Impact of Revised Time of Use Tariff on Variable Renewable Energy Curtailment on Jeju Island

Abstract

Jeju Island announced the “Carbon Free Island (CFI) Plan by 2030” in 2012. This plan aims to replace conventional generators with distributed energy resources (DERs) up to a level of 70% by 2030. Akin to Jeju Island, as DERs have been expanded in islanded power systems, variable renewable energy (VRE) has become a significant component of DERs. However, VRE curtailment can occur to meet power balance, and VRE curtailment generally causes energy waste and low efficiency, so it should be minimized. This paper first presents a systematic procedure for estimating the annual VRE curtailment for the stable operation of the islanded power systems. In this procedure, the VRE curtailment is estimated based on the power demand, the grid interconnection, the capacity factor of VRE, and conventional generators in the base year. Next, through the analysis of the hourly net load profile for the year in which the VRE curtailment is expected to occur, a procedure was proposed to find the season and hour when VRE curtailment occurs the most. It could be applied to revised Time-of-Use (ToU) tariff rates as the most cost-effective mitigation method of VRE curtailment on the retail market-side. Finally, price elasticity of electricity demand was presented for applying the revised ToU tariff rate scenarios in a specific season and hour, which found that VRE curtailment occurred the most. Considering self- and cross-price elasticity of electricity, revised ToU tariff rate scenarios were used in a case study on Jeju Island. Eventually, it was confirmed that VRE curtailment could be mitigated when the revised ToU tariff rates were applied, considering the price elasticity of demand.

Full text

electronics
Article
Impact of Revised Time of Use Tariff on Variable Renewable
Energy Curtailment on Jeju Island
Jinyeong Lee 1, Jaehee Lee 2and Young-Min Wi 3,*


Citation: Lee, J.; Lee, J.; Wi, Y.-M.
Impact of Revised Time of Use Tariff
on Variable Renewable Energy
Curtailment on Jeju Island. Electronics
2021,10, 135. https://doi.org/
10.3390/electronics10020135
Received: 2 December 2020
Accepted: 4 January 2021
Published: 10 January 2021
Publisher’s Note: MDPI stays neu-
tral with regard to jurisdictional clai-
ms in published maps and institutio-
nal affiliations.
Copyright: © 2021 by the authors. Li-
censee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and con-
ditions of the Creative Commons At-
tribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1School of Electrical Engineering, Korea University, Seoul 02841, Korea; korea6611@korea.ac.kr
2Department of Information and Electronic Engineering, Mokpo National University, Muan 58554, Korea;
jaehee@mokpo.ac.kr
3School of Electrical and Electronic Engineering, Gwangju University, Gwangju 61743, Korea
*Correspondence: ymwi@gwangju.ac.kr; Tel.: +82-62-670-2035
Abstract:
Jeju Island announced the “Carbon Free Island (CFI) Plan by 2030” in 2012. This plan
aims to replace conventional generators with distributed energy resources (DERs) up to a level of
70% by 2030. Akin to Jeju Island, as DERs have been expanded in islanded power systems, variable
renewable energy (VRE) has become a significant component of DERs. However, VRE curtailment
can occur to meet power balance, and VRE curtailment generally causes energy waste and low
efficiency, so it should be minimized. This paper first presents a systematic procedure for estimating
the annual VRE curtailment for the stable operation of the islanded power systems. In this procedure,
the VRE curtailment is estimated based on the power demand, the grid interconnection, the capacity
factor of VRE, and conventional generators in the base year. Next, through the analysis of the hourly
net load profile for the year in which the VRE curtailment is expected to occur, a procedure was
proposed to find the season and hour when VRE curtailment occurs the most. It could be applied to
revised Time-of-Use (ToU) tariff rates as the most cost-effective mitigation method of VRE curtailment
on the retail market-side. Finally, price elasticity of electricity demand was presented for applying
the revised ToU tariff rate scenarios in a specific season and hour, which found that VRE curtailment
occurred the most. Considering self- and cross-price elasticity of electricity, revised ToU tariff rate
scenarios were used in a case study on Jeju Island. Eventually, it was confirmed that VRE curtailment
could be mitigated when the revised ToU tariff rates were applied, considering the price elasticity
of demand.
Keywords: variable renewable energy; curtailment; time-of-use tariffs; price elasticity; Jeju
1. Introduction
Many countries around the world are striving to reduce greenhouse gas (GHG) emis-
sions and the use of fossil fuels due to the adoption of the Kyoto Protocol and the Paris
Agreement, by increasing their use of variable renewable energy (VRE) sources such as
wind power and photovoltaics (PVs) [
1
,
2
]. On Jeju Island, the largest island in South
Korea, wind power and PV generators are rapidly being installed with the aim of energy
self-sufficiency and GHG emission reduction. Jeju Special Self-Governing Province, a local
government encompassing Jeju Island in the south of the Republic of Korea, announced
the “Carbon Free Island (CFI) Plan by 2030” in 2012 [
3
]. According to the plan, Jeju aims to
become a more environmentally friendly island by reducing the use of fossil fuels by 2030,
and this plan intends to reduce GHG emissions while maintaining a stable energy supply
and demand structure. One of the strategies of the plan is to quickly replace conventional
power generation with VRE sources such as wind and solar energy [4,5].
The replacement of conventional generators with VRE sources can help to create a less
fossil-fuel-dependent power supply environment. However, VRE sources cannot always
produce the energy required in periods of high electricity demand, unlike conventional
generators [
6
]. The output of VRE cannot always be controlled by power system operators,
Electronics 2021,10, 135. https://doi.org/10.3390/electronics10020135 https://www.mdpi.com/journal/electronics

Electronics 2021,10, 135 2 of 20
and its output can vary significantly from time to time. VRE sources typically have
uncertainty issues because it is difficult to accurately forecast their outputs, so these sources
need to include more reserve resources to meet the power balance [
7
]. Moreover, PV
energy generally has a variable output because of its intensive generation during the
daytime; therefore, PV energy requires other generators that can ramp up quickly to meet
the power balance [
8
]. Power system operators must ensure a power balance between
electricity supply and demand at all times, and power systems are usually designed to
handle the variable nature of loads. The variability and uncertainty of VRE can induce
new challenges for power system operators [
9
]. In particular, high levels of VRE can be
difficult to integrate into islanded power systems because of limitations in variability and
predictability. Additionally, increasing penetration levels of VRE can lead power systems
to encounter operational constraints, resulting in system operators accepting less VRE
than is available [
10
]. Thus, high penetrations of VRE sources on power systems result in
increasing VRE curtailment, and infrastructure and operational changes to power systems
may be required [
11
]. VRE curtailment is therefore defined as the act of reducing the supply
from VRE sources to the power grid. Not all the energy produced is used, so it can be
classified as some kind of inefficiency. It is usually thought that VRE curtailment leads
to respectable energy wastage, and although VRE curtailment can be helpful to ensure
power balance, mitigation measures to reduce VRE curtailment in the future should be
addressed [
12
]. In addition, it is necessary to predict the time period in which the VRE
curtailment occurs to apply measures to mitigate VRE curtailment, and case studies for
different mitigation scenarios should be carried out at that time period. However, there
have been limited studies on the hour-by-hour estimation of VRE curtailment in islanded
power systems. Therefore, a method has been proposed in this study to calculate the
long-term estimation of the amount of VRE curtailment.
There have been technical methods proposed to mitigate VRE curtailment by ensuring
the flexibility of the power systems. The main method used is adjusting the maximum and
minimum operating levels of conventional generators [
12
,
13
]. However, there are not many
existing generators in islanded power systems, so the plan may not be sufficiently effective.
Another method of mitigation is to have plenty of flexible resources to maintain
the stability of power systems. Energy storage systems (ESSs) are an effective means of
mitigating VRE curtailment among several flexible resources because ESS can store the
VRE output during high levels of VRE generation and discharge it when required [
14
]. If
the PV penetration rate increases, the net load, which is the value excluding the VRE value
from the power demand, decreases significantly in the afternoon, and attenuation of the
conventional power generator increases, leading to economic loss [
15
]. However, ESSs are
not yet economically suitable as resources to mitigate VRE curtailment, and geographic
conditions and environmental issues make it difficult to build additional pump storage in
the islanded power systems.
A further method is to improve the interconnection of the power grid for electricity
transmission [
16
]. This is one of the main methods used in countries in Europe, as there
is intensive grid interconnection between districts. Conversely, islanded power systems
have the problem of distance from other regions, and the infrastructure for transmitting
electricity between different regions is limited. Other possible methods include introducing
negative bidding for VRE and improving the next-day forecasting of VRE generation [
17
].
The introduction of negative bids can encourage VRE producers to store electricity without
selling electricity or sending it to other regions at certain times. However, power systems
are required to have a suitable price bidding generation pools for negative biddings of
VRE sources. Islanded power systems do not usually have a price bidding generation pool
for VRE sources. Improving the next-day forecasting of VRE allows for better scheduling
of daily generation plans with other conventional generation resources. However, power
systems in the island region do not have many conventional generation resources.
The methods described above are a way to increase the flexibility of the power system
so that it meets the demand and supply of power and allows a high level of VRE to be

