market in
Japan, considering the impact of customer risk aversion and dynamic price elasticity of
demand: A mathematical modeling approach was developed based on maximizing the CU’s
welfare by considering a price-responsive demand response system in the wholesale market
in Japan. The proposed model is founded on the customer theory in microeconomics, using
the concept of the expected utility function to model the behavior of the risk-averse CUs in
responding to different DPRs. In order to precisely reflect the CUs' behavior in responding
to the DRPs, the PEMD was developed based on identifying the hourly self-and cross-price
elasticities of demand, considering different responding strategies: flexible, in-flexible,
forward-shifting, backward-shifting, and optimizing responses. An hourly day-ahead
electricity demand model was developed using the time series forecasting method to predict
an hour-ahead demand with a MAPE of 0.94% and R2 of 0.99. The results of applying the
proposed model to the JEPX day-ahead spot price market revealed a peak reduction potential
of 10.7% and 7.3%, respectively, from applying TOU and RTP programs to the flexible CUs.
By applying the RTP program to the curtailable loads, a 7.7% reduction in the daily peak
demand and a 1.6% reduction in daily electricity consumption can be achieved. The effect of
risk aversion on expected utility was determined in this study, with results indicating that
customers with high-risk aversion can obtain more expected utility by effectively
participating in DRPs. Although the TOU and CPP programs show better results in savings,
RTP performs better in satisfying the CUs from electricity consumption, providing higher
expected utility values. Thus, although the wholesale market operators prefer to implement
DRPs that guarantee more cost and energy savings, in a customer-oriented demand response
market, the CUs’ preference concerning the DPR choices is a function of their satisfaction
due to their consumption levels, which can be reflected in their expected utility function.
Region-Wise Evaluation of Price-Based Demand Response Programs in Japan's
Wholesale Electricity Market Considering Microeconomic Equilibrium: A
mathematical modeling technique focused on maximizing the customer’s welfare was
implemented, taking into account an RTP scheme in Japan's wholesale market. The regionwise impact of the wholesale electricity market was explored by formulating the price
elasticity matrix of demand for each region dedicatedly, while applying a single mathematical
modeling technique of the customer’s welfare to all the regions similarly. The region-wise
price elasticity matrix of demand was formulated by estimating the hourly self and crossprice elasticities, considering the flexibility of consumers. Furthermore, the region-wise selfelasticity was calculated using two stages of econometrics, which estimate the regional
wholesale price based on the VRE penetration and then evaluate the self-PED. The developed
model was then applied to investigate the region-wise potential benefits (peak reduction,
104
energy savings, and avoided emissions) of implementing the RTP-DRP in Japan’s wholesale
electricity market. The obtained results indicate a wide variation range of the hourly
estimated region-wise PED of -0.005 to -0.21. Meanwhile, the estimated risk aversion
coefficients that evaluate end-user’s willingness to engage in RTP-DRP vary in all the ranges
in a similar range of 0.001 to 0.003. This implies that, the PED variation is not caused by the
end-user side, but rather by the price-driving parameters of supply and demand
microeconomic equilibrium. In addition, given the application of similar RTP-DRP to all the
regions, the potential for daily peak reduction of the residential sector considering flexible
customers and shiftable load various between 1.91% to 22.9%. The energy saved from the
developed RTP-DRP for all regions varies between 0.16% to 1.02%. On the other hand, the
potential avoided GHG emissions resulting from the proposed program in the Tokyo region
are remarkable, with values of 82.6 and 192.2 (TonCO2e) in the summer and winter,
respectively. The estimated PEMD has shown high elasticity indices for Hokkaido, Hokuriku,
and Shikoku, which have been justified by the increased wholesale price considering their
VRE penetration and the dependency on the inter-regional connections.
Incentive-based demand response modeling in a day-ahead wholesale electricity market
in Japan, considering the impact of customer satisfaction on social welfare and
profitability: A multi-objective mathematical model was developed that maximizes the
social welfare function of both SPs and CUs to find the optimal incentive rates paid to the
CUs for decreasing their electricity consumption, taking into account the impact of the CU’s
satisfaction with the different IBDRP attributes of comfort, flexibility, energy security, and
environmental protection. The results revealed that the CUs’ satisfaction with comfort and
energy security has a linear relationship with their welfare. Furthermore, the satisfaction
elasticity of welfare is more negative with the flexibility attribute and more positive with the
environmental protection attribute. The findings highlighted the significance of the
environmental protection attribute of the IBDRP in motivating the CUs to active participation
in the program. The model was used to estimate the optimal demand load, peak reduction,
optimal incentive rates, and welfare of CU and SP for two scenarios, including with and
without CU's satisfaction. Based on the two scenarios considered in this study, the optimal
load reduction of a dissatisfied customer was estimated at 186,103,70 and 64 MWh with
environmental protection, comfort, flexibility, and energy security attributes, respectively.
