Photovoltaic (PV) and Diesel Generator (DG) hybrid power plant system could be one of the solutions to increase the renewable energy share and to reduce the fuel consumption in isolated Island. Especially in Indonesia, where most of the island supplied by DG. The goal of this study is to have the optimized solution of the PV Diesel system without a battery in Nusa Penida Island. It is assumed that new PV without a battery will be installed to work with six existing DG with a capacity of 1600 kW each to cover an average of 112 MWh/day load. By having the irradiance data, load data, diesel, and PV specification, the optimization can be done in HOMER Pro software. The sensitivity analysis is focused on the minimum load ratio where in this study it ranges from 25% to 80%. The result shows that the optimized PV size for the system is 6150 kW and it could cover 21% of the load, while the DG covers 79% of the total load. The sensitivity analysis indicates that different minimum load ratio affects the overall system performance. In the simple case shown, the different number of DG minimum load ratios can reduce fuel consumption by 5%.

1. Photovoltaic and Diesel Power Plant Optimization
for Isolated Island
Dianing Novita Nurmala Putri
Electrical Engineering Department
Universitas Trisakti
Jakarta, Indonesia
dianingnovita@trisakti.ac.id
Eddie Widiono Suwondo
Chairman
Prakarsa Jaringan Cerdas Indonesia
Jakarta, Indonesia
etwasuka001@gmail.com
Andrie Syatriawan
Electrical Inspector
ESDM
Jakarta, Indonesia
andrie.syatria@gmail.com
Syamsir Abduh
Electrical Engineering Department
Universitas Trisakti
Jakarta, Indonesia
syamsir.abduh@trisakti.ac.id
Ishak Kasim
Electrical Engineering Department
Universitas Trisakti
Jakarta, Indonesia
ishak@trisakti.ac.id
Nazmia Kurniawati
Electrical Engineering Department
Universitas Trisakti
Jakarta, Indonesia
nazmia.kurniawati@trisakti.ac.id
Abstract—Photovoltaic (PV) and Diesel Generator (DG) hybrid
power plant system could be one of the solutions to increase
the renewable energy share and to reduce the fuel consumption
in isolated Island. Especially in Indonesia, where most of the
island supplied by DG. The goal of this study is to have the
optimized solution of the PV Diesel system without a battery in
Nusa Penida Island. It is assumed that new PV without a battery
will be installed to work with six existing DG with a capacity
of 1600 kW each to cover an average of 112 MWh/day load. By
having the irradiance data, load data, diesel, and PV specification,
the optimization can be done in HOMER Pro software. The
sensitivity analysis is focused on the minimum load ratio where
in this study it ranges from 25% to 80%. The result shows that
the optimized PV size for the system is 6150 kW and it could
cover 21% of the load, while the DG covers 79% of the total
load. The sensitivity analysis indicates that different minimum
load ratio affects the overall system performance. In the simple
case shown, the different number of DG minimum load ratios
can reduce fuel consumption by 5%.
Index Terms—Photovoltaic, Diesel, Hybrid Power Plant
I. INTRODUCTION
Indonesia has a target to increase the share of renewable
energy by 23% in 2025 [1]. Having more than sixteen thousand
islands, the majority of the island is an isolated island supplied
by the Diesel Generator (DG). Nowadays, the hybrid power
plant is believed to be more reliable compared to the single
power source from solar or wind energy with high intermit-
tency. Furthermore, the high solar potential and decreasing
cost of Photovoltaic (PV) made it one of the alternatives to
reach the goal by increasing the share of renewable energy
and reduce diesel fuel consumption. For example, one of the
PT.PLN program is to install PV in one thousand islands. This
is expected to gradually increase the number of PV installed.
The common combination of hybrid PV is with a battery
system. However, the high investment cost could increase the
basic cost of electricity supply. Therefore, more study on PV
DG system without battery for the isolated island in Indonesia
is needed. Several studies have been done in some, like [2]
discussed the bus configuration for a different type of hybrid
and stated that the best configuration for small scale hybrid
power system is ac/dc bus, [3] explained the PID controller
to overcome the PV fluctuation, and [4] reveals the optimize
design of PV DG system without battery. However, none of
them are focused on diesel fuel consumption and minimum
load ratio for DG. Furthermore, PT.PLN state that Sumba
Island and Nusa Penida Island will be a target to implement the
smart grid pilot project in Indonesia where one of the goals is
to reduce the electricity production cost. Thus, it is necessary
to have more studies on both islands.
This paper is focused on PV DG optimization, simulation,
and sensitivity analysis. The aim is to design the optimal
solution for the PV DG hybrid system and examine the effect
when a different combination of the minimum load ratio of
DG for the system is applied.
II. HYBRID POWER PLANT
The hybrid power plant is a combination of more than one
energy resource. To deal with the intermittency of renewable
energy sources, it becomes one of the best options because it
is more reliable compared to one source of energy. Especially
a system with high intermittencies from PV or wind energy.
However, the combination of the system makes it more com-
plex [5]. So, having a good design and controlling system is
needed to have a reliable system. Besides, several operation
standards should be followed [6].
A. Simulation, Optimization and Sensitivity Analysis
In this study, three steps are done, the simulation, optimiza-
tion, and sensitivity analysis. By doing the optimization, it
can achieve the best configuration to meet the load, while
the sensitivity analysis is done to see the effect of changing
parameters for the whole system. The process can be illus-
trated in Fig. 1. To get the best solution, HOMER assesses
all of the combinations concerning the constraint, and also
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2. uses a derivative-free algorithm. The simulation is done for
one year. The optimization completed to meet the load and
the sensitivity analysis is accomplished to see the effect of
different minimum load ratio of the diesel to overall systems
Fig. 1. Process Using HOMER Pro Software
B. Photovoltaic
To design a PV system, accurate solar irradiation and load
data are needed. In HOMER Pro software, the PV output is
calculated by using the following equation.
PP V = YP V fP V
ḠT
ḠT,ST C
[1 + αP (TC − TC,ST C)] (1)
Where YPV is the power output in STC condition(kW), f is a
derating factor (%), ḠT is the solar incident in the time step
kW/m2
, α is the temperature coefficient (% / ◦
C), TC is the
PV cell temperature in time step (◦
C) and TC,ST C is the PV
temperature under STC [7].
C. Diesel Generator
Diesel generator has been a reliable resource for an isolated
island in Indonesia. However, the increasing price of fuel
and the delivery cost to the isolated island always become
a problem. By combining renewable energy like solar, is
expected to decrease the amount of total fuel consumption,
increasing the renewable energy share and reducing the CO2
emission caused by the DG [8].
To calculate the diesel consumption duel, the following
equation is used:
F = F0Ygen + F1Pgen (2)
Where F0 is fuel consumption rate (L/hr), Ygen is generator
rating, Pgen is generator output in time step, and F1 is fuel
curve slope (L/hour/kW output).
III. NUSA PENIDA ISLAND
Nusa Penida Island is one of the famous tourist areas located
at 11◦
31.0’S, 128◦
40.3’E. For this study case, it is assumed
that new PV will be installed in the system, and it will be
combined with six existing 1600 kW of diesel on the island.
The PV sizing is to be optimized by HOMER and the DG
minimum load is limited by 25%. The solar data is taken
from the NASA database which automatically generates from
HOMER Pro Software.
A. Solar Irradiation
Having a high solar potential, Nusa Penida Island has a
good global solar irradiation which can be seen in Fig.2. The
monthly average is range from 4790 kWh/m2
/day and reaches
the highest number of 6190 kWh/m2
/day in October. Although
June and July have the lowest number of irradiance, the
number is still above 4000 kWh/m2
/day. As for the clearness
Index, the highest occurring in May with 0.58 while the lowest
happened in January with 0.45.
Fig. 2. Solar Irradiance in Nusa Penida Island
B. Load
Having an average of 112 MWh/day, the highest consump-
tion occurs in August with a value of 3605 MWh while the
lowest happened in February with 3060 MWh.
Fig. 3. Monthly Average Load in One Year Simulation Time
Load characteristics always depend on electricity user be-
havior, figure 4 (a) and (b) show a different pattern of the load
in different days. Figure 4 (a) shows that in August, the peak
of the load occurred between 20.00 hrs and 22.00 hrs, while
in May, as shown in figure 4(b), it happened between 15.00
hrs to 18.00 hrs.
(a)
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3. (b)
Fig. 4. Load in different Date of the year (a) 8 August (b) 21 May
The daily load profile is described in Fig.5 and it is varying
between 80.3 MWh/day to 153.78 MWh/day
Fig. 5. Daily Load Profile
C. Diesel Fuel Consumption Curve
To know the consumption of the diesel generator, one of
the most important parameters to be known is the diesel
fuel consumption curve. For this simulation, the diesel fuel
consumption curve as shown in the following figure. It shows
that maximum fuel consumption when the output is maximum
reach 400 L/kW while the minimum consumption is 100
L/kW.
Fig. 6. Diesel Fuel Consumption Curve [9]
IV. RESULT AND DISCUSSION
By doing the simulation, optimization, and sensitivity anal-
ysis, is expected to have the best system configuration that can
meet the load. The optimization is done by deciding the size
of the PV, considering the available resource which is, in this
case, the solar energy and diesel generator.
A. System Architecture
Since there are six identical types of diesel with 1600 kW
power, the first task is to determine the size of the PV Panel.
And the result shows that the best size for PV to support
the system is 6150 kW. The following table describes the
architecture of the systems.
TABLE I
DIESEL GENERATOR PRODUCTION AND CONSUMPTION
No Component Size Unit
1 photovoltaic 6150 kW
2 DG1 1600 kW
3 DG2 1600 kW
4 DG3 1600 kW
5 DG4 1600 kW
6 DG5 1600 kW
7 DG6 1600 kW
B. Electricity Production and Consumption
By doing optimization and applied the dispatch systems,
the system can meet the load in the best combination. Due
to the DG has the same size and specification, there is no
specific sequence or rules applied. The optimization is done
considering the load and the availability of the resources.
The PV would be a priority because it has no cost for the
generation. Thus, the rest of the load is covered by DG. The
optimized solution shows that it is better to maximize the
power output on the diesel in sequence. For example, when
the first DG has to work, it will work in optimum power and if
it is not enough then the second DG will work and so on. The
DG will work depending on the PV power output. Simply, if
the PV is enough to cover the load, then the diesel will not
operate. Fig. 7 shows the Monthly average of DG and PV
output. It shows the varying number of PV and DG outputfor
one year. The PV production is varying start from 715 MWh
in January to 927 MWh in October, while the diesel has the
highest share in August and the lowest in February.
Fig. 7. Monthly Average Electricity Production and Consumption
The Monthly Average of Load, Diesel, and PV output can
be seen in Fig. 8 where the majority of the load is covered by
the DG. Overall, the PV covers about 21% of the load while
DG covers 79% of the load. Due to the system works without
a battery, when the PV reaches its peak and the load is low, the
energy will not be able to store. So, in some time step, there
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4. is a condition where PV produces up to three times the load.
The diesel power output monthly ranges from 2465 MWh to
2830 MWh to cover the total of 41070 MWh yearly load.
Fig. 8. Monthly Average of Load, Diesel and PV Output
C. Diesel Generator Output and Fuel Consumption
As explained before, the system makes DG operate at
their maximum power output before trigger the other DG.
Fig. 9 illustrates the power output of all DG and also fuel
consumption. It can be seen that each DG has a different
power and fuel consumption also different. Furthermore, DG1
has the highest number of fuel consumption and power output
while DG6 is the lowest. The number of power output and fuel
consumption is gradually decreasing from DG1 to DG6. This
occurs because the system works by maximizing the power
output of each diesel start from DG1 and end with DG6. So
the diesel work in sequence to cover the load. Once DG1
cannot meet the load, it will trigger DG2, and if DG2 is not
enough it will push DG3 to operate. The same rules applied
for DG4,5 and 6.
Fig. 9. Diesel Generator Output and Fuel Consumption
Besides the power output and the fuel consumption, the
other important parameters from the diesel generator are the
amount of each diesel starts in one year. The following table
shows the yearly working hours, fuel consumption, the number
of stars, and the production of all six types of diesel. It shows
that DG1 has the largest amount of production with 12.03
GWh and fuel consumption with 2980070 Liter/Year in one
year. However, DG4 produces only 2.79 GWh (23% of DG1)
even though it consumes 2798675 L/Year This occurs because
DG4 has 1625 number of stars, while DG1 only have one
number of starts.
TABLE II
DIESEL OUTPUT PARAMETERS
DG Hrs/year
Fuel
(L/year)
Starts
Production
(GWh/year)
DG1 8760 2980070 1 12.03
DG2 8738 2561954 23 10.19
DG3 7927 1713501 670 6.56
DG4 4309 2798675 1625 2.79
DG5 1315 206349 763 0.74
DG6 272 40296 205 0.14
The monthly range of fuel consumption is illustrated in Fig.
10, where on the highest month of consumption that occurs
in August, the fuel consumption ranges from 14787 liters to
30693 liters, while in February where the fuel consumption is
the lowest, the number is between 16999 to 26881 liters.
Fig. 10. Monthly Range of Diesel Fuel Consumption
Fig. 11. Daily Diesel Fuel Consumption
D. Sensitivity Analysis
Sensitivity analysis can be done by inserting various num-
bers for one parameter in each simulation. For this study,
different numbers of diesel minimum load ratios which start
from 30% to 80% for all six DG are imported to the software.
However, due to the very long hours of simulation, there are
three separate simulations with a different combination of load
minimum ratio of DG. The first combination is 30% and 40%
minimum load ratio in imported in each diesel, the second
one is 50% and 60%, and the last one is 70% and 80%. The
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5. result of a different combination can be seen in Fig. 12. While
Fig. 11 shows the total daily fuel consumption in a year for
all DG. It is varying start from 14787 liters on 7 January to
33894 liters on 30 December.
Fig. 12. Sensitivity Analysis for Diesel Minimum Load Ratio
The following table describes two different combinations,
sensitivity case #1 and #2 where there is a different number
on DG minimum load for DG3 and DG6. It can be seen
by changing the minimum load ration, it affects the whole
generation system. The Consumption and Diesel hours become
different for each DG. Besides, it could also reduce fuel
consumption.
TABLE III
DIESEL OUTPUT PARAMETERS
DG
#1 #2 #1 #2 #1 #2
DG
Minimum
Load (%)
FuelConsumption
(Liter/Year)
Diesel
Hours/Year
DG1 30 30 2790323 2950367 8406 8760
DG2 30 30 2363435 2492529 8199 8553
DG3 40 30 1477956 1642974 5818 7174
DG4 30 30 1183527 774740.9 5696 4309
DG5 30 30 464477.7 124834.5 2911 668
DG6 30 40 46785.4 341059 291 1857
Total 7815241 7426929 31321 31321
V. CONCLUSION
By doing the optimization using HOMER Pro Software, the
optimized architecture is achieved. The best PV size for the
system is 6150 kW. And to cover 112 MWh/day load, it is
suggested to use 6150 kW PV where it can cover 21% of the
load. The sensitivity analysis indicates that a different amount
of load ratio combination resulted in a different amount of fuel
consumption where in this case it reduced by 5%. The future
work of this study is to be more focused on the search for
the best method in optimizing the other parameter to decrease
fuel consumption.
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