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2016 International Conference on Cogeneration, Small Power Plants and District Energy (ICUE 2016)
BITEC, Bang-Na, Thailand, 14-16 September 2016
Financial Incentive Mechanisms for
Residential PV systems: an Analysis Based on the
Real Performance Data
Femin V, Najmu H, Dayana K B, Petra I , Mathew S
Universiti Brunei Darussalam, UBD | IBM Centre
Jalan Tungku link, Gadong B E 1410, Brunei Darussalam.
Abstract— One of the major hurdles in popularizing the
residential solar projects is its high cost, which has to be borne
by individual house owners. Several policy frameworks and
incentive mechanisms like Feed in Tariff (FiT) and Net Metering
(NM) are being implemented globally to make these projects
attractive to the consumers. In this study, we identify the viable
FiT and NM for making residential solar PV projects
economically attractive in Brunei Darussalam. The analysis is
based on the actual performance data collected from a 6kWp
Multi-crystalline residential solar PV system. By considering the
break-even point of Net Present Value (NPV) of the project, the
minimum FiT for the residential PV projects is estimated as $
0.22 /kWh. Due to the very low electricity tariff in Brunei, the
NM rate is highly sensitive to the installed PV size and electricity
consumption pattern. Under this condition, the viable NM rate is
identified as $ 0.74/kWh. Sensitivities of Fit and NM rates on
other economic metrics are also presented in the paper.
Index Terms-- Feed in Tariff, Net Metering, Net Present
Value, Pay Back Period, Internal Rate of Return, Residential
solar PV systems.
I. INTRODUCTION
Global energy scenario is changing from conventional
generation options to more sustainable and secure resources
and technologies. As a result, the share of renewable energy
has significantly increased in past decades. For example,
renewable based energy generation has observed an increase
of 4.3 % during the period from 2010 to 2015 [1], [2]. Future
projections show promising trends, indicating that renewable
energy would be a major player in the future global energy
markets. Deliberations and summits are being organized all
over the world to enhance the penetration of renewable
energy in the power mix. The recent example is the Paris
summit in 2016, where leaders from all the nations joined
together to declare their renewable energy “Ambitions”.
Brunei Darussalam, which lies in the north coast of
Borneo island in Southeast Asia, has committed to increase
the share of renewable energy in its energy mix by 10% by
2035 during the Paris summit [3], [4]. Being a country in the
tropical region, solar energy is the most viable renewable
resource for Brunei Darussalam to meet this noble target. The
average solar intensity in Brunei comes around 5.43
kWh/m2/day [3], [5]. However, to meet the 10% target, 954
GWh of solar electricity would have to be generated by 2035
[6]. Taking an average efficiency of 15 % for the commercial
solar panels, this needs and installed solar capacity of 726
MW. This in turn would require 484 hectors of solar farms
installed across the country. One way to find at least a part of
this large area is to popularize the residential solar PV
systems, utilizing the rooftops or nearby free area of the
existing houses.
One of the major hurdles in popularizing the residential
solar PV system is its high initial investments and relatively
higher cost of generation. For example, currently, the
generation cost of solar PV based electricity in Brunei is
between $ 0.20 to 0.30/kWh [7]. As the prevailing electricity
tariff in the country is the lowest in the region, expecting the
house owners to completely meet this higher cost of
generation is not reasonable. Hence, economic incentives are
to be given to encourage the consumers to opt for sustainable
and clean technologies like solar.
The most common incentive mechanisms, globally
implemented to promote renewable energy, are the Net
Metering ( NM) and Feed in Tariff (FiT). In Feed in Tariff,
all the electricity generated by the system would be purchased
by the utility and injected to the grid, while the local
consumption will be charged at the normal price. On the other
hand, under the Net Metering, the PV generated electricity
2016 International Conference on Cogeneration, Small Power Plants and District Energy (ICUE 2016)
BITEC, Bang-Na, Thailand, 14-16 September 2016
Figure 1. The 6kWp installed PV system.
will first be consumed by the house owners to meet the local
demand, and the surplus electricity, if any, would be
purchased and exported back to the grid at an agreed rate [8],
[9]. Both these mechanisms have their relative merits and
demerits, and hence, adopting either of these methods for a
particular region require careful analysis and studies [10]–[12].
Though theoretical models can give some indications on
the viability of such mechanisms, it is always advisable to
demonstrate the concept through pilot projects, so that the
incentives for NM and FiT can be calculated based on real
field observations. In this paper, we presents such a study, in
which the viability of these incentive mechanisms are
analyzed and compared so that policy guidelines can be
formulated for further implementation of solar PV based
residential projects in Brunei Darussalam.
II. EXPERIMENTAL RESIDENTIAL PV SYSTEM
The experimental residential PV system is shown in Fig.1.
It consist of 6 kWp Multi-crystalline silicon PV panels, with
24 PV modules, covering a total area of 39 m2. The module
efficiency under standard test condition is 15.21%. The solar
electricity generated at the panels, after getting inverted to
AC, goes to the monitoring system, where the inflow and out
flow of electricity to the grid as well as the local consumption
at the house were measured. The measurements were made at
a resolution of 2 seconds and the data are transmitted to a
central server for further processing, analysis and
visualization. From these measurements, the energy flow
under FiT and NM could be calculated.
III. PERFORMANCE OF THE PV SYSTEM
The performance of the solar PV system for the month of
March, 2016 has been used for this study. The total domestic
load during this period was also recorded to compare the
generation with the consumption.
0
1
2
3
4
5
6
0246810121416182022
Energy (kWh)
Time (h)
Generation
Consumption
Figure 2. Hourly variation in the consumption and generation of a single
day.
0
20
40
60
80
100
120
1 3 5 7 9 111315171924262830
Energy (kWh)
Day (d)
Generation
Load
Figure 3. Daily variation over the month.
Hourly variations in the consumption and generation, for
a typical day, is shown in Fig.2 As expected, the solar PV
generation peaks at noon hours and reaches its maximum of
4.75 kWh. Energy generated in excess to the consumption is
indicated in the shaded area. Similar trends were observed in
other days as well.
Daily variations in the electricity generated by the solar
PV system over the month, and the corresponding variations
in the local consumption are shown in Fig. 3. The production
from the panels varies day by day, depending upon the
strength of available solar insolation. Similarly, the load
pattern also changes depending on the daily environmental
conditions and occupancy level. Based on this performance
data, the capacity factor of the panels, over the month, is
around 15.53%, which agrees closely with the theoretical
estimates [7].
IV. ECONOMIC INDICES AND ASSUMPTIONS
The economic merits of the residential solar project under
this study has been assessed based on four indices which are
Net Present Value (NPV), Benefit Cost Ratio (BCR), Pay
2016 International Conference on Cogeneration, Small Power Plants and District Energy (ICUE 2016)
BITEC, Bang-Na, Thailand, 14-16 September 2016
Back Period (PBP), and Internal Rate of Return (IRR). NPV,
which is the difference between the net present value of
benefits and costs, discounted to the initial year of the project,
is given by
11 11
1
11
nn
AI
nn
II
NPV B C m
II II
½
ªº
ªº § ·
°°
«»
¨¸
«»
®¾
¨¸
«»
«»
°°
¬¼ © ¹
¬¼
¯¿
(1)
where BAis yearly benefit, CIcapital cost, mis the
maintenance cost, Iis the discounting rate and nis the
lifespan of the project. Similarly, BCR is the ratio between
net present value of all the benefits and net present value of
all the cost accumulated over the lifetime of the project.
Hence BCR is given by
11 11
1
11
nn
AI
nn
II
BCR B C m
II II
ªº
ªº § ·
«»
¨¸
«» ¨¸
«»
«»
¬¼ © ¹
¬¼
(2)
The PBP, which is the minimum number of years at
which the project investment is paid back, is expressed as
ln 1
ln 1
I
AI
IC
BmC
PBP I
§·
¨¸
©¹
(3)
The IRR, which is the real rate of interest at which net
present value of cost equals with the net present value of
benefits, is computed by the expression
1-1 1-1
1
11
nn
AI
nn
IRR IRR
BCm
IRR IRR IRR IRR
ªº
ªº§ ·
«»
¨¸
«»
¨¸
«»
«»
¬¼© ¹
¬¼
(4)
Cost of the panel was assumed as $ 3000/kWp, and the
real rate of interest, adjusted for inflation and escalation was
taken 4.68%. The maintenance cost of this project was
assumed as 0.01% of the initial investment and the life span
of this project (n) is taken as 20 years.
V. FEED IN TARIFF AND NET METERING
Based on the assumptions mentioned above, economics of
the residential PV project was analyzed. To identify the rate
for the solar based electricity under the FiT, the electricity
price at which the NPV of the projects becomes zero has been
identified. As this is the point at which the project is neither
at loss nor at profit, it indicates the lowest price at which the
electricity has to be purchased from the house owners under
the FiT, to make the residential PV projects economically
viable. Based on these calculations, a minimum breakeven
FiT of $ 0.22/kWh suggested for the residential PV projects
under Bruneian conditions.
