Financial Analysis of Additional Supply
to Obtain Optimal Basic Costs of Provision in The Weda System
Maman Sulaeman
Electricity and Renewable Energy, PLN Institute of Technology,
Indonesia
Email: [email protected]
|
Keywords |
|
ABSTRACT |
|
Cost
of Goods (BPP), SWOT and TOWS Analysis, Financial Feasibility Study. |
|
The electricity growth in the
PLN Weda Customer Service Unit (ULP) area in
Central Halmahera Regency reached 26.64% in 2022, driven by national-scale
nickel mining, resulting in consistent yearly increases in electricity
demand. ULP Weda's electricity supply, with an
installed power of 5.2 MW and a peak load of 5.6 MW, faces challenges due to
high fuel prices, leading to a Cost of Supply (BPP) value of IDR 4,193,
significantly higher than the average selling price of IDR 1,365 in the Veda
system. To address these issues, a research methodology, incorporating SWOT
and TOWS analyses, was employed. Three potential scenarios emerged:
relocating Diesel Generating System (SPD) engines, adding rental generator
engines, and purchasing excess power. Financial Feasibility Study (KKF)
calculations, considering Nett's Present Value (NPV), Nett's Present Cost
(NPC), and Internal Rate of Return (IRR), determined the excess power
purchase scenario as the most viable, with an NPV of IDR 29.8 billion, NPC of
IDR 623 billion, IRR of 33.49%, and the lowest BPP value at IDR 1,244. The
Homer application provided insights into optimizing generating machine units
for optimal BPP values. Sensitivity analysis showed that higher interest
rates and lower fuel prices contribute to lower BPP values. This
comprehensive research offers a strategic framework for addressing
electricity supply challenges in the ULP Weda area,
ensuring financial viability and optimal operation. |
|
|
|
INTRODUCTION
The need for electrical power will continue to grow every
year. Population growth and economic growth are believed to be the two main
factors influencing the increasing consumption of electrical energy in a region
In line with the government's policy to
develop more renewable energy, the development of renewable energy projects
such as biomass is encouraged but still considers and considers economic value
(price efficiency)
In these expected conditions there are
some facts that not all electrical systems can be carried out, this is
illustrated in one Vedic system located on Halmahera Island which is the
largest island in North Maluku Province
The Weda system is supplied by PLTD
Weda with an installed power of 5.2 MW, capable power of 4.2 MW with nine (9)
units of machines. In addition, it is also supplied by private rental machines
with an installed power of 3.3 MW, capable power of 1.9 MW with three (3)
engine units. So that the total Capable Power is 6.1 MW, while the peak load is
5.6 MW. With this condition the Vedic system is on standby.
In addition, a very high load growth of
26.64% in 2022 shows a very large demand for electricity in Vedic ULP. With a
national-scale Nickel mining area in the Central Halmahera area that is still
developing, the number of workers absorbed is very large, both from the
surrounding community and from outside communities. A big challenge for PLN
units because in fulfilling the supply of power plants is still constrained by
standby status
The plants available in the Vedic
system come from oil-fired Diesel Power Plants (PLTD)
To note, there is one company that has
its own electricity supply business license (IUPTLS) using coal-fired steam
power plants (PLTU), namely PT Weda Bay Energi which supplies to PT Indonesia
Weda Bay Industrial Park (IWIP) with a capacity of up to 2,500 MW.
With the condition of the system in
standby condition that makes customer growth a bit braked, it is necessary to
increase supply so that the Veda system is in normal condition and ready to
increase electricity sales. However, in this case, BPP Pembangkit is still
considered to remain in PLN's financial control. Therefore, every time there is
an increase in plant supply, it is necessary to take care of the Financial
Feasibility Study (KKF) so that optimal BPP is obtained.
METHODS
The research methodology employed in
this study involves a series of steps outlined in the research process flow.
Initially, the research begins with the preparation phase, which includes field
studies and literature reviews to understand the background and conditions of
the object of discussion at a specific location. Data from these studies are
utilized to formulate research problems and support subsequent data collection.
After the data is gathered, the
research continues with an analytical method using SWOT and TOWS analysis
tools. This process aims to strengthen the formulation of problems and produce
a model design. The model design originates from scenarios selected based on
the analysis results, which are then evaluated through calculations and
simulations using the Homer application to assess financial feasibility.
The research design adopts a
descriptive approach with a quantitative method. Descriptive research provides
a comprehensive overview of the social issues being discussed, while the
quantitative approach is used to collect and analyze data using numerical
values. Thus, variables such as income, business duration, capital, business
type, and education will be processed quantitatively.
Data collection methods involve Focus
Group Discussion (FGD) and observation. FGD is used to discuss survey subjects
with carefully selected groups, while observation is conducted by directly
observing relevant phenomena. Before data collection, the research has a
framework to determine the initial conditions and research objectives.
The research stages involve four main
steps: empathy, definition, ideation, and prototyping. The empathy stage is
conducted through interviews and in-depth information exploration to better
understand the problem. The definition stage produces problem statements from
SWOT analysis findings. Next, the ideation stage generates ideas to solve
external problems and develop activity scenarios. The prototyping stage
involves developing scenarios, which are then tested through financial
feasibility studies.
Research analysis methods include SWOT
Analysis and TOWS Analysis. SWOT Analysis is used to evaluate the strengths,
weaknesses, opportunities, and threats affecting the research. TOWS Analysis is
used to identify strategies based on the relationship between internal and
external factors. The results of the TOWS analysis are used to formulate
project scenarios. Thus, this research combines descriptive, quantitative, and
strategic analysis approaