Economic Feasibility of the Investment in Residential Photovoltaics System Considering the Effects of Subsidy Policies: A Korean Case Journal: The… [623016]

For Peer Review Only
Economic Feasibility of the Investment in Residential
Photovoltaics System Considering the Effects of Subsidy
Policies: A Korean Case
Journal: The Engineering Economist
Manuscript ID UTEE-2019-1919
Manuscript Type: Case Reports
Keywords: Case Study

URL: http://mc.manuscriptcentral.com/uteeThe Engineering Economist

For Peer Review OnlyEconomic Feasibility of the Investment in Residential Photovoltaics System
Considering the Effects of Subsidy Policies: A Korean Case
The economic feasibility of the investment is critical for residential users’ decision making in investing
photovoltaic (PV) systems because the high costs of installing PV technology may be burdensome.
Therefore, governments in many countries have been implementing policies to reduce the economic
burden of household users' PV investments and thus promote solar energy to household users. The
purpose of this paper is to perform an economic feasibility analysis of investments in residential PV
systems that considers the effects of several subsidy plan alternatives using the empirical data of Korea.
The result shows that the residential PV investment project would be economically viable without
subsidy, however a payback period exceeds 10 years which could be perceived by residential customers
as too long to be attractive enough to invest in a PV system at present. In addition, we found that the
net present value is highest under the production based subsidy scheme, whereas the payback period is
shortest with a lump-sum subsidy.
Introduction
The energy consumption of conventional fossil fuel sources increased by 14.1% in 2016, despite their
contributions to environmental problems (BP, 2017). It is now widely argued that shifting to renewable
energy (RE) could help reduce greenhouse gas emissions, thereby limiting future extreme weather and
climate impacts, as well as ensuring the non-depletable and cost-efficient delivery of energy (Ellabban
et al., 2014). Many countries focus on policies that promote the use of RE in the energy sector. For
example, the Korean government has implemented an RE diffusion policy through the Korea Energy
Agency (KEA) with an aim to expand RE use to 20% by 2030 and thus reform the national energy
economy structure into an eco-friendly and highly efficient system. In particular, the government plans
to increase the penetration rate of photovoltaic (PV) power from 2.7% to 14.1%, making it one of the Page 1 of 31
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For Peer Review Onlykey sources of energy by 2035. An emphasis has also been placed on policies for the successful
diffusion of PV power for residential use to increase the penetration rate and expand the social
awareness of RE.
Among the various technologies based on renewable and sustainable energy sources, PV is an
attractive RE source for residential users because of its noiselessness, lack of carbon dioxide emissions
during operation, scale flexibility, and relatively simple operation and maintenance (Ho et al., 2009).
However, although all the benchmarked prices of PV systems have been trending downward (Fu et al.,
2017), it is still crucial for solar PV policies to overcome the financial barriers associated with the high
initial costs of PV systems compared with conventional energy. Above all, for residential users who
wish to adopt PV as a major RE source of electricity generation, the economic feasibility of the
investment is critical for decision making because the high costs of installing PV technology may be
burdensome.
Governments in many countries have been implementing policies to reduce the economic burden of
household users' solar investments and thus promote solar energy to household users. For example, the
United States and countries in Europe have implemented various PV dissemination policies for
residential users, including initial lump-sum subsidies and performance-based incentives, such as Feed-
in-Tariff (FIT). Several studies have suggested improvements for FIT. Bertoldi et al. (2013) suggested
the use of an energy-savings FIT to reward consumers for saved kilowatt-hours rather than discouraging
energy consumption by an additional tax. Leepa et al. (2013) proposed a FIT scheme tied to PV panel
prices, which was compared to a constant FIT and linearly decreasing FIT scheme. Lesser and Su (2008)
designed a two-part FIT, with payments based on system capacity and the market price for electricity.