Incentive mechanism required for NM is highly sensitive
to the amount of electricity injected back to the grid. This in
turn is a function of the total production from the panels and
the local electricity consumption rate at the household.
-20000
-10000
0
10000
20000
30000
40000
50000
60000
70000
80000
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Net present value ($)
Electricity selling price ($/kWh)
Figure 4. The changes in NPV over different electricity selling price
per kWh for FiT.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0 0.2 0.4 0.6 0.8 1
Benefit cost ratio
Electricity selling price ($/kWh)
Figure 5. The changes in BCR value over different electricity selling
price per kWh for FiT.
0
5
10
15
20
25
0 0.2 0.4 0.6 0.8 1
Pay back period (yr)
Electricity selling price ($/kWh)
Figure 6. The changes in PBP value over different electricity selling
price per kWh for FiT.
2016 International Conference on Cogeneration, Small Power Plants and District Energy (ICUE 2016)
BITEC, Bang-Na, Thailand, 14-16 September 2016
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0 0.2 0.4 0.6 0.8 1
Internal rate of return (%)
Electricity selling price ($/kWh)
Figure 7. The changes in IRR value over different electricity selling price
per kWh for FiT.
-35000
-30000
-25000
-20000
-15000
-10000
-5000
0
5000
10000
15000
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Net present value ($)
Electricity selling price ($/kWh)
Figure 8. The changes in NPV value over different electricity selling
price per kWh for NM.
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 0.2 0.4 0.6 0.8 1
Benefit cost ratio
Electricity selling price ($/kWh)
Figure 9. The changes in BCR value over different electricity selling
price per kWh for NM.
0
10
20
30
40
50
60
0.4 0.5 0.6 0.7 0.8 0.9 1
Pay back period (yr)
Electricity selling price ($/kWh)
Figure 10. The changes in PBP value over different electricity selling price
per kWh for NM.
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Internal rate of return (%)
Electricity selling price ($/kWh)
Figure 11. The changes in IRR value over different electricity selling price
per kWh for NM.
Hence, the panel size and the household consumption level
are to be predetermined in the calculation of Net Metering. In
order to include these parameters, the average consumption
rate and roof top size of Bruneian houses were calculated
from the available data. Thus, an average PV system capacity
of 12 kWp and the average annual consumption of 11400
kWh were considered for NM analysis. Based on these
assumptions, a minimum price of $ 0.74/kWh should be paid
to the house owners to make PV generation attractive under
the NM.
VI. ECONOMIC SENSITIVITES OF THE RESIDENTIAL PV
PROJECTS ON THE INCENTIVE MECHANISMS
The economic merits of the residential based PV projects
are highly sensitive to the prevailing incentive mechanisms.
These sensitivities were analyzed by varying the rates for FiT
and NM and estimating its effect on various economic indices
discussed above. The results are presented in Fig. 4 to Fig.
11. From the Figures, we can see that the project economics
significantly changes when FiT and NM rates are varied. For
2016 International Conference on Cogeneration, Small Power Plants and District Energy (ICUE 2016)
BITEC, Bang-Na, Thailand, 14-16 September 2016
example, when the FiT is increases from $ 0.3/kWh to $
0.5/kWh, the NPV increases by 71.10 % . This corresponds to
an increase of 40 % in the BCR and reduction of 6 years in
the PBP. Under this scenario, the IRR of the project would
also reach to an impressive percent of 18.4%. Similar changes
are also seen with the variations in the NM rates.
VII. CONCLUSIONS
With its commitment to meet 10% of the National
electricity demand through renewable energy, residential PV
programme is expected to be implemented in a large scale in
Brunei Darussalam. In this paper, we identify the economic
incentives required to make such programmes attractive to the
house owners in Brunei. The most common incentive
mechanisms viz. FiT and NM are considered for the analysis.
Real performance data from a six kW peak residential PV
system, installed at a house in Brunei is used for the study.
Under the FiT, a minimum breakeven rate of $ 0.22 per kWh
has to be paid to the system owners to make such projects
viable under the Bruneian environment. The NM tariff is
highly sensitive to the capacity of the solar panel and
electricity locally consumed by the houses. Considering the
average household electricity consumption rate and possible
PV system size, a minimum of $0.74 per kWh has to be paid
to the owners under the NM framework. The sensitivities of
FiT and NM on different economic metrics like NPV,BCR,
PBP and IRR are also presented in the paper.
VIII. ACKNOWLEDGMENTS
The authors are thankful to the University of Brunei
Darussalam and the Brunei Research Council, for extending
necessary supports during the course of this study.
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