Despite that, the daily electricity reduction after implementing the proposed IBDRP was
estimated at 277 MWh with all IBDRP attributes for a satisfied CU. The insights from this
research may help the Japanese local government achieve a more precise perception of
customer satisfaction with the IBDRP, allowing for better implementation of the program in
a large-scale society.
105
To validate the results of this study, a comprehensive comparison has been conducted
between various relevant studies and the findings of this research. The comparative analysis
is presented in the table below, highlighting the key similarities and differences between the
studies.
Table 5-1 A comprehensive comparison between the output results and other studies.
Program
Combined PB
and IB
IBDRP
PBDRP
IBDRP
PBDRP
IBDRP
DRP
DRP
DRP
PBDRP
IBDRP (DCL)
Remarks
Demand peak
reduction %
9.7
Electricity
saving %
6.4
7.6,4.6,7.4
7.2
5.02,2.17,3.32
6.04
5.2 to 10.2
8.2
8.3
0.3,0.1,0.1
1.3
0.22, 0.1, 0.99
0.32
7.8 to 16.2
11.3 to 13
10.7, 7.3
4.7 to 14
1, 0.7
11, 29, 7.7
2.3, 6.3, 1.6
4.3
2.9
1.4
0.9
Reference
(Yu et al.,2020)
Satisfied CU
Dissatisfied CU
TOU, CPP, RTP
DCL
TOU, CPP, RTP
DCL
Japanese rural
residential customers
Residential customers
Winter
Summer
TOU, RTP (shiftable
load)
TOU, CPP, RTP
(curtailable loads)
Satisfied CU
Dissatisfied CU
(Lu et al., 2018)
(Aalami, H.A.,et
al,2010)
(Moghaddam, M.P.,et
al.2011)
(Rohman and
Kobayashi, 2014)
(Mizutani et al., 2018)
(Yunqin Lu et al.,
2022)
This study
This study
5.2. Study limitation
Despite the significant contributions, some limitations of the study should be mentioned.
1- CUs preference is assumed to be unchanged and stable across participation in DRPs.
However, it is possible that CUs that were motivated by a value, e.g., environmental
protection, before participating in the DRP, may change their preferences during the
program and begin to find value in economic incentives.
2- Only four features of comfort, flexibility, energy security, and environmental
protection were considered in this study. However, other functional, epistemic, and
social values may help people perceive the main benefits of DRP, which were not
addressed in this study.
3- This modeling bears potential limitations in using similar relationships among
service providers and end-users in the demand-responsive market of various regions.
However, emphasizing the potential of adjusting the supply and demand imbalance
106
cost-effectively in the different areas proposed in this study leads to a new
formulation to target each region, with specific consideration for the regional supplydemand equilibrium, wholesale prices, VRE penetration, and load profiles.
5.3. Policy implications
Based on the conclusions of the study, the following policy implications can be drawn:
Customer-Centric Approach: Policymakers should adopt a customer-centric
approach when designing demand response programs. Understanding customer behavior,
preferences, and risk aversion levels is crucial for the success of these programs.
Consideration should be given to developing and implementing programs tailored to the
needs and preferences of different customer groups
Environmental protection awareness: The study highlights the importance of
incorporating environmental protection awareness into demand response programs.
Policymakers should emphasize the potential benefits of reduced greenhouse gas emissions
and incentivize customers to actively participate in programs that contribute to environmental
sustainability. Additionally, the remarkable potential for avoiding GHG emissions in Tokyo
emphasizes the importance of tailoring strategies to address specific regional challenges and
goals.
Continuous monitoring and Improvement: Policymakers should establish
mechanisms to continuously monitor and improve the implemented demand response
programs. Monitoring the impact of programs, customer satisfaction levels, and costeffectiveness will help identify areas for enhancement and optimize the overall performance
of demand response initiatives.
Collaboration with Wholesale Market Operators: Policymakers should collaborate
closely with wholesale market operators to align the implementation of demand response
programs with cost and energy-saving objectives. Balancing the preferences and welfare of
customers with the goals of the wholesale market is essential for the success and acceptance
of demand response initiatives.
The abovementioned policy implications empower policymakers to foster a customeroriented demand response market in Japan. By considering customer preferences, regional
variations, environmental concerns, and long-term goals, policymakers can design effective
and sustainable demand response programs that optimize customer welfare, reduce peak
demand, promote energy efficiency, and contribute to a more resilient and sustainable
electricity system.
5.4. Future work
In the future, this project will investigate the interaction between Virtual Power Plants
(VPPs) and Demand Response Programs (DRPs) in the Day-Ahead Market. It focuses on
107
how VPPs might collect and manage distributed energy resources (DERs) in order to improve
energy supply and market participation. It evaluates VPPs' ability to provide their aggregated
capacity and flexibility in the day ahead market, hence contributing to the efficient operation
of the energy system. The study explores the influence of integrating flexible loads into VPPs
for demand-side activities in DRPs on market dynamics, revenue generation, and
sustainability. It provides insights for policymakers, grid operators, and market participants
to shape effective strategies for future energy markets and support the transition towards a
more flexible, efficient, and resilient electricity system.
Furthermore, a detailed analysis of the climate co-benefits obtained from applying demand
response programs and energy management actions in climate change mitigation should be
carried out, in order to evaluate and quantify the additional benefits, such as local air quality
and public health improvement or green job creation.
In addition, in evaluating the satisfaction function in IBDRPs, further justification should
be provided for the selection of the four values: comfort, flexibility, energy security, and
environmental protection. While these values have been identified as important
considerations in the analysis, it is necessary to explore and justify their inclusion based on
additional dimensions of value. Specifically, the study will delve into the various forms of
value, including functional, epistemic, and social, to assess their relevance to the model. It
will investigate whether these forms of value align with the identified values or if there are
other dimensions that should be considered.
108
APPENDICES
Appendix 1: Examining the Customer satisfaction from participating in demand
response programs (DRPs).
This questionnaire examines the electricity customer's satisfaction from participating in
different Demand Response Programs (DRP). DRP allows electricity customers to maximize
their bill savings and earn bounces from supporting the grid efficiency and security by
cutting/shifting their electricity usage from peak hours (3:00 pm to 7:00 pm) to off-peak
hours. Therefore, customers are asked to change their consumption patterns by
cutting/shifting the electricity-drawing appliances (such as washing machines, vacuum
cleaners, iron, etc.) from costly peak times to times when costs are less, and demand is down.
This questionnaire proposes some key questions to explore the customer preference to
subscribe to DRP, and the main factors influencing customer satisfaction.
The key terms considered in this questionnaire are as follows:
1. Demand Response Programs (DRP): Cutting/shifting some electricity usage from peak
hours (3:00 pm to 7:00 pm) to off-peak hours.
2. Comfort: using electric appliances whenever a customer desires at any time (peak hours
or off-peak hours)
3. Peak hours: The times of day when electric consumption is highest (e.g., 3:00 pm to 7:00
pm)
4. Savings: Earning money from reducing electricity consumption and bill payment or
receiving credit or monetary incentives from the electricity supplier
5. Stable and secure electricity supply: ensuring that electricity is always available to meet
the demand requirements, including peak times.
6. Environmental protection: climate change mitigation and air pollution reduction
• Basic information
Age
Less than 20
years
20
Female
21 to 30
years old
21 30
Male
31 to 40 years
old
Education
Less than
high school
High school
Occupation
Employed
full time
Employed
part time
Gender
Current
residence
41 to 60 years
old
61
or
more
Professional
certification
Bachelor’s
degree
Master’s
degree
Doctorate
degree
Not currently
employed
Retired
Student
Homemaking
/other
Prefer not to say
109
Effect
Start main questions about DRPs
Preference from 5 (high) to 1(low)
Question
Response
-I will be
Satisfied
(Like)
(5)
Comfort
Flexibility
If participating in DRP
improves your savings but
decreases your comfort from
electricity usage during peak
hours, how do you feel? (Prefer
to pay less for electricity bill but
have less comfort)
If Not participating in DRP
doesn't affect your comfort from
using electricity during peak
hours, while it doesn't provide
any savings for you, how do you
feel? (Prefer to pay more for
electricity bill but have enough
comfort)
If participating in DRP offers
lots of savings and pays less for
electricity bills, but takes your
time and effort in order to work
with some data monitoring and
reporting programs, how do you
feel?
If the DRP is simple to follow,
but offers few savings, how do
you feel?
If participating in DRP offers
lots of savings, but needs
additional investment, such as
installing
smart
metering,
remote or online control
systems, cables, applications,
etc., how do you feel?
I am expecting
it to be that
way (Must-be)
(4)
am
neutral
can
accept it
I am not
Satisfied
(Dislike)
(2)
(1)
(3)
110
If participating in DRP is not
costly and doesn’t need too
much investment, but offers few
savings, how do you feel?
Energy
security
If participating in DRP grants
you a stable and secure
electricity supply, how do you
feel?
If NOT participating in DRP
doesn't grant you a stable and
secure electricity supply, how
do you feel?
Environment
al protection
If participating in DRP
improves your savings. In
addition, it protects the
environment, how do you feel?
If participating in DRP
improves your savings. But it
doesn't protect the environment,
how do you feel?
...
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