In Korea, the current policies related to the dissemination of residential PV systems are mainly
focused on subsidizing a significant amount of money upfront, which can be subtracted from the
installation costs of the initial stage. In 2018, the Korean government, represented by KEA, set up a Page 2 of 31
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For Peer Review Onlytotal budget of 50 billion KRW1 in capital subsidies for residential PV system installation, which was
2.5 times larger than in the previous year. KEA provides the subsidies on a gradual scale depending on
the installation capacity of a PV system up to 3 kW and the average monthly consumption of electricity.
In recent years, many studies have been conducted on the economic impact of residential PV
investments and the effect of solar diffusion policies on these investments. For example, Boeck et al.
(2016) examined the effects of different support policies for residential PV systems in EU countries,
such as Belgium, Germany, Italy, Spain, and France, using a discounted cash flow model during the
lifetime of the facility. In Spain, support policies failed to achieve economic gains, although they were
shown to be effective in other countries. Nicholls et al. (2015) evaluated the life-cycle economic benefits
of rooftop PV installation in Australia. Hirvonen et al. (2015) focused on production-based policies in
Finland that required 2 to 3 times the initial installation costs in a payback period of 20 years. In the
United States, Lee et al. (2017) conducted a break-even analysis of residential PV systems by state
based on their present value, profitability index, and payback period. In this study, 18 of 51 target cities
reached the break-even point, with 7 cities being very adequate for PV systems due to their high levels
of incentives. Matisoff and Johnson (2017) paired incentive policy types with the amount of new
installations of residential PV systems and compared residential PV incentive policies in the United
States from the perspective of economic effectiveness. In other countries, Ghosh et al. (2015) performed
a techno-economic analysis of rooftop PV systems for both residential and industrial use in India. Watts
et al. (2015) conducted a comparison analysis on the economic effects of net billing policies in Chile.
In a net billing scheme, excess electricity is compensated monetarily, whereas net metering is designed
to offset it from the total amount received from the network. In Korea, Oh et al. (2013) determined that
it was reasonable to subsidize potential users by decreasing the payback period. No and Kim (2015)
showed that the payback period has faced continual decreases due to product price drops. In 2015, the
payback period of a 3-kW facility in Korea was 8 years.
1 KRW is the monetary unit of Korea. The exchange rate for $1 was approximately 1,150 KRW in 2018.Page 3 of 31
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For Peer Review OnlySeveral studies have suggested new criteria or measurement tools for the economic analysis of
household PV investments. Bertsch et al. (2017) suggested self-sufficiency—the ratio of self-consumed
PV electricity to total electricity demand—as an indicator of a PV system’s profitability. Based on self-
sufficiency, the authors found that the cost of a PV system and the availability of FIT are crucial drivers
of the profitability of household PV investments. Tantisattayakul and Kanchanapiya (2017) examined
financial measures for promoting and stimulating residential PV investments under a FIT policy in
Thailand; they concluded that a low-interest-rate loan appears to be the best measure. Although not
considering PV systems, He et al. (2016) proposed an improved evaluation index system of the benefits
and efficiency of energy system investment projects.
Although the aforementioned studies have focused on evaluating the economic impacts of existing
subsidy policies on residential PV investments, some other studies have pointed out limitations of
existing support policies and attempted to propose better policies. For instance, Lee et al. (2016)
analyzed the economic impact of each state’s incentive policies for improving the financial performance
of residential PV systems in the United States; the authors proposed more reasonable state-differentiated
incentive rates. Yamamoto (2017) attempted to find the optimal combination of FITs and capital
subsidies to promote the adoption of residential PV systems. Koumparou et al. (2017) suggested a
methodology for designing a new appropriate policy, such as a configuring model of residential PV net-
metering policies, whereas Blommestein et al. (2018) proposed a decision model for structuring
financial incentives to promote residential PV system adoption.
Although most of the studies analyzed and compared various aspects of PV policies, few studies
conducted a comprehensive economic analysis using empirical data between various residential PV
policies in Korea. To overcome this problem, it is necessary for various residential PV alternatives to
be discussed. The main objective of this study is to perform an economic feasibility analysis of
investments in residential PV systems that considers several alternatives of the subsidy plan using the
empirical data of Korea. To achieve this objective, we developed an economic evaluation model for
investments in residential PV systems based on the discounted cash flow method. By estimating the Page 4 of 31
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For Peer Review Onlycash flows of the investment, we evaluated the economic viability in terms of the net present value
(NPV) and the payback period with or without subsidies. In particular, we considered several widely
used subsidy plans as alternative policies for promoting the diffusion of residential PV systems in Korea.
We compared the economic effects of the subsidy plans on the NPV and payback period of residential
PV system investments using a sensitivity analysis with respect to the financial elements of the subsidy
plans.
The remainder of this paper is organized as follows: We first presents the section of model in which
the equations to evaluate the NPV by considering the costs and benefits of investments are described.
In the next section, we apply this model to a Korean household case and analyze the economic feasibility
of the residential PV system investment with the estimation of cash flows. In addition, we conduct a
sensitivity analysis to compare the effects of subsidy plans on the economic values of investment.
Finally, we concludes our study with some policy implications.
Model
The NPV provides the economic viability of an alternative under a certain discount rate using a
discounted cash flow method. To calculate the NPV of investments in a PV system, it is necessary to
identify the factors affecting the cash flow of the investment in some specific residential PV system.
The factors affecting cash flow are generally divided into installation/maintenance costs and the benefits
of the investment.
Let denote the present value of the total installation and maintenance costs of a residential PV 𝑇𝐶
system that is composed of a solar panel and inverter. In general, the lifespan of the PV system largely
depends on the lifetime of the solar panel because the existing PV system should be replaced with a
new one when the panel life ends and it can no longer function. Hence, if the lifespan of the solar panel
is , we set the study period to be the same at . Furthermore, we assume that the installation panTpanT
cost of the panel, denoted by , is invested only once at the beginning of study period. panCPage 5 of 31
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For Peer Review OnlyIn the case of the inverter, because its lifetime is generally shorter than the panel, periodic
replacements are required. If we let be the lifetime of the inverter, the installation cost of the invT
inverter, which is denoted by , will be paid both at the beginning of study period and additionally invC
times for every periods thereafter as replacement costs. Therefore, the present value of pan
invT
T 
 
 invT
the total cost for a residential PV system can be calculated as follows, where is the discount rate per r
period:
. (1)(1)
1(1)pan
inv
invT
T
inv
pan n T
nCTCCr 
 
 

 
After implementing the PV system, the household that invested in the system would be able to
save the expense of electricity consumption while operating the system. The economic benefit of the
investment in a residential PV system can be measured by estimating the amount of this expense savings.
Because there is no residential retail market for electricity in Korea, the government has an “electricity
offset” system to provide residential consumers with an incentive to use PV for electricity generation:
the charged bill for consuming grid-supplied electricity can be compensated by the excess electricity
generation, if any, produced by PV during the daytime. That is, the excess electricity production of the
previous period is carried over to the next period and subtracted from the electricity bill. Therefore, it
is necessary to consider this offset system in calculating the electricity expense savings of a household
with a PV system. Figure 1 illustrates a typical pattern of daily electricity consumption and generation
by a household with a PV system.
<Insert Figure 1 around here>Page 6 of 31
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For Peer Review OnlyTo calculate the electricity consumption expense savings, let be the function for calculating ()bx
the electricity bill, be the amount of monthly electricity consumption in the period, be nq nthnp
the amount of electricity produced by the PV system in the period, and be the amount of nth1nx
excess generation carried from the period . Then, a household with a PV system will receive an 1n
electricity bill of instead of , which must be paid if the household has not 1 ( )n n n bq p x   ()nbq
invested in a PV system. Therefore, the present value of benefits from monthly electricity bill savings
after the installation of the PV system can be calculated as follows:
. (2)1
11[()( )](1)panT
n n n n n
nB bq bq pxr
   
Finally, if there are any kind of subsidies, denoted by , in a certain period , that amount of nS n
money should be added to cash flows. Then, the NPV of a residential PV investment can be obtained
as follows:
. (3)( 1
11)
11[()( ) ](1) (1)pan
inv
in
vpa
nT
T
inv
pan n T
nT
n n n n n n
nCNPV bq bq p x S Cr r 
 
 


        
Analysis
Data
The period of this study was set to 240 months (20 years), from 2018 to 2038, based on the warranty
period of a PV panel. The discount rate was set to be 2% per year compounded monthly, which is Page 7 of 31
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For Peer Review Onlyslightly higher than the Bank of Korea Base Rate (1.75%)2. The electricity tariff system in Korea was
established to encourage energy savings by introducing a progressive rate plan. The progressive rate
plan for residential use has been composed of three phases since 2016, as shown in Table 1, including
a value-added tax of 10% and the Power Industry Infrastructure Fund fee of 3.7%.
<Insert Table 1 around here>
This study selected a stand-alone house located in a residential area of Seoul, Korea. The house has
a sufficient installation area of 80 for a PV system on its rooftop. The installation panel capacity for 2m
the target household was 3 kW, which can cover the electricity demands of most households in Korea
(Oh, 2013). We assumed that the installation cost of the PV system was 6.32 million KRW for 3 kW,
which is the same level as the upper limit price for PV system installation regulated by KEA in 2018 to
prevent excessive pricing between installation companies. A loan was not considered as a source of
installation costs. The salvage value at the end of the study period was assumed to be zero because the
PV system will be discarded after its expected lifespan. The major contributor to the maintenance cost
of a PV system is the solar inverter, which converts the variable DC output of the panel into a utility
frequency of AC. We assumed the solar inverter has a lifespan of 60 months (5 years) based on its
warranty period and replacement cost of 660,000 KRW.
Assuming that the price level will be fixed at the current level, monthly electricity consumption ()iq
and expected electricity generation were repeated at the levels shown in Table 2, which were ()ip
obtained from a simulation using Seoul Solarmap. The excess electricity generated by the solar panels
is carried forward to the next monthly bill and offset from the electricity consumption of the next month.
2 The reference policy rate is applied in transactions between the Bank of Korea and financial institutions, such as repurchase
agreements and the Bank's liquidity adjustment deposits and loans.Page 8 of 31
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For Peer Review Only<Insert Table 2 around here>
Table 3 summarizes the parameter values of our model for the case study.
<Insert Table 3 around here>
Economic Evaluation without Subsidies
Using the data related to the price, monthly consumption, and generation by the PV system given in
Tables 1 and 2, we can calculate the expected monthly electricity bills before and after PV installation.
In addition, if we consider the purchasing costs of a PV panel and inverter, the cash flows of a residential
PV investment over the lifespan of the inverter (60 months) can be obtained, as shown in Table 4. Then,
the cash flows for the whole study period are assumed to be the 4-time repetitions in Table 4 over 240
months.
<Insert Table 4 around here>
We calculated the NPV using Eq. (3) with for all n. Table 5 presents the result of the 0nS
discounted payback period calculation. The NPV result shows that the residential PV investment project
would be economically viable within the 20 years of the study period. However, a payback period of
12.7 years, which exceeds 10 years, could be perceived by residential customers as too long to be
attractive enough to invest in a PV system at present. This result indicates that any kind of subsidy as a
form of financial aid may be necessary to promote the successful diffusion of PV systems. Page 9 of 31
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For Peer Review Only<Insert Table 5 around here>
Economic Evaluation Considering the Effects of Subsidies
In this section, we examine how subsidies affect investments in residential PV systems in terms of
economic feasibility. To do so, three kinds of subsidy plans were considered: a lump-sum subsidy,
which is available in Korea now, and self-consumption and performance-based subsidies, which are not
offered yet but can be considered as alternative PV subsidy schemes by the Korean government.
Currently in Korea, the KEA provides a government-scale lump-sum subsidy to minimize the
financial burden of residential installation of PV systems. Table 6 illustrates the eligible amounts of the
lump-sum subsidy. A household with a monthly average electricity consumption of 360 kWh can be
subsidized as 3.51 million KRW in total. Therefore, we assume that a household will be subsidized in
the amount of 3.51 million KRW at the time of PV installation one time under the lump-sum subsidy
scheme.
<Insert Table 6 around here>
Although not yet available in Korea, the self-consumption incentive (SCI) is a subsidy scheme that
rewards a bonus payment on top of the retail electricity rate of the power consumed onsite. The self-
consumption rate of a PV system is defined as the ratio of a household’s consumed energy out of the
total energy generation by the PV system. The self-consumption rate is a means to reduce the burden
created by PV on the distribution grid. Not only does the user not purchase the electricity from the grid,
but the user can receive an extra tariff by self-consuming PV-generated energy. Germany has
incentivized self-consumption for solar PV, with the tariffs being applicable for installations
commissioned until 2013 (Hirvonen et al., 2015). Page 10 of 31
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For Peer Review OnlyA production-based incentive (PBI), also known as a performance-based incentive, is a widely
implemented subsidy scheme in the United States (Moosavian et al., 2013). Basically, a PBI provides
cash payments based on the number of kilowatt-hours generated by a renewable energy system,
including PV. Among the various incentive schemes for renewable energy, the PBI in particular is
regarded as an effective way to reward residential consumers because it is based on the actual energy
produced by a household.
We selected the SCI and PBI as subsidy scheme alternatives to the existing lump-sum inventive in
Korea. However, because these two alternative schemes have not been introduced in Korea, incentive
rates from Germany and the United States were used to set the actual rate levels for our Korean case
study. For the SCI incentive rate, considering the annual inflation rate, it is known that German
households with PV systems can receive up to 9.5 euro cents for each kilowatt-hour of solar energy
they consume instead of feeding it to the public grid. Based on this fact, by applying the recent currency
rate, we assumed that the SCI subsidy rate would be 133.28 KRW per kilowatt-hour for the consumption
of solar energy.
In the case of PBI, we used the United States as a reference to determine the actual incentive rate.
The PBI rates and their contract periods for each U.S. state that adopted a PBI scheme are shown in
Table 7.
<Insert Table 7 around here>
Because several U.S. states have adopted PBI, we used the average incentive value of the states as a
reference PBI rate for our Korean case. Consequently, by applying the recent currency rate, we set the
subsidy rate of PBI to be 124.63 KRW per kilowatt-hour for the production of solar energy. Table 8
summarizes the financial components for the three subsidy scheme alternatives.Page 11 of 31
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For Peer Review Only<Insert Table 8 around here>
To calculate the NPV with a subsidy, the subsidy term of Eq. (3), Sn, should be formulated according
to the rule by which the total amount of the subsidy can be obtained for each subsidy scheme. The
corresponding equations are as follows:
(i) Lump-sum scheme
3,510,000 0
0 nifnSotherwise 

(ii) SCI scheme
133.28 60
0 n
np ifnSotherwise  

(iii) PBI scheme
124.63 min(,) 120
0 n n
npq ifnSotherwise  

Using the above equations, the cash flows of the subsidy for each scheme can be obtained as shown
in Table 9. For SCI and PBI, the cash flows are repeated annually over the contract period.
<Insert Table 9 around here>
Using Eq. (3), we calculated the NPV of cash flows with subsidies according to the subsidy scheme
alternatives. Table 10 shows the results with a discounted payback period. Figure 2 compares the yearly
cumulative NPV among the three subsidy schemes over the study period of 20 years.Page 12 of 31
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For Peer Review Only<Insert Table 10 around here>
<Insert Figure 2 around here>
The results show that the NPV is higher under the PBI subsidy scheme than the lump-sum or SCI
scheme, whereas the payback period is shortest with a lump-sum subsidy. Therefore, if Korean
consumers are sensitive to liquidity when they consider investing in a PV system, the current subsidy
scheme would be more effective than the two new types of subsidy schemes. However, if consumers
are more interested in the overall economic value of their investment, the Korean government needs to
consider a PBI scheme to promote the diffusion of residential PV systems.
3.3. Sensitivity Analysis
In this section, a sensitivity analysis was performed to determine how the effects of a subsidy on
the economic values of residential PV investments would vary with respect to the changes in variables
related to the financial aspects of the subsidy schemes. This analysis was based on the following
parameters: the annual discount rate, SCI rate, PBI rate, and monthly electricity consumption. Figure 3
shows the results of the sensitivity analysis according to the variations of each variable.
<Insert Figure 3 around here>
Figure 3 (a) shows that decreases in the cumulative NPV as the discount rate increases are minimized
under the lump-sum subsidy scheme because the cash flow of the subsidy is generated only in the period
0. The cash flows of the subsidy under the other two subsidy schemes are present in the future periods Page 13 of 31
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For Peer Review Onlyuntil the contract is terminated. Therefore, a break-even discount rate exists by which the subsidy
scheme of the greatest NPV can be changed. Hence, Figure 3 (a) shows that the break-even discount
rate is 4%. If the discount rate is higher than 4%, then the current lump-sum subsidy guarantees the
maximum economic values of investments in residential PV systems.
In Figures 3 (b) and (c), we can obtain the break-even values of the SCI rate or PBI rate among the
subsidy scheme alternatives. For the SCI scheme, if the subsidy rate is increased to a level higher than
224 KRW per kilowatt-hour, then this subsidy scheme becomes the best from the consumer’s point of
view. However, for the PBI scheme, if the subsidy rate is set to a level lower than 113.4 KRW per
kilowatt-hour, then the PBI scheme is no longer the best one; rather, the current lump-sum subsidy
scheme gives the highest NPV when others remain unchanged.
Figure 3 (d) shows the cumulative NPV when electricity consumption is increased from the current
level to 100% (twice). We found that the cumulative NPV will increase as the amount of electricity
consumption increases because the expense of usage can be reduced by using more PV-generated
electricity. The slope of the NPV curve decreases gradually, likely because of the combined effect of
the graduated system of electricity rates in Korea and the discount rate. The NPV of the lump-sum
shows a step-wise curve, likely because the range of consumption that determines the amount of the
lump-sum subsidy changes at the step point (see Table 6). If we compare the SCI and PBI curves, we
find an interval where the SCI increases to some extent as consumption increases; however, both
increase similarly over a certain level of consumption.
Conclusions
This study aimed to conduct an economic feasibility analysis of investments in residential PV systems
by considering some prevailing PV-related subsidy policies in Korea and other advanced countries. To
achieve this goal, we developed a generic financial model to compute the NPV from the cash flows
generated by investments in PV systems; in addition, subsidy policy alternatives were compared from Page 14 of 31
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For Peer Review Onlythe perspective of the NPV and the payback period based on the model. The results provide an answer
to the question of whether installing a PV system in Korea is an attractive financial investment in the
residential sector.
As a result, a residential PV investment without a subsidy in Korea would be economically feasible
within the 20 years of the study period. However, the payback period exceeded 10 years, which may be
regarded by residential customers with limited financial capacity as too long to be attractive. When we
considered lump-sum, SCI, and PBI subsidy schemes in the economic evaluation of PV systems, the
results showed that the NPV was highest under a PBI subsidy scheme, whereas the payback period was
shortest under the lump-sum subsidy scheme that is currently used in Korea. Furthermore, a sensitivity
analysis showed the influence of the discount rate, SCI rate, PBI rate, and monthly electricity
consumption. The lump-sum subsidy was proven to be economically viable; however, it may not assure
government regulators that PV systems will be well managed after installation. Therefore, SCI and PBI
were introduced as alternative effective plans for the responsible management of PV systems. The
incentive rates that meet the economic level of the existing policy were analyzed and discussed.
The cost of PV facilities has decreased as the technology has developed over time, and the extent of
subsidies has been increased as people have become more concerned about the use of renewable energy.
At this point, it is necessary to consider a greater range of policies that address these changes and are
capable of covering a variety of residential electricity demands. This case study can serve as a reference
to policymakers who wish to set up future policy guidelines to promote the dissemination of residential
PV systems in Korea.Page 15 of 31
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For Peer Review OnlyReferences
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For Peer Review OnlyKoumparou, I., Christoforidis, G. C., Efthymiou, V., Papagiannis, G. K., Georghiou, G. E., 2017.