Electronics 2021,10, 135 3 of 20
used in the power system. However, owing to the geographical and environmental charac-
teristics of islanded power systems, it may be expensive to apply these methods. In [
17
],
methods to increase power system flexibility due to the expansion of renewable energy are
classified according to cost. The cheapest method to increase power system flexibility in
terms of the electricity market is to adjust the electricity demand by improving the energy
market design. Therefore, this paper proposes a systematic procedure for mitigating VRE
curtailment by changing the electricity demand through price changes of the time-of-use
(ToU) tariffs in the electricity market. This revised ToU tariff rate is suggested by [
18
] and
applied with the price elasticity of electricity demand. Similar to a study on coordination
of the charging of electric vehicles by applying the ToU tariffs to reduce wind-energy
curtailment, the ToU tariffs can be applied to mitigate VRE curtailment [
19
,
20
]. However,
there has been no research on easing future VRE curtailment by analyzing the change in
power demand considering price elasticity from a long-term perspective. Accordingly, the
objective of this study is to estimate the amount of future VRE curtailment and thereby
mitigate the estimated VRE curtailment by applying a systematic procedure for analyzing
the impacts of the revised ToU tariff.
A case study has been carried out on the power system of Jeju Island to illustrate
the impact of the revised time-of-use tariff on VRE curtailment. All actual datasets of the
hourly supplies and demands of the Jeju power system were obtained from the Korea
Power Exchange (KPX) and Korea Electric Power Corporation (KEPCO). According to
Jeju’s VRE expansion plan [
21
,
22
], the first VRE curtailment in South Korea occurred in
Jeju in August 2015, and VRE curtailment in Jeju has been increasing every year [
23
]. The
high penetration of planned VRE in recent years necessitates changes to energy policies as
well as revisions to the infrastructure to integrate a large amount of VRE and mitigate VRE
curtailment, as stated in the Carbon Free Island (CFI) plan 2030 for Jeju [
5
]. The mitigation
of curtailment, thereby enhancing the power system efficiency, is the aim of the power
system operator.
In this paper, there are two main contributions. First, by applying a systematic proce-
dure to estimate the annual VRE curtailment for the stable operation of the islanded power
systems, islanded power systems operators can grasp the amount of energy waste due to
VRE curtailment in advance and seek proactive countermeasures. Secondly, this paper
presents the impact of revised ToU tariffs on VRE curtailment for islanded power systems.
From the retail market aspect, the most cost-efficient method to increase power system
flexibility is to adjust the electricity demand by the revised ToU tariff rates. Therefore, a
method for mitigating VRE curtailment by increasing the electricity demand through price
decrease scenarios of the ToU tariff rates is suggested. Scenarios are applied by the self and
cross-price elasticity of electricity demand in a case study on Jeju Island. As a result, this
procedure makes grid operators stabilize their islanded power system by improving the
efficiency of the demand response program which mitigates VRE curtailment, based on the
revised ToU tariff rates.
This paper is organized as follows: Section 2describes the power system, VRE curtail-
ment cases, and the ToU tariff for Jeju. A systematic procedure for analyzing the impacts of
the revised ToU tariff on VRE curtailment is given in Section 3. This procedure consists of
three parts: estimation of the VRE curtailment, analysis of the net load profile for applying
the revised ToU tariff and the price elasticity of electricity demand for the revised ToU
tariff. The case study on the impacts of the revised ToU tariff on VRE curtailment is given
in Section 4, followed by the conclusions in Section 5.
2. Variable Renewable Energy Curtailment and Time-of-Use Tariff in Jeju
2.1. Power System and VRE Curtailment Cases of Jeju Island
The integration of distributed energy resources (DERs) into the Jeju power grid is an
essential part of one of the detailed CFI plans and Jeju Special Self-Governing Province
aims to replace conventional generators with VRE such as wind and solar power for up to

Electronics 2021,10, 135 4 of 20
70% of power generation by 2030 [
5
]. Figure 1shows the power system diagram of Jeju
Island in 2017 and the location of Jeju Island in South Korea [24].
Electronics 2021, 10, x FOR PEER REVIEW 4 of 20
2. Variable Renewable Energy Curtailment and Time-of-Use Tariff in Jeju
2.1. Power System and VRE Curtailment Cases of Jeju Island
The integration of distributed energy resources (DERs) into the Jeju power grid is an
essential part of one of the detailed CFI plans and Jeju Special Self-Governing Province
aims to replace conventional generators with VRE such as wind and solar power for up
to 70% of power generation by 2030 [5]. Figure 1 shows the power system diagram of Jeju
Island in 2017 and the location of Jeju Island in South Korea [24].
Figure 1. Power system diagram of Jeju Island in 2017 and the location of Jeju Island in South Korea.
Jeju Island, the largest island in South Korea, had a population of about 678,000 in
2017 and is well known for its natural tourist attractions. The administration of Jeju Island
has active policies and plans to replace existing fossil fuels with DERs, specifically PV and
wind energy, to maintain a clean natural environment. Jeju Island is popular with tourists,
and with the development of various industries, the population grew from 641,355 in 2015
to 678,772 in 2017. Therefore, Jeju Island is a suitable example of an island power system
for analyzing the impact of ToU tariff rates on power systems with high levels of renew-
able resources.
The Jeju Island power system is composed of conventional generators, high-voltage
direct current (HVDC) grid interconnection, transmission lines, and renewable energy
sources. Conventional generators using Liquefied Natural Gas (LNG) and oil as fuel are
classified as controllable generators that are available for output control by power dis-
patch instructions. PV and wind power generators were classified as VRE. Renewable en-
ergy generators of other types, such as hydro, bioenergy, and waste energy, are classified
as noncontrollable generators. HVDC #1–#3 transmission lines are classified as grid inter-
connections.
Table 1 shows the generation capacity and power generation on Jeju Island from 2015
to 2017. The total power generation increased from 4791.5 GWh in 2015 to 5422.0 GWh in
2017, and the total generation capacity increased from 1287 MW in 2015 to 1511 MW in
2017. The generation capacity of the grid interconnection is 400 MW based on supply ca-
pacity, which was the same in both 2015 and 2017. However, the power generation ratio
of grid interconnections increased from 36.4% in 2015 to 42.4% in 2017. The power gener-
ation ratio of PV increased from 1.8% in 2015 to 2.6% in 2017, and the power generation
ratio of wind energy increased from 7.0% in 2015 to 9.9% in 2017. Renewable energy
sources other than PV and wind energy are noncontrollable generators, and their power
generation ratio increased from 0.5% in 2015 to 0.7% in 2017. On the other hand, the ratio
of the generation ratio of controllable generators that use LNG and oil as fuels decreased
Figure 1. Power system diagram of Jeju Island in 2017 and the location of Jeju Island in South Korea.
Jeju Island, the largest island in South Korea, had a population of about 678,000 in
2017 and is well known for its natural tourist attractions. The administration of Jeju Island
has active policies and plans to replace existing fossil fuels with DERs, specifically PV
and wind energy, to maintain a clean natural environment. Jeju Island is popular with
tourists, and with the development of various industries, the population grew from 641,355
in 2015 to 678,772 in 2017. Therefore, Jeju Island is a suitable example of an island power
system for analyzing the impact of ToU tariff rates on power systems with high levels of
renewable resources.
The Jeju Island power system is composed of conventional generators, high-voltage
direct current (HVDC) grid interconnection, transmission lines, and renewable energy
sources. Conventional generators using Liquefied Natural Gas (LNG) and oil as fuel
are classified as controllable generators that are available for output control by power
dispatch instructions. PV and wind power generators were classified as VRE. Renew-
able energy generators of other types, such as hydro, bioenergy, and waste energy, are
classified as noncontrollable generators. HVDC #1–#3 transmission lines are classified as
grid interconnections.
Table 1shows the generation capacity and power generation on Jeju Island from 2015
to 2017. The total power generation increased from 4791.5 GWh in 2015 to 5422.0 GWh in
2017, and the total generation capacity increased from 1287 MW in 2015 to 1511 MW in 2017.
The generation capacity of the grid interconnection is 400 MW based on supply capacity,
which was the same in both 2015 and 2017. However, the power generation ratio of grid
interconnections increased from 36.4% in 2015 to 42.4% in 2017. The power generation
ratio of PV increased from 1.8% in 2015 to 2.6% in 2017, and the power generation ratio of
wind energy increased from 7.0% in 2015 to 9.9% in 2017. Renewable energy sources other
than PV and wind energy are noncontrollable generators, and their power generation ratio
increased from 0.5% in 2015 to 0.7% in 2017. On the other hand, the ratio of the generation
ratio of controllable generators that use LNG and oil as fuels decreased from 54.3% in
2015 to 44.5% in 2017. This indicates that the generation ratio of renewable energy and
grid interconnection in Jeju Island is increasing and the generation ratio of controllable
generators is decreasing.

Electronics 2021,10, 135 5 of 20
Table 1. Generation capacity and power generation on Jeju Island from 2015 to 2017.
Year Generation Capacity [MW] Power Generation [GWh]
2015 2016 2017 2015 2016 2017
Grid
Interconnection
400.0
(31.1%)
400.0
(26.9%)
400.0
(26.5%)
1742.2
(36.4%)
2002.5
(39.1%)
2297.3
(42.4%)
Controllable
Generators
(LNG, Oil, etc.)
590.0
(45.8%)
706.0
(47.5%)
706.0
(46.7%)
2602.1
(54.3%)
2535.5
(49.4%)
2410.3
(44.5%)
VRE (PV) 71.7
(5.6%)
88.2
(5.9%)
125.0
(8.3%)
88.3
(1.8%)
116.3
(2.3%)
141.0
(2.6%)
VRE (Wind) 215.0
(16.7%)
271.0
(18.2%)
273.0
(18.1%)
334.9
(7.0%)
441.5
(8.6%)
535.0
(9.9%)
Noncontrollable
Generators
10.3
(0.8%)
20.8
(1.4%)
7.0
(0.5%)
24.0
(0.5%)
31.7
(0.6%)
38.4
(0.7%)
Total 1287.0
(100%)
1486.0
(100%)
1511.0
(100%)
4791.5
(100%)
5127.5
(100%)
5422.0
(100%)
The VRE output is not easily controlled by the power system operator because its
output can vary greatly from minute to minute. The variable power supply of VRE can
cause problems, such as the risk of VRE curtailment, because the power system operator is
required to ensure the balance between supply and demand of the electricity at all times.
Table 2below shows the statistical data for wind-energy curtailment in Jeju from 2015
to 2017 [
23
]. The data were divided by season and day/night. Since there were not enough
solar energy facilities connected to the power conversion systems, only wind generators
were able to limit the power output to balance power supply and demand.
Table 2. Wind-energy curtailment in Jeju from 2015 to 2017.
Number of Instances of
Wind-Energy Curtailment
2015 2016 2017
Day Night Day Night Day Night
Spring 0 0 1 1 2 2
Summer 0 1 0 0 0 0
Autumn 0 2 0 4 6 6
Winter 0 0 0 0 0 0
Total 0 3 1 5 8 8
Amount of
wind-energy curtailment [MWh]
Day: 0 Night: 152 Day: 2 Night: 250 Day: 710 Night: 591
Total: 152 Total: 252 Total: 1301
Total generation of
wind energy [MWh] 352,183 470,576 542,526
Rate of curtailment [%] 0.04 0.05 0.23
In 2015, wind-energy curtailment occurred three times, all at night. However, wind-
energy curtailment occurred eight times during the day and eight times at night, respec-
tively, in 2017. The amount of annual wind-energy curtailment increased from 152 MWh in
2015 to 1301 MWh in 2017. In addition, the wind-energy curtailment ratio was 0.04% in
2015 but increased to 0.23% in 2017.
In particular, it can be seen that the amount of wind-energy curtailment sharply
increased in the daytime during spring and autumn, from 0 MWh in 2015 to 710 MWh in
2017. The reason for this is that although the power demand in spring and autumn is lower
than in other seasons, the power supply from PV and wind energy is high, resulting in VRE
curtailment during these times. When controllable generators have reached a minimum
level, VRE curtailment occurs to ensure the supply–demand balance of the electricity. This
means that there is less flexibility of the power system and potentially higher curtailment
can occur on days when the VRE exceeds requirements.

Electronics 2021,10, 135 6 of 20
Power system operators need to estimate future VRE curtailment, and systematically
establish an energy mix plan for renewable energy resources, existing suppliers, and
demand resources. However, there are not many studies dealing with VRE curtailment
in islanded power systems, such as Jeju Island, despite the need for appropriate power
suppliers and the requirement of operational plans for islanded power systems. In addition,
there have been limited studies analyzing how much VRE curtailment will occur in islanded
power systems.
In this study, to calculate the amount of annual VRE curtailment, all the hourly
demand and supply data in the Jeju power system are known so that VRE curtailment
could be estimated using a systematic process.
2.2. Revised ToU Tariff Rates to Reduce VRE Curtailment on the Demand Side
The various demand resources are classified according to the type of electricity tariffs
on the demand side. The electricity tariffs in South Korea, including Jeju, differ by contract
type, season, and hour. Users are allowed to choose from different rates offered for different
types of loads. The policy of differentiated tariff rates involves applying different rates to
various contract types based on the cost of supplying electricity for each type.
In its basic supply agreement, KEPCO lists the types of contracts: residential, general,
educational, industrial, agricultural, public lighting, and midnight. Table 3summarizes the
tariff rates for each type of contract, electricity used, and average revenues in Jeju for 2017
according to the statistics provided by KEPCO [25].
Table 3. Tariff rates, electricity used, average revenues by type of contract in Jeju 2017.
Type Tariff Rates Electricity Used
[kWh (%)]
Average Revenues
[Won/kWh]
Residential 3-Stage Progressive
Tariff 810,678,777 (16.2%) 108.50
General Time-of-Use (ToU)
Tariff
1,913,259,060 (38.2%) 130.42
Educational 130,395,448 (2.6%) 103.07
Industrial 593,234,772 (11.8%) 107.41
Agricultural Flat Tariff 1,390,704,857 (27.7%) 47.57
Public Lighting A(fixed),
B(metric) 52,182,047 (1.0%) 113.48
Midnight A(heat),
B(air-conditioning) 123,089,730 (2.5%) 67.48
In particular, ToU tariff rates by season and hour involve charging higher rates for
peak seasons/hours and lower rates for off-peak seasons/hours. Higher rates are applied
in the summer and winter and at peak hours. In spring and autumn, the subpeak and
off-peak hours are subjected to lower tariff rates. The price differential in ToU tariffs
gives customers an incentive to shift their electricity consumption to lower-priced hours,
providing bill saving opportunities, and an associated potential reduction in overall power
system costs. Table 4summarizes the time range for the current seasonal ToU tariff in
South Korea [26].

Electronics 2021,10, 135 7 of 20
Table 4. The time range for the current seasonal Time-of-Use (ToU) tariff in South Korea.
Seasons Type Time
Spring
(March, April, May)
and Autumn
(September, October, November)
Off-Peak 00:00~09:00 am/23:00~24:00 pm
Medium 09:00~10:00 am/12:00~13:00 pm/
17:00~23:00 pm
Peak 10:00~12:00 am/13:00~17:00 pm
Summer
(June, July, August)
Off-Peak 00:00~09:00 am/23:00~24:00 pm
Medium 09:00~10:00 am/12:00~13:00 pm/
17:00~23:00 pm
Peak 10:00~12:00 am/13:00~17:00 pm
Winter
(December, January, February)
Off-Peak 00:00~09:00 am/23:00~24:00 pm
Medium 09:00~10:00 am/12:00~17:00 pm/
20:00~22:00 pm
Peak 10:00~12:00 am/17:00~20:00 pm/
22:00~23:00 pm
If a large amount of VRE is introduced without implementing any type of mitigation
solutions such as management of other power supply and demand resources, energy
storage systems, or expansion of grid interconnection, then there is a possibility of VRE
curtailment. Several solutions [
12
–
17
] have been suggested to reduce the VRE curtailment
for power systems. As mentioned in [
17
], the cheapest solution is to adjust the power
demand by revising the design of the energy market. Moreover, from Table 2above, it can
be seen that curtailment during the daytime sharply increased in Jeju in 2017. This is due to
the rapid increase in PV power generation facilities. If the ToU tariff rates for the daytime
period when the curtailment occurs can be adjusted, the power demand for the daytime
period can be relatively increased by the self-elasticity. The power demand for the other
time periods can then be relatively decreased by the cross-elasticity.
In this paper, a systematic procedure is proposed to mitigate VRE curtailment by
changing the power demand through changing the price of the ToU tariffs in the energy
market. Accordingly, the objective of this study is to predict the amount of future VRE
curtailment in islanded power systems and to mitigate the predicted VRE curtailment by
applying a systematic procedure to analyze the impact of the revised ToU tariff.
3. Systematic Procedure for Analyzing the Impacts of the Revised ToU Tariff on
VRE Curtailment
3.1. Estimation of VRE Curtailment of Islanded Power Systems
Islanded power systems operators can seek proactive countermeasures and grasp
the amount of energy waste due to VRE curtailment in advance by applying a systematic
procedure to estimate the annual VRE curtailment for the stable operation of the islanded
power systems. To estimate the amount of future annual VRE curtailment for a specific
year, it is necessary to know the electric power demand, the amount of renewable energy
generation, the minimum generation level of the thermal power generator, and the max-
imum amount of grid interconnection for a specific year. The estimation procedure for
calculating the amount of curtailment is as follows:
Cyear
VR E,t=hPyear
VR E,t+Pyear
min,t−HVDCyear
max,t−Dyear
ti,t=1, 2, . . . , T(1)
where the unit of tis hour and thas a value from 1 to
T
;
T
is the end-time of the year;
Cyear
VR E,t
is the amount of VRE curtailment at time tof the year;
Pyear
VR E,t
is the amount of VRE at time t
of the year;
Pyear
min,t
is the minimum generation level of the thermal power generators at time

Electronics 2021,10, 135 8 of 20
tof the year;
HV DCyear
max,t
is the maximum power transmission of the HVDC connections at
time tof the year; Dyear
tis the power demand at time tof the year.
Pyear
VR E,t=CFbase
VR E,t×CAPyear
VR E,t ∵CFbase
VR E,t=Pbase
VR E,t
CAPbase
VR E,t!,t=1, 2, . . . , T(2)
where
CFbase
VR E,t
is the capacity factor of VRE at time tof the base year,
CAPyear
VR E
is the VRE
capacity for the year,
Pbase
VR E,t
is the VRE generation amount at time tof the base year, and
CAPbase
VR E is the VRE capacity of the base year.
Dyear
t=Dbase
t×1
2(Dyear
max
Dbase
max
+Gyear
total
Gbase
total
),t=1, 2, . . . , T(3)
where
Dbase
t
is the electric power demand at time tof the base year,
Dyear
max
is the maximum
amount of electric power demand for the year,
Dbase
max
is the maximum electric power
demand for the base year,
Gyear
total
is the sum of the total generation of the year, and
Gbase
total
is
the sum of the total generation amounts for the base year.
Cyear
VR E =
T
∑
t=1
Cyear
VR E,t>0, t=1, 2, . . . , T(4)
where
Cyear
VR E
is the total VRE curtailment for the year and is calculated only when the value
of
Cyear
VR E,t
is a positive number. The total VRE curtailment for each year can be calculated
as the sum of the values of
Cyear
VR E,t
for the year. Figure 2shows a flowchart that estimates
the amount of VRE curtailment based on the systematic procedure of calculating the VRE
curtailment of the islanded power systems for the entire year.
Electronics 2021, 10, x FOR PEER REVIEW 8 of 20
where the unit of t is hour and t has a value from 1 to 𝑇; 𝑇 is the end-time of the year;
𝐶,
 is the amount of VRE curtailment at time t of the year; 𝑃,
 is the amount of VRE
at time t of the year; 𝑃,
 is the minimum generation level of the thermal power gener-
ators at time t of the year; 𝐻𝑉𝐷𝐶,
 is the maximum power transmission of the HVDC
connections at time t of the year; 𝐷 is the power demand at time t of the year.
𝑃,
 = 𝐶𝐹,
 ×𝐶𝐴𝑃,
  ∵ 𝐶𝐹,
 = 
,


,

 , 𝑡=1,2,…,𝑇 (2)
where 𝐶𝐹,
 is the capacity factor of VRE at time t of the base year, 𝐶𝐴𝑃
 is the VRE
capacity for the year, 𝑃,
 is the VRE generation amount at time t of the base year, and
𝐶𝐴𝑃
 is the VRE capacity of the base year.
𝐷 
 = 𝐷 ×
 





+ 





) , 𝑡=1,2,…,𝑇 (3)
where 𝐷 is the electric power demand at time t of the base year, 𝐷
 is the maxi-
mum amount of electric power demand for the year, 𝐷
 is the maximum electric
power demand for the base year, 𝐺
 is the sum of the total generation of the year, and
𝐺
 is the sum of the total generation amounts for the base year.
𝐶
 =  𝐶,
 0

 , 𝑡=1,2,…,𝑇 (4)
where 𝐶
 is the total VRE curtailment for the year and is calculated only when the
value of 𝐶,
 is a positive number. The total VRE curtailment for each year can be cal-
culated as the sum of the values of 𝐶,
 for the year. Figure 2 shows a flowchart that
estimates the amount of VRE curtailment based on the systematic procedure of calculating
the VRE curtailment of the islanded power systems for the entire year.
Figure 2. Flowchart of the long-term estimation of the amount of variable renewable energy (VRE) curtailment.
In order to determine the appropriateness of the method of forecasting the VRE cur-
tailment, Table 5 compares the actual VRE curtailment in 2017, 2018, and 2019 with the
estimated VRE curtailment according to the flowchart in Figure 2. The error between the
actual values and the estimated values of VRE curtailment was 0.295% in 2017, 0.518% in
2018, and 0.713% in 2019, which are all within 1% which can be seen as a high prediction
accuracy. Therefore, future VRE curtailment has been estimated up to 2030 through the
process described in Section 3.
Figure 2. Flowchart of the long-term estimation of the amount of variable renewable energy (VRE) curtailment.

Electronics 2021,10, 135 9 of 20
In order to determine the appropriateness of the method of forecasting the VRE
curtailment, Table 5compares the actual VRE curtailment in 2017, 2018, and 2019 with the
estimated VRE curtailment according to the flowchart in Figure 2. The error between the
actual values and the estimated values of VRE curtailment was 0.295% in 2017, 0.518% in
2018, and 0.713% in 2019, which are all within 1% which can be seen as a high prediction
accuracy. Therefore, future VRE curtailment has been estimated up to 2030 through the
process described in Section 3.
Table 5. Error between actual and estimated VRE curtailment for 2017, 2018, and 2019 in Jeju.
Number of VRE Curtailment Days Total VRE Curtailment [MWh]
Year 2017 2018 2019 2017 2018 2019
Actual VRE curtailment [days] 16 16 46 1301 1366 9223
Estimated VRE curtailment [MWh] 16 16 46 1297.16 1358.92 9216.42
Error [%] 0 0 0 0.295 0.518 0.713
3.2. Analyzing Net Load Profile for Applying Revised ToU Tariff
The net load is the difference between the predicted load and the expected electricity
production from the VRE [
27
–
29
]. The increase or decrease in the net load curve is de-
pendent on the power generation output of the VRE and the electricity demand. When
VRE curtailment occurs in islanded power systems, the amount of VRE curtailment can
be mitigated if the power demand can be increased by providing a lower electricity price
signal than the price of the unrevised ToU tariff rates. Therefore, a revised ToU tariff is
proposed to mitigate the VRE curtailment by changing the electricity demand. This revised
ToU tariff rate is proposed by applying the concept of price elasticity of electricity demand,
which has been widely used to assess consumer behavior in the electricity market. The
price elasticity of demand can be used to design appropriate ToU tariffs to manage the load
in an islanded power system. A process to create the revised ToU tariff rates is summarized
as follows:
Netloadyear
t=Dyear
t−Pyear
VR E,t,t=1, 2, . . . , T(5)
where
Netloadyear
t
is the net load at time tof the year;
Dyear
max
is the maximum electric power
demand during the year;
Dyear
t
and
Pyear
VR E,t
are taken from Equations (2) and (3). In addition,
to analyze the value of
Netloadyear
t
, the value of
Netloadyear
t
is separated according to the
current ToU tariff time period to which time tbelongs.
Netloadyear
t=Netloadyear
s,p,t(t=1, 2, . . . , T;s=1, 2, 3; p=1, 2, 3)(6)
where
s=
1 refers to spring and autumn,
s=
2 is summer,
s=
3 is winter;
p=
1 is the
peak period,
p=
2 is the medium period, and
p=
3 is the off-peak period. Through the
separation of the net load,
Netloadyear
t
is divided into nine time periods, consisting of three
time periods per season (spring and autumn, summer, and winter).
If the ToU tariff rates for the time period where the most VRE curtailment occurred
for each season is lowered, a lower price signal is sent to consumers. Consumers will then
increase their electricity consumption during that time period, and the amount of VRE
curtailment can be mitigated. Therefore, it is necessary to determine the time period for
which the ToU tariff rates should be changed.
To determine the period for which the ToU tariffs rate is revised, the number of VRE
curtailments that have occurred for each of the three periods within the same season are
compared. The period with the highest VRE curtailment is that for which the ToU tariff
rates should be reduced.
Kyear
s,p
is the number of VRE curtailments for each season and
period. There are three periods (peak, medium, and off-peak) in each season, and the
numbers of VRE curtailments (
Kyear
s,p
) are compared for each period. During the period in
which the number of VRE curtailments (
Kyear
s,p
) is the greatest, the ToU tariff rates plan will

Electronics 2021,10, 135 10 of 20
be revised to be lower than the original plan. The flowchart for counting the number of
VRE curtailments is shown in Figure 3.
Electronics 2021, 10, x FOR PEER REVIEW 10 of 20
Figure 3. Flowchart for counting the number of VRE curtailments for each season and period.
3.3. Price Elasticity of Electricity Demand for Revised ToU Tariff
The concept of price elasticity of power demand is crucial for the proper design or
revision of ToU tariff rates. Decreasing the price of a product, even by a small amount,
will clearly increase demand. To determine the amount of change, we can use the deriva-
tive )
) of the demand curve. The price elasticity of electricity demand has defined
the ratio of the relative change in demand to the relative price change [30].
𝜀= 𝛥𝐷𝑒𝑚𝑎𝑛𝑑
𝐷𝑒𝑚𝑎𝑛𝑑
𝛥𝑃𝑟𝑖𝑐𝑒
𝑃𝑟𝑖𝑐𝑒 =
𝑃𝑟𝑖𝑐𝑒
𝐷𝑒𝑚𝑎𝑛𝑑 × 𝛥𝐷𝑒𝑚𝑎𝑛𝑑
𝛥𝑃𝑟𝑖𝑐𝑒 (7)
In the short run, the price elasticity of the demand for electricity is low because con-
sumers do not have enough choice. However, in the long run, the price elasticity of the
demand for electricity will be much higher because consumers have enough time to
choose other selections. In addition, the elasticity of the power demand depends in part
on the availability of substitutes. When dealing with substitutes and elasticity, the time-
scale for substitutions should be clearly defined. If two different electricity demands in
two different periods are complementary, a change in the demand for one will be accom-
panied by a similar change in the demand for the other.
In the case of transition of electricity demand from period A to period B, the electric-
ity consumption changes in certain hours of periods A and B depend on the changes in
the price 𝛥𝑃𝑟𝑖𝑐𝑒 for period A. That is, if the price for period A is lowered, the electricity
demand during period A may increase, but that of period B may decrease correspondingly.
The ratio of the relative demand change in period A according to the price change in
period A is defined as self-elasticity 𝜀, and the ratio of the relative demand change in
period B according to the price change in period A is defined as cross-elasticity 𝜀.
While the elasticity of a product to its own price (its self-elasticity) is always negative,
cross-elasticities between substitute products are positive because a decrease in the price
Figure 3. Flowchart for counting the number of VRE curtailments for each season and period.
3.3. Price Elasticity of Electricity Demand for Revised ToU Tariff
The concept of price elasticity of power demand is crucial for the proper design or
revision of ToU tariff rates. Decreasing the price of a product, even by a small amount, will
clearly increase demand. To determine the amount of change, we can use the derivative
d(Demand)
d(Price)
of the demand curve. The price elasticity of electricity demand has defined the
ratio of the relative change in demand to the relative price change [30].
ε=∆Demand
Demand /∆Price
Price =Price
Demand ×∆Demand
∆Price (7)
In the short run, the price elasticity of the demand for electricity is low because
consumers do not have enough choice. However, in the long run, the price elasticity of
the demand for electricity will be much higher because consumers have enough time to
choose other selections. In addition, the elasticity of the power demand depends in part on
the availability of substitutes. When dealing with substitutes and elasticity, the timescale
for substitutions should be clearly defined. If two different electricity demands in two
different periods are complementary, a change in the demand for one will be accompanied
by a similar change in the demand for the other.
In the case of transition of electricity demand from period Ato period B, the electricity
consumption changes in certain hours of periods Aand Bdepend on the changes in the
price
∆PriceA
for period A. That is, if the price for period Ais lowered, the electricity
demand during period Amay increase, but that of period Bmay decrease correspondingly.
The ratio of the relative demand change in period Aaccording to the price change
in period Ais defined as self-elasticity
εS
, and the ratio of the relative demand change in
period Baccording to the price change in period Ais defined as cross-elasticity εC.
While the elasticity of a product to its own price (its self-elasticity) is always negative,
cross-elasticities between substitute products are positive because a decrease in the price of

Electronics 2021,10, 135 11 of 20
one will spur a demand for the other. The self-elasticity
εS,AA
and cross-elasticity
εC,BA
in
periods Aand Bcan be described by the following equation:
εS,AA =∆DemandAA
DemandA,0
/∆PriceA
PriceA,0
,∆DemandAA =DemandA,1 −DemandA,0
∆PriceA=PriceA,1 −PriceA,0 (8)
εC,BA =∆DemandB A
DemandB,0
/∆PriceA
PriceA,0
,∆DemandBA =DemandB,1 −DemandB,0
∆PriceA=PriceA,1 −PriceA,0 (9)
where
εS,AA
is the self-elasticity, which is the ratio of the relative demand change in period
Aaccording to the price change in period A;
εC,BA
is the cross-elasticity, which is the ratio of
the relative demand change in period Baccording to the price change in period A;
∆PriceA
is the change in price of ToU tariff rates in period A;
PriceA,0
is the initial price of ToU tariff
rates in period A;
PriceA,1
is the change in the price of the revised ToU tariff rates in period
A;
∆DemandAA
and
∆DemandBA
are the changes in the electricity demand in periods Aand
B, respectively;
DemandA,0
and
DemandB,0
are the initial values of the electricity demand
in periods Aand B, respectively;
DemandA,1
and
DemandB,1
are the changed values of the
electricity demand in periods Aand B, respectively.
If the self-elasticity
εS,AA
and cross-elasticity
εC,BA
are known, the amount of change in
electricity demand for each period (A and B) can be calculated. Equations (8) and (9) above
can be expressed as the changed demand value ∆DemandAA and ∆DemandBA as follows:
∆DemandAA =εS,AA ×Price A,1 −PriceA,0
PriceA,0
×DemandA,0 (10)
∆DemandBA =εC,B A ×PriceA,1 −PriceA,0
PriceA,0
×DemandB,0 (11)
Reference [
18
] attempted to estimate the electricity demand function and obtain
quantitative values on the price elasticity of the electricity demand to derive long-run
and short-run elasticities using the time-series data from 1991 to 2014 in South Korea.
The short-run price elasticity of the electricity demand is estimated to be
−
0.142 and the
long-run price elasticity of the electricity demand is calculated to be
−
0.210. Since the price
elasticity is considered from a long-term perspective, the value of long-run price elasticity
was taken from reference [
18
] in this study. A conceptual illustration of the ability of the
revised ToU tariffs to mitigate the VRE curtailment is shown in Figure 4below.
Electronics 2021, 10, x FOR PEER REVIEW 11 of 20
of one will spur a demand for the other. The self-elasticity 𝜀, and cross-elasticity 𝜀,
in periods A and B can be described by the following equation:
𝜀, = 𝛥𝐷𝑒𝑚𝑎𝑛𝑑
𝐷𝑒𝑚𝑎𝑛𝑑,
𝛥𝑃𝑟𝑖𝑐𝑒
𝑃𝑟𝑖𝑐𝑒, ,
𝛥𝐷𝑒𝑚𝑎𝑛𝑑 = 𝐷𝑒𝑚𝑎𝑛𝑑, − 𝐷𝑒𝑚𝑎𝑛𝑑,
𝛥𝑃𝑟𝑖𝑐𝑒= 𝑃𝑟𝑖𝑐𝑒, − 𝑃𝑟𝑖𝑐𝑒,  (8)
𝜀, = 𝛥𝐷𝑒𝑚𝑎𝑛𝑑
𝐷𝑒𝑚𝑎𝑛𝑑,
𝛥𝑃𝑟𝑖𝑐𝑒
𝑃𝑟𝑖𝑐𝑒, ,
𝛥𝐷𝑒𝑚𝑎𝑛𝑑 = 𝐷𝑒𝑚𝑎𝑛𝑑, − 𝐷𝑒𝑚𝑎𝑛𝑑,
𝛥𝑃𝑟𝑖𝑐𝑒= 𝑃𝑟𝑖𝑐𝑒, − 𝑃𝑟𝑖𝑐𝑒,  (9)
where 𝜀, is the self-elasticity, which is the ratio of the relative demand change in pe-
riod A according to the price change in period A; 𝜀, is the cross-elasticity, which is the
ratio of the relative demand change in period B according to the price change in period A;
𝛥𝑃𝑟𝑖𝑐𝑒 is the change in price of ToU tariff rates in period A; 𝑃𝑟𝑖𝑐𝑒, is the initial price
of ToU tariff rates in period A; 𝑃𝑟𝑖𝑐𝑒, is the change in the price of the revised ToU tariff
rates in period A; 𝛥𝐷𝑒𝑚𝑎𝑛𝑑 and 𝛥𝐷𝑒𝑚𝑎𝑛𝑑 are the changes in the electricity de-
mand in periods A and B, respectively; 𝐷𝑒𝑚𝑎𝑛𝑑, and 𝐷𝑒𝑚𝑎𝑛𝑑, are the initial values
of the electricity demand in periods A and B, respectively; 𝐷𝑒𝑚𝑎𝑛𝑑, and 𝐷𝑒𝑚𝑎𝑛𝑑,
are the changed values of the electricity demand in periods A and B, respectively.
If the self-elasticity 𝜀, and cross-elasticity 𝜀, are known, the amount of change
in electricity demand for each period (A and B) can be calculated. Equations (8) and (9)
above can be expressed as the changed demand value 𝛥𝐷𝑒𝑚𝑎𝑛𝑑 and 𝛥𝐷𝑒𝑚𝑎𝑛𝑑 as
follows:
𝛥𝐷𝑒𝑚𝑎𝑛𝑑 =𝜀
, × 𝑃𝑟𝑖𝑐𝑒, − 𝑃𝑟𝑖𝑐𝑒,
𝑃𝑟𝑖𝑐𝑒, × 𝐷𝑒𝑚𝑎𝑛𝑑, (10)
𝛥𝐷𝑒𝑚𝑎𝑛𝑑 =𝜀, × 𝑃𝑟𝑖𝑐𝑒, − 𝑃𝑟𝑖𝑐𝑒,
𝑃𝑟𝑖𝑐𝑒, ×𝐷𝑒𝑚𝑎𝑛𝑑, (11)
Reference [18] attempted to estimate the electricity demand function and obtain
quantitative values on the price elasticity of the electricity demand to derive long-run and
short-run elasticities using the time-series data from 1991 to 2014 in South Korea. The
short-run price elasticity of the electricity demand is estimated to be −0.142 and the long-
run price elasticity of the electricity demand is calculated to be −0.210. Since the price elas-
ticity is considered from a long-term perspective, the value of long-run price elasticity was
taken from reference [18] in this study. A conceptual illustration of the ability of the re-
vised ToU tariffs to mitigate the VRE curtailment is shown in Figure 4 below.
Figure 4. Conceptual illustration of the mitigation of the VRE curtailment by revised ToU tariffs.
Figure 4. Conceptual illustration of the mitigation of the VRE curtailment by revised ToU tariffs.

Electronics 2021,10, 135 12 of 20
4. Case Study
4.1. Jeju Power System from 2022 to 2030
To analyze the VRE curtailment due to the expansion of renewable energy in Jeju in
the future, the predictions of the capacity and generation mix for the Jeju power system are
based on the data from [21,22].
The main dataset is the hourly supply and demand breakdown for Jeju from 2015
to 2017 obtained from KPX and KEPCO. The data used in this study are composed of all
the demand and power generation sources for each hour. It is hypothesized that VRE
curtailment will rapidly worsen as penetration of VRE continues to augment in line with
the Jeju CFI 2030 plan, unless appropriate actions to mitigate the VRE curtailment are
introduced in the Jeju power system. Figure 5shows the projected installed capacity for
Jeju until 2030 [21].
Electronics 2021, 10, x FOR PEER REVIEW 12 of 20
4. Case Study
4.1. Jeju Power System from 2022 to 2030
To analyze the VRE curtailment due to the expansion of renewable energy in Jeju in
the future, the predictions of the capacity and generation mix for the Jeju power system
are based on the data from [21,22].
The main dataset is the hourly supply and demand breakdown for Jeju from 2015 to
2017 obtained from KPX and KEPCO. The data used in this study are composed of all the
demand and power generation sources for each hour. It is hypothesized that VRE curtail-
ment will rapidly worsen as penetration of VRE continues to augment in line with the Jeju
CFI 2030 plan, unless appropriate actions to mitigate the VRE curtailment are introduced
in the Jeju power system. Figure 5 shows the projected installed capacity for Jeju until 2030
[21].
Figure 5. Projected installed capacity for Jeju until 2030.
In 2017, the installed capacity consisted of 400 MW from HVDC, 706 MW from con-
ventional generators, and 405 MW from renewable energy, but by 2030, increases to 600
MW for HVDC, 1016 MW for conventional generators, and 3782 MW for renewable en-
ergy are expected. In particular, the installed capacity of VRE will increase rapidly accord-
ing to the 2030 plan, and the amount of renewable energy that exceeds the demand of Jeju
Island is planned to be sent to the main grid of South Korea via the HVDC system. The
HVDC system on Jeju Island is a submarine cable interconnection between the Korean
peninsula and Jeju. Two HVDCs, the 180 kV/300 MW HVDC #1 and ±250 kV/400 MW
HVDC #2 [31,32], were constructed by KEPCO to support Jeju Island and integrate the
large amount of renewable energy. Furthermore, KEPCO is planning to construct one ad-
ditional ±150 kV/200 MW HVDC #3 between the mainland and Jeju Island in 2022 [33].
It was planned for HVDC #3 to transfer power from Jeju to the mainland in case the
power of renewable energy and the minimum power generation of other thermal power
generators exceeded the demand of Jeju Island. HVDC #1 and HVDC #2 are currently in
operation to support a stable power supply from the mainland to Jeju. It is planned for #3
HVDC begin operation between the mainland and Jeju in 2022. Moreover, Jeju Special
Self-Governing Province proposed an upgrade to enable reverse transmission of all
HVDCs by 2022 as one of the renewable energy expansion plans [34]. The reverse trans-
mission of HVDC interconnections from Jeju to the mainland is important in estimating
the VRE curtailment in Jeju Island, as it accounts for about 40% of the total power gener-
ation. A systematic procedure was applied in this study to estimate the future VRE cur-
tailment in the Jeju Island power system with #3 HVDC installed.
Figure 5. Projected installed capacity for Jeju until 2030.
In 2017, the installed capacity consisted of 400 MW from HVDC, 706 MW from
conventional generators, and 405 MW from renewable energy, but by 2030, increases to
600 MW for HVDC, 1016 MW for conventional generators, and 3782 MW for renewable
energy are expected. In particular, the installed capacity of VRE will increase rapidly
according to the 2030 plan, and the amount of renewable energy that exceeds the demand
of Jeju Island is planned to be sent to the main grid of South Korea via the HVDC system.
The HVDC system on Jeju Island is a submarine cable interconnection between the Korean
peninsula and Jeju. Two HVDCs, the 180 kV/300 MW HVDC #1 and
±
250 kV/400 MW
HVDC #2 [
31
,
32
], were constructed by KEPCO to support Jeju Island and integrate the
large amount of renewable energy. Furthermore, KEPCO is planning to construct one
additional
±
150 kV/200 MW HVDC #3 between the mainland and Jeju Island in 2022 [
33
].
It was planned for HVDC #3 to transfer power from Jeju to the mainland in case the
power of renewable energy and the minimum power generation of other thermal power
generators exceeded the demand of Jeju Island. HVDC #1 and HVDC #2 are currently in
operation to support a stable power supply from the mainland to Jeju. It is planned for
#3 HVDC begin operation between the mainland and Jeju in 2022. Moreover, Jeju Special
Self-Governing Province proposed an upgrade to enable reverse transmission of all HVDCs
by 2022 as one of the renewable energy expansion plans [
34
]. The reverse transmission
of HVDC interconnections from Jeju to the mainland is important in estimating the VRE
curtailment in Jeju Island, as it accounts for about 40% of the total power generation.

Electronics 2021,10, 135 13 of 20
A systematic procedure was applied in this study to estimate the future VRE curtailment
in the Jeju Island power system with #3 HVDC installed.
4.2. Estimation of VRE Curtailment in Jeju from 2022 to 2030
The reason for estimating the VRE curtailment from 2022 is to consider #3 HVDC
entering after 2022 from the currently established power resource forecast on Jeju Island [
33
].
The renewable energy capacity of Jeju Island will continue to increase to occupy 70% of the
total capacity in 2030. In the case of generation of wind power and PV, they are expected to
account for 74.5% of the total generation in 2030 based on the capacity factor for the year
2017. Each value is indicated in Table 6.
Table 6. The estimated power demand and the amount of VRE capacity of Jeju.
Year 2022 2023 2024 2025 2026 2027 2028 2029 2030
Max. Demand [MW] 1111 1138 1161 1182 1204 1227 1252 1282 1321
Total Generation [GWh] 6212 6454 6696 6935 7171 7403 7631 7853 8068
VRE (Wind) [MW] 975 1015 1075 1265 1365 1565 1815 2085 2345
VRE (PV) [MW] 659.9 780.3 911.7 1034 1121 1202 1270 1337 1411
Total RE Capacity [MW] 1635 1795 1987 2299 2486 2767 3085 3422 3756
The power demand (
Dyear
t
) was generated by time in 2017 based on the maximum
power demand and the total generation amount in [
21
]. The amount of VRE generation at
time tof the year (
Pyear
VR E,t
) was calculated based on the capacity factor of renewable energy
by 2017, reflecting the Jeju CFI plan [5].
The total minimum generation capacity of the thermal power generators (
Pyear
min,t
)
combines the minimum power generation capacity of four thermal generators based on
the current must-run generators of Jeju Island, comprising South Jeju #1, Jeju Thermal
#2, Jeju CC #1, and Jeju CC #2, considering overhaul periods. The sum of the minimum
power generation capacities of these four generators is 55 + 46 + 67 + 67 = 235 MW. Table 7
shows the values of minimum generation capacity and maximum generation capacity of
all generators in Jeju [35].
Table 7. The minimum and maximum of generation capacity of all conventional generators in Jeju.
Generators Min. Max.
South Jeju #1, #2 55 103
Jeju Thermal #2, #3 46 79
Jeju CC #1, #2 (2019~) 67 102
Hanlim CC (Hanlim GT) 43 (28) 104 (74)
Jeju Internal Combustion Engine #1, #2 28 40
South Jeju CC 90 125
Jeju GT #3 16 49
The amount of maximum power transmission of HVDC (
HV DCyear
max,t
) was calculated
based on the sum of the HVDC maximum reverse supply capacity considering the HVDC
N-1 contingency (300 MW), the minimum operation capacity (40 MW), and overhaul
periods. The maximum amount of reversal transmission of each HVDC is 120 MW for
#1 HVDC, 240 MW for #2 HVDC, and 200 MW for #3 HVDC. This means that 560 MW
of maximum power transmission of HVDC can be transferred from Jeju to the main grid
via HVDC.
To determine the net load of a specific year in islanded power systems, we combined
the values of the power demand with values of the seasonal VRE generation provided
by KPX. The numerical result analysis shows the amount of total generation, the amount
of VRE generation, and the amount of VRE curtailment each year. It also shows the VRE
curtailment time and the VRE curtailment rate. The rate of VRE curtailment is expected to
exceed 1% of the annual VRE generation from 2025. In 2030, the rate of VRE curtailment is

Electronics 2021,10, 135 14 of 20
expected to exceed approximately 10%. Figure 6and Table 8show the estimation of VRE
curtailment results.
Electronics 2021, 10, x FOR PEER REVIEW 14 of 20
curtailment time and the VRE curtailment rate. The rate of VRE curtailment is expected to
exceed 1% of the annual VRE generation from 2025. In 2030, the rate of VRE curtailment
is expected to exceed approximately 10%. Figure 6 and Table 8 show the estimation of
VRE curtailment results.
Figure 6. The duration curve of the net load in Jeju from 2022 to 2030.
Table 8. Amount of curtailment for each year.
Year
Total
generation
[GWh]
VRE Generation VRE Curtailment
Wind
[GWh]
PV
[GWh]
Total
[GWh]
Curtailment
[MWh]
Time
[Hour]
Rate of
Curtailment [%]
2022 6212 1941.13 627.57 2568.70 1820.73 30 0.07
2023 6454 2020.76 742.08 2762.84 5079.92 63 0.18
2024 6696 2140.21 867.04 3007.25 12,532.10 109 0.42
2025 6935 2518.49 983.35 3501.83 41,043.24 246 1.17
2026 7171 2717.58 1066.09 3783.66 63,971.86 337 1.69
2027 7403 3115.75 1143.12 4258.87 126,844.75 597 2.98
2028 7631 3613.48 1207.79 4821.27 249,186.03 945 5.17
2029 7853 4151.02 1271.51 5422.53 432,456.04 1301 7.98
2030 8068 4668.65 1341.88 6010.54 646,447.13 1609 10.76
As shown in Figure 6 and Table 8 above, the estimation of the annual VRE curtail-
ment increases noticeably. VRE curtailment causes waste of VRE and low efficiency,
which should be mitigated. The mitigation of VRE curtailment in terms of the electricity
retail market by adjusting the electricity demand when VRE curtailment occurs is pro-
posed in Section 4.3.
4.3. Mitigation of VRE Curtailment by the Revised ToU Tariff
A mitigation procedure for VRE curtailment in Jeju Island was calculated based on
2022 conditions. The reason for this is to consider the reverse transmission of the grid
interconnection line after #3 HVDC enters the Jeju power system.
Figure 6. The duration curve of the net load in Jeju from 2022 to 2030.
Table 8. Amount of curtailment for each year.
Year
Total
generation
[GWh]
VRE Generation VRE Curtailment
Wind
[GWh]
PV
[GWh]
Total
[GWh]
Curtailment
[MWh]
Time
[Hour]
Rate of
Curtailment [%]
2022 6212 1941.13 627.57 2568.70 1820.73 30 0.07
2023 6454 2020.76 742.08 2762.84 5079.92 63 0.18
2024 6696 2140.21 867.04 3007.25 12,532.10 109 0.42
2025 6935 2518.49 983.35 3501.83 41,043.24 246 1.17
2026 7171 2717.58 1066.09 3783.66 63,971.86 337 1.69
2027 7403 3115.75 1143.12 4258.87 126,844.75 597 2.98
2028 7631 3613.48 1207.79 4821.27 249,186.03 945 5.17
2029 7853 4151.02 1271.51 5422.53 432,456.04 1301 7.98
2030 8068 4668.65 1341.88 6010.54 646,447.13 1609 10.76
As shown in Figure 6and Table 8above, the estimation of the annual VRE curtailment
increases noticeably. VRE curtailment causes waste of VRE and low efficiency, which
should be mitigated. The mitigation of VRE curtailment in terms of the electricity retail
market by adjusting the electricity demand when VRE curtailment occurs is proposed in
Section 4.3.
4.3. Mitigation of VRE Curtailment by the Revised ToU Tariff
A mitigation procedure for VRE curtailment in Jeju Island was calculated based on
2022 conditions. The reason for this is to consider the reverse transmission of the grid
interconnection line after #3 HVDC enters the Jeju power system.
As suggested earlier in Section 3, to determine the period for which the ToU tariff rates
should be revised, the numbers of VRE curtailments that have occurred for each of the
three periods within the same season are compared. The ToU tariff rates will be reduced

Electronics 2021,10, 135 15 of 20
for the period with the highest VRE curtailment. In order to examine the number of VRE
curtailments, the predicted seasonal monthly net load curve and the predicted number of
times of VRE curtailment per hour in Jeju during 2022 are shown in Figures 7and 8below.
Electronics 2021, 10, x FOR PEER REVIEW 15 of 20
As suggested earlier in Section 3, to determine the period for which the ToU tariff
rates should be revised, the numbers of VRE curtailments that have occurred for each of
the three periods within the same season are compared. The ToU tariff rates will be re-
duced for the period with the highest VRE curtailment. In order to examine the number
of VRE curtailments, the predicted seasonal monthly net load curve and the predicted
number of times of VRE curtailment per hour in Jeju during 2022 are shown in Figure 7
and Figure 8 below.
(a)
(b)
(c)
(d)
Figure 7. Estimated seasonal monthly net load curve in Jeju 2022: (a) spring; (b) summer; (c) autumn; (d) winter.
Figure 7. Estimated seasonal monthly net load curve in Jeju 2022: (a) spring; (b) summer; (c) autumn; (d) winter.

Electronics 2021,10, 135 16 of 20
Electronics 2021, 10, x FOR PEER REVIEW 16 of 20
Figure 8. The number of times of estimated VRE curtailment per hour in Jeju 2022.
The period with the highest number of estimated VRE curtailments will have its ToU
tariff rates reduced. 𝐾,
 is the number of VRE curtailments for each season and period.
The analysis results of the number of estimated VRE curtailments for each season and
period in Jeju for 2022 are shown in Table 9.
Table 9. Analysis results of the number of VRE curtailment 𝐾
,

in Jeju 2022.
Season 𝑲𝒔,𝒑
𝟐𝟎𝟐𝟐 of Period 1
(On-Peak) 𝑲𝒔,𝒑
𝟐𝟎𝟐𝟐 of Period 2
(Medium) 𝑲𝒔,𝒑
𝟐𝟎𝟐𝟐 of Period 3
(Off-Peak)
Spring and Autumn 𝐾,
 = 20 𝐾,
 = 7 𝐾,
 = 0
Summer 𝐾,
 = 0 𝐾,
 = 0 𝐾,
 = 0
Winter 𝐾,
 = 0 𝐾,
 = 3 𝐾,
 = 0
As of 2017, the proportion of electricity used that was covered by the ToU tariff rates
in Jeju Island was 52.6% from Table 3. It is difficult to know the exact proportion of ToU
tariff users for any specific time in the estimated year. In this study, the proportion of ToU
tariff users in 2017, 52.6%, was applied. In addition, the comparison between the current
ToU tariff and the revised ToU tariff rates is shown in Table 10.
Table 10. Comparison between current ToU tariff and revised ToU tariff rates.
Average
(Max.~Min.)
[Won/kWh]
Current ToU Tariff Rates Revised ToU Tariff Rates
Spring and Au-
tumn Summer Winter
Spring and Au-
tumn Summer Winter
Peak 91.9
(68.1~114.8)
157.7
(114.2~196.6)
137.3
(106.7~172.2) Scenarios 157.7
(114.2~196.6)
137.3
(106.7~172.2)
Medium 70.2
(58.0~84.1)
101.0
(80.4~114.5)
98.0
(78.0~114.7)
70.2
(58.0~84.1)
101.0
(80.4~114.5)
98.0
(78.0~114.7)
Off-Peak 55.4
(43.8~62.7)
55.4
(43.8~62.7)
62.3
(47.6~71.4)
55.4
(43.8~62.7)
55.4
(43.8~62.7)
62.3
(47.6~71.4)
The number of occurrences of VRE curtailment for Period 1 (𝐾,
) in spring and
autumn was the highest at 20 times in 2022. The time of Period 1 in the spring and autumn
is 10:00–12:00 am and 13:00–17:00 pm (6 h). Similar to the systematic procedure described
above in Section 3, the ToU tariff rates of Period 1 in the spring and autumn seasons were
lowered by price scenarios. The composition of scenarios for applying the revised ToU
tariff rates is shown in Table 11.
Figure 8. The number of times of estimated VRE curtailment per hour in Jeju 2022.
The period with the highest number of estimated VRE curtailments will have its ToU
tariff rates reduced.
K2022
s,p
is the number of VRE curtailments for each season and period.
The analysis results of the number of estimated VRE curtailments for each season and
period in Jeju for 2022 are shown in Table 9.
Table 9. Analysis results of the number of VRE curtailment K2022
s,pin Jeju 2022.
Season K2022
s,pof Period 1
(On-Peak)
K2022
s,pof Period 2
(Medium)
K2022
s,pof Period 3
(Off-Peak)
Spring and Autumn K2022
1,1 = 20 K2022
1,2 = 7 K2022
1,3 = 0
Summer K2022
2,1 = 0 K2022
2,2 = 0 K2022
2,3 = 0
Winter K2022
3,1 = 0 K2022
3,2 = 3 K2022
3,3 = 0
As of 2017, the proportion of electricity used that was covered by the ToU tariff rates
in Jeju Island was 52.6% from Table 3. It is difficult to know the exact proportion of ToU
tariff users for any specific time in the estimated year. In this study, the proportion of ToU
tariff users in 2017, 52.6%, was applied. In addition, the comparison between the current
ToU tariff and the revised ToU tariff rates is shown in Table 10.
Table 10. Comparison between current ToU tariff and revised ToU tariff rates.
Average
(Max.~Min.)
[Won/kWh]
Current ToU Tariff Rates Revised ToU Tariff Rates
Spring and
Autumn Summer Winter Spring and
Autumn Summer Winter
Peak 91.9
(68.1~114.8)
157.7
(114.2~196.6)
137.3
(106.7~172.2) Scenarios 157.7
(114.2~196.6)
137.3
(106.7~172.2)
Medium 70.2
(58.0~84.1)
101.0
(80.4~114.5)
98.0
(78.0~114.7)
70.2
(58.0~84.1)
101.0
(80.4~114.5)
98.0
(78.0~114.7)
Off-Peak 55.4
(43.8~62.7)
55.4
(43.8~62.7)
62.3
(47.6~71.4)
55.4
(43.8~62.7)
55.4
(43.8~62.7)
62.3
(47.6~71.4)
The number of occurrences of VRE curtailment for Period 1 (
K2022
1,1
) in spring and
autumn was the highest at 20 times in 2022. The time of Period 1 in the spring and autumn
is 10:00–12:00 am and 13:00–17:00 pm (6 h). Similar to the systematic procedure described
above in Section 3, the ToU tariff rates of Period 1 in the spring and autumn seasons were
lowered by price scenarios. The composition of scenarios for applying the revised ToU
tariff rates is shown in Table 11.

Electronics 2021,10, 135 17 of 20
Table 11. The composition of scenarios for applying the revised ToU tariff rates.
Season and Period
(The Highest Number of
VRE Curtailment)
[Time Interval]
Period
(Demand
Changed)
[Time Interval]
Price
Elasticities
Scenarios
Price Demand
εS,AA εC,BA Period A∆DemandAA ∆DemandBA
Spring
and
Autumn
A1[10~12] A1[10~12] −0.21 - 5% Down UP Down
B1[07~09] - +0.21 10% Down UP Down
A2[13~17] A2[13~17] −0.21 - 20% Down UP Down
B2[18~22] - +0.21 30% Down UP Down
During the peak periods in the spring and autumn seasons, a decrease in ToU tariff
rates from 10:00 to 12:00 am (2 h) was assumed to be a factor for increasing demand from
07:00 to 09:00 am (2 h) during the off-peak period. In addition, a decrease in ToU tariff
rates from 13:00 to 17:00 pm (4 h) was assumed to be a factor for increasing demand from
18:00 to 22:00 pm (4 h) in the medium-peak period. In addition, we forecasted changes in
electricity demand when long-term price elasticity was applied to ToU tariff rate users.
The ToU tariff rates for the on-peak period in the spring and autumn seasons where
the VRE curtailment occurred the most were changed by 5%, 10%, 20%, and 30% in
different pricing scenarios. The long-run price elasticity of the electricity demand was
calculated by [
18
] in these scenarios. The self-elasticity (
εS,AA )
is
−
0.21, which is the ratio
of change in relative demand for periods
A1
and
A2
to price changes in periods
A1
and
A2
, respectively. In contrast, the cross-elasticity (
εC,BA )
is +0.21, which is the ratio of
change in relative demand for periods
B1
and
B2
to price changes in periods
A1
and
A2
,
respectively. According to Equations (10) and (11), the changed demand values
DemandA,1
and DemandB,1 can be calculated by applying price scenarios as follows:
DemandA,1 =εS,AA ×PriceA,1 −PriceA,0
PriceA,0
×DemandA,0 +Demand A,0 (12)
DemandB,1 =εC,BA ×PriceA,1 −PriceA,0
PriceA,0
×DemandB,0+DemandB,0 (13)
Table 12 shows the amount of annual VRE curtailment, time of annual VRE curtail-
ment, and rate of annual VRE curtailment according to the revised ToU rates proposed for
the mitigation scenarios.
Table 12. Results of annual VRE curtailment by mitigation scenarios.
Scenarios VRE Generation
[GWh]
VRE Curtailment Rate of
Mitigation [%]
Curtailment
[MWh]
Time
[Hour]
Rate of
Curtailment [%]
No Mitigation 2568.70 1820.73 30 0.071 0
5% Down 2568.70 1736.67 30 0.068 4.62
10% Down 2568.70 1653.97 29 0.064 9.16
20% Down 2568.70 1497.07 28 0.058 17.78
30% Down 2568.70 1345.12 28 0.052 26.12
The rate changes of mitigation in the VRE curtailment between no mitigation and the
mitigation procedure of the revised ToU tariff rates show how much the VRE curtailment
was decreased due to the application of the revised ToU tariff rates. These results can affect
the operation of a stable islanded power system by improving the efficiency of the revised
ToU tariff rates applied by power market operators and grid operators based on the ToU
rate tariff rates plan.

Electronics 2021,10, 135 18 of 20
5. Conclusions
Although VRE curtailment can be effective to ensure power balance, mitigating
VRE curtailment to improve system efficiency should be the goal of the power system
operator. Moreover, the ToU tariff rates are the form of rate design most widely used to
generate incentives for customers to switch to usage at a better time for a stable islanded
power system. This paper explains how much VRE curtailment can be mitigated as the
scenarios, when the electricity price of specific seasons and hours changes, within existed
time schemes of ToU tariff rates. In other words, it only changes the price by specific
season and hour, while maintaining the existing seasons and hours schemes of ToU tariff.
Therefore, reasonable and cost-effective schemes of ToU tariff rates that can mitigate
the VRE curtailment in islanded power systems is to adjust the price at specific seasons
and hours. We suggest that islanded power system operators find these specific seasons
and hours when VRE curtailment occurs the most by analyzing the net load profile and
following the procedures listed above.
The aim of this paper is to propose a systematic procedure for mitigating VRE cur-
tailment by changing the electricity demand through price changes of the ToU tariffs rates
in the Jeju electricity market. The procedure is based on a load profile comparison of
customers, such as general, educational, and industrial, using ToU tariffs. A case study
of mitigating the VRE curtailment in Jeju in 2022 through the procedure described above
is presented, and we forecast changes in electricity demand when applying long-term
price elasticity to ToU tariffs users. The ToU tariff rates for the periods where the VRE
curtailment occurred most were changed by 5%, 10%, 20%, and 30%, and a reduced amount
of VRE curtailment was shown in the results. These results can affect the operation of a
stable power system by improving the efficiency of the demand response program applied
by power market operators and grid operators based on the ToU rate tariff rate plan. For
future work, to provide greater validity to the values of the revised ToU tariffs, this study
needs to be widened to a synthesis of nation-level research by embodying the national
power demand and the price elasticity of electricity demand.
Author Contributions:
Conceptualization, J.L. (Jinyeong Lee), J.L. (Jaehee Lee) and Y.-M.W.; method-
ology, J.L. (Jinyeong Lee); data curation, J.L. (Jinyeong Lee); writing—original draft preparation, J.L.
(Jinyeong Lee); writing—review and editing, J.L. (Jinyeong Lee) and J.L. (Jaehee Lee); supervision,
Y.-M.W. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: The data are not publicly available due to confidential issue.
Acknowledgments:
This work was supported by a National Research Foundation of Korea (NRF)
grant funded by the Korea government (MSIT) (NRF-2020R1C1C1013228). This work was supported
by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of
Trade, Industry and Energy (MOTIE) of the Republic of Korea (No. 20181210301430). This work was
supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the
Ministry of Trade, Industry and Energy (MOTIE) of the Republic of Korea (No. 20173010013610).
Conflicts of Interest: The authors declare no conflict of interest.
References
1.
Ellabban, O.; Abu-Rub, H.; Blaabjerg, F. Renewable energy resources: Current status, future prospects and their enabling
technology. Renew. Sustain. Energy Rev. 2014,39, 748–764. [CrossRef]
2.
Panwar, N.L.; Kaushik, S.C.; Kothari, S. Role of renewable energy sources in environmental protection: A review. Renew. Sustain.
Energy Rev. 2011,15, 1513–1524. [CrossRef]
3.
Jeju Special Self-Governing Province. Carbon Free Island Jeju by 2030. Available online: http://www.ksga.org/down/down.asp?
file=Carbon%20Free%20Island%20Jeju%20by%202030.pdf (accessed on 28 October 2020).

Electronics 2021,10, 135 19 of 20
4.
The Centre of Excellence (COE) for the Sustainable Development of Small Island Developing States. The Path to a Carbon-
Free Island, Jeju—Republic of Korea, 2019. Available online: http://www.sustainablesids.org/wp-content/uploads/2019/0
1/COE-Case-Study-in-Sustainable-Energy-The-Path-to-a- Carbon-free-Island-Jeju-Republic-of-Korea-2019.pdf (accessed on
28 October 2020).
5.
Korea Energy Economics Institute (KEEI). Modified CFI 2030 Plan to Implement Energy Self-Reliance Island; KEEI: Ulsan, Korea, 2019.
6.
Nguyen, N.; Mitra, J. Reliability of Power System with High Wind Penetration Under Frequency Stability Constraint. IEEE
Trans.Power Syst. 2018,33, 985–994. [CrossRef]
7.
Baharvandi, A.; Aghaei, J.; Niknam, T.; Shafie-Khah, M.; Godina, R.; Nojavan, S. Bundled Generation and Transmission Planning
Under Demand and Wind Generation Uncertainty Based on a Combination of Robust and Stochastic Optimization. IEEE Trans.
Sustain. Energy 2018,9, 1477–1486. [CrossRef]
8.
Ueckerdt, F.; Brecha, R.J.; Luderer, G. Analyzing major challenges of wind and solar variability in power systems. Renew. Energy
2015,81, 1–10. [CrossRef]
9.
Bird, L.; Milligan, M.; Lew, D. Integrating Variable Renewable Energy: Challenges and Solutions; National Renewable Energy
Laboratory (NREL): Golden, CO, USA, 2013.
10. Sigrist, L.; Lobato, E.; Echavarren, F.M.; Egido, I.; Rouco, L. Island Power Systems, 1st ed.; CRC Press: Boca Raton, FL, USA, 2016;
pp. 1–26.
11.
Lew, D.; Bird, L.; Milligan, M.; Speer, B.; Wang, X.; Carlini, E.M.; Estanqueiro, A.; Flynn, D.; Gomez-Lazaro, E.; Menemenlis, N.;
et al. Wind and Solar Curtailment. In Proceedings of the International Workshop on Large-Scale Integration of Wind Power into
Power Systems, London, UK, 22–24 October 2013.
12.
Bunodiere, A.; Lee, H.S. Renewable Energy Curtailment: Prediction Using a Logic-Based Forecasting Method and Mitigation
Measures in Kyushu, Japan. Energies 2020,13, 4703. [CrossRef]
13.
Lee, J.; Lee, J.; Wi, Y.-M.; Joo, S.-K. Stochastic Wind Curtailment Scheduling for Mitigation of Short-Term Variations in a Power
System with High Wind Power and Electric Vehicle. Appl. Sci. 2018,8, 1684. [CrossRef]
14.
Sabera, H.; Moeini-Aghtaie, M.; Ehsan, M.; Fotuhi-Firuzabada, M. A scenario-based planning framework for energy storage
systems with the main goal of mitigating wind curtailment issue. Int. J. Electr. Power Energy Syst.
2019
,104, 414–422. [CrossRef]
15. Han, Y.R. State of Duck Curve in California, USA and Response Policy. Electr. World Mon. Mag. 2018,493, 35–41.
16.
Brenna, M.; Foiadelli, F.; Longo, M.; Zaninelli, D. Improvement of Wind Energy Production through HVDC Systems. Energies
2017,10, 157. [CrossRef]
17.
Cochran, J.; Miller, M.; Zinaman, O.; Milligan, M.; Arent, D.; Palmintier, B.; O’Malley, M.; Mueller, S.; Lannoye, E.; Tuohy, A.; et al.
Flexibility in 21st Century Power Systems; National Renewable Energy Lab.: Golden, CO, USA, 2014.
18.
Ahn, S.Y.; Jin, S.J.; Yoo, S.H. Estimation of the electricity demand function using a lagged dependent variable model. J. Energy
Eng. 2016,25, 37–44. [CrossRef]
19.
Liu, P.; Yu, J.; Fan, S.; Bi, K.; An, Q. PEV Charging Coordination Using Adaptive Time-of-use Tariffs to Reduce Wind Energy
Curtailment. In Proceedings of the 2018 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific),
Bangkok, Thailand, 6–9 June 2018.
20.
Jeon, W.; Cho, S.; Lee, S. Estimating the Impact of Electric Vehicle Demand Response Programs in a Grid with Varying Levels of
Renewable Energy Sources: Time-of-Use Tariff versus Smart Charging. Energies 2020,13, 4365. [CrossRef]
21.
Ministry of Trade, Industry and Energy (MOTIE). The 8th Basic Plan for Long-Term Electricity Supply and Demand (2017~2031);
MOTIE: Sejong, Korea, 2017.
22.
Ministry of Trade, Industry and Energy (MOTIE). The 3rd Basic Plan for Long-Term Energy Supply and Demand (2020~2040); MOTIE:
Sejong, Korea, 2019.
23.
Myung, H.S.; Kim, H.C.; Kang, N.H.; Kim, Y.H.; Kim, S.H. Analysis of the Load Contribution of Wind Power and Photovoltaic
Power to Power System in Jeju. J. Korean Solar Energy Soc. 2018,38, 13–24.
24.
Kim, S.; Lee, H.; Kim, H.; Jang, D.H.; Kim, H.J.; Hur, J.; Cho, Y.S.; Hur, K. Improvement in policy and proactive interconnection
procedure for renewable energy expansion in South Korea. Renew. Sustain. Energy Rev. 2018,98, 150–162. [CrossRef]
25.
Korea Electric Power Corporation. Statistics of Electric Power in Korea, June 2018. Available online: https://home.kepco.co.
kr/kepco/cmmn/fms/FileDownSecure.do?atchFileId=ebc971a9521982009dab568591f3135dcd127129c9ad22a4aed6e67d7c1a5
7dfd4&fileSn=96d2f7b28d01c0ba8073192bc050ecd7e7 (accessed on 28 October 2020).
26.
Korea Electric Power Corporation. Electric Rates Table in South Korea, July 2019. Available online: http://cyber.kepco.co.kr/
ckepco/front/jsp/CY/E/E/CYEEHP00201.jsp (accessed on 28 October 2020).
27.
Holttinen, H.; Kiviluoma, J.; Estanquerio, A.; Gomez-Lazaro, E.; Rawn, B.; Dobschinski, J.; Meibom, P.; Lannoye, E.; Aigner,
T.; Wan, Y.H.; et al. Variability of load and net load in case of large-scale distributed wind power. In Proceedings of the 10th
International Workshop on Large-Scale Integration of Wind Power into Power Systems as Well as on Transmission Networks for
Offshore Wind farms, Aarhus, Denmark, 25–26 October 2011.
28.
Zhang, L.; Shi, J.; Wang, L.; Xu, C. Electricity, Heat, and Gas Load Forecasting Based on Deep Multitask Learning in Industrial-Park
Integrated Energy System. Entropy 2020,22, 1355. [CrossRef] [PubMed]
29.
Li, T.; Qian, Z.; He, T. Short-Term Load Forecasting with Improved CEEMDAN and GWO-Based Multiple Kernel ELM. Complexity
2020,2020, 1–20. [CrossRef]
30. Kirschen, D.S.; Strbac, G. Fundamentals of Power System Economics; John Wiley & Sons: Hoboken, NJ, USA, 2004.

Electronics 2021,10, 135 20 of 20
31.
Jang, G.; Oh, S.; Han, B.M.; Kim, C.K. Novel reactive power compensation scheme for the Jeju-Haenam HVDC system. IEE Proc.
Gener. Transm. Ditrib. 2005,152, 514–520. [CrossRef]
32.
Market, P.E.; Skliutas, J.P.; Sung, P.Y.; Kim, K.S.; Kim, H.M.; Sailer, L.H.; Young, R.R. New synchronous condensers for Jeju island.
In Proceedings of the 2012 IEEE Power & Energy Society General Meeting, San Diego, CA, USA, 22–26 July 2012.
33.
Korea Institute of Energy Technology Evaluation and Planning (KETEP). Green Energy New Deal Briefs, September 2020. Avail-
able online: http://energytransitionkorea.org/sites/default/files/2020-09/%EA%B7%B8%EB%A6%B0%EC%97%90%EB%84%8
8%EC%A7%80%EB%89%B4%EB%94%9C%20%EB%B8%8C%EB%A6%AC%ED%94%84%209%EC%9B%94%ED%98%B8.pdf (ac-
cessed on 28 October 2020).
34.
Jeju Special Self-Governing Province. 6th Local Energy Plan for the CFI, January 2020. Available online: http://www.prism.go.kr/
homepage/researchCommon/downloadResearchAttachFile.do;jsessionid=F5062C5E781CAB59E07A9A515CE89D8A.node02?
work_key=001&file_type=CPR&seq_no=001&pdf_conv_yn=Y&research_id=6500000-202000092 (accessed on 28 October 2020).
35.
Kim, Y.H.; Kim, S.H. Increasing Effect Analysis of the Wind Power Limit Using Energy Storage System in Jeju-Korea. J. Korean
Solar Energy Soc. 2014,34, 81–90. [CrossRef]