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For Peer Review OnlyArchitecture Institute of Korea, 17, 135-141.
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promotion of photovoltaic uses for residential houses in Korea. Energy Policy, 53, 248-256.
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photovoltaics under a feed-in tariff framework in Thailand. Energy Policy, 109, 260-269.
Watts, D., Valdés, M. F., Jara, D., Watson, A., 2015. Potential residential PV development in Chile:
The effect of Net Metering and Net Billing schemes for grid-connected PV systems. Renewable and
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residential photovoltaic systems. Energy Policy, 111, 312-320Page 18 of 31
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Figure 1. Daily electricity consumption and generation of a household with PV systemPage 19 of 31
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For Peer Review Only2 4 6 8 10 12 14 16 18 20
Year-8,000,000-6,000,000-4,000,000-2,000,00002,000,0004,000,0006,000,0008,000,000Cumulative NPV (KRW)
Lump sum
SCI
PBI
Figure 2. Cumulative NPV with subsidiesPage 20 of 31
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For Peer Review Only2 4 6 810 12 14 16 18 20
Annual discount rate (%)-2,000,00002,000,0004,000,0006,000,0008,000,00010,000,000Cumulative NPV (KRW)(a)
MARR = 4%
130140150160170180190200210220230240250
SCI rate (KRW/kWh)5,000,0005,500,0006,000,0006,500,0007,000,0007,500,000Cumulative NPV (KRW)(b)
205224
50 60 70 80 90 100 110 120
PBI rate (KRW/kWh)4,500,0005,000,0005,500,0006,000,0006,500,0007,000,000Cumulative NPV (KRW)(c)
74114
0 10 20 30 40 50 60 70 80 90100
Electricity consumption change (%)4,000,0006,000,0008,000,00010,000,00012,000,00014,000,00016,000,000Cumulative NPV (KRW)(d)
Lump sum SCI PBI
Figure 3. Results of the sensitivity analysis Page 21 of 31
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For Peer Review OnlyTable 1
The electricity tariff system
Basic charge Power usage charge (KRW/kWh)
For 200 kWh or less 910 For the first 200 kWh 93.3
For 201–400 kWh 1,600 For the next 200 kWh 187.9
For all over 400 kWh 7,300 For all over 400 kWh 280.6Page 22 of 31
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For Peer Review OnlyTable 2
Electricity consumption and expected electricity generation of a PV system
MonthElectricity consumption (q)
(kWh)Expected electricity generation (p)
(kWh)
January 388 325.9
February 442 312.5
March 453 392.3
April 401 370.3
May 319 384.4
June 299 376.5
July 312 261.3
August 342 264.9
September 350 343.7
October 322 346.8
November 335 196.9
December 356 194.4
Average ( ) 𝑞 360Page 23 of 31
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For Peer Review OnlyTable 3
Parameter values
Symbol Description Value
M Study period or lifespan of panel (months) 240
r Annual discount rate (%) 2
𝐶𝑝𝑎𝑛 Installation cost of panels (KRW) 6,320,000
𝑇𝑖𝑛𝑣 Lifespan of the inverter (months) 60
𝐶𝑖𝑛𝑣 Replacement cost of the inverter (KRW) 660,000Page 24 of 31
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For Peer Review OnlyTable 4
Cash flows without subsidies
Year MonthBill
without PVPV
Installation costReplacement
cost of inverterBill
with PVNet Cash
Flow
0 -6,320,000 -6,320,000
1 -63,190 -3,050 60,140
2 -85,630 -10,270 75,360
3 -89,150 -2,950 86,200
4 -72,560 -1,130 71,430
5 -48,450 -1,130 47,320
6 -44,170 -1,130 43,040
7 -46,950 -1,130 45,820
8 -53,360 -4,650 48,710
9 -55,080 -1,130 53,950
10 -49,090 -1,130 47,960
11 -51,860 -8,460 43,4001
12 -56,350 -13,660 42,690
13 -63,190 -3,050 60,140
14 -85,630 -10,270 75,360
15 -89,150 -2,950 86,200
16 -72,560 -1,130 71,430
17 -48,450 -1,130 47,320
18 -44,170 -1,130 43,040
19 -46,950 -1,130 45,820
20 -53,360 -4,650 48,710
21 -55,080 -1,130 53,950
22 -49,090 -1,130 47,960
23 -51,860 -8,460 43,4002
24 -56,350 -13,660 42,690
25 -63,190 -3,050 60,140
26 -85,630 -10,270 75,360
27 -89,150 -2,950 86,200
28 -72,560 -1,130 71,430
29 -48,450 -1,130 47,320
30 -44,170 -1,130 43,040
31 -46,950 -1,130 45,820
32 -53,360 -4,650 48,710
33 -55,080 -1,130 53,950
34 -49,090 -1,130 47,960
35 -51,860 -8,460 43,4003
36 -56,350 -13,660 42,690
37 -63,190 -3,050 60,140
38 -85,630 -10,270 75,360
39 -89,150 -2,950 86,200
40 -72,560 -1,130 71,430
41 -48,450 -1,130 47,320
42 -44,170 -1,130 43,040
43 -46,950 -1,130 45,820
44 -53,360 -4,650 48,710
45 -55,080 -1,130 53,950
46 -49,090 -1,130 47,960
47 -51,860 -8,460 43,4004
48 -56,350 -13,660 42,690
49 -63,190 -3,050 60,140
50 -85,630 -10,270 75,360
51 -89,150 -2,950 86,200
52 -72,560 -1,130 71,430
53 -48,450 -1,130 47,320
54 -44,170 -1,130 43,040
55 -46,950 -1,130 45,820
56 -53,360 -4,650 48,710
57 -55,080 -1,130 53,950
58 -49,090 -1,130 47,960
59 -51,860 -8,460 43,4005
60 -56,350 -660,000 -13,660 -617,310Page 25 of 31
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For Peer Review OnlyTable 5
The result of the case study without subsidies
Economic measure
NPV (KRW) 3,035,840
Payback period (years) 12.7Page 26 of 31
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For Peer Review OnlyTable 6
Lump-sum subsidy plan for a 3-kW PV system
Annual average consumption (kWh)
Min MaxSubsidy rate
(KRW/Watt)Total subsidy
(KRW)
450 1,170 3,510,000
450 500 1,050 3,150,000
500 550 700 2,100,000
550 600 580 1,740,000
600 650 470 1,410,000
650 350 1,050,000Page 27 of 31
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For Peer Review OnlyTable 7
PBI rates in the United States
State PBI Rate (USD/kWh) Contract Period (Years)
Californiaa0.025 5
Floridab0.050 5
Minnesotab0.080 10
New Mexicob0.080 12
Oregonb0.390 10
South Carolinab0.040 10
Average 0.111 8.9
a Go Solar California (https://www.gosolarcalifornia.ca.gov/documents/CSI_HANDBOOK.PDF).
b Solar Power Rocks ( https://www.solarpowerrocks.com)Page 28 of 31
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For Peer Review OnlyTable 8
Financial components of the subsidy schemes
Subsidy schemeAmount of subsidy
(KRW)Contract period (month)
Lump sum 3,510,000 –
SCI 133.28/kWh 60
PBI 124.63/kWh 120Page 29 of 31
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For Peer Review OnlyTable 9
Cash flows of the subsidies
Month Lump sum (Unit : KRW) SCI (Unit : KRW) PBI (Unit : KRW)
0 3,510,000 0 0
1 0 43,437 40,505
2 0 41,651 38,885
3 0 52,288 48,856
4 0 49,355 46,114
5 0 42,518 47,859
6 0 39,852 46,862
7 0 34,827 32,529
8 0 35,307 32,903
9 0 45,810 42,749
10 0 42,918 43,123
11 0 26,244 24,428
12 0 25,911 24,179Page 30 of 31
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For Peer Review OnlyTable 10
The results of the case study with subsidies
Economic measure Lump sum SCI PBI
NPV (KRW) 6,545,840 5,320,241 6,878,443
Payback period (years) 4.3 7.4 6.5Page 31 of 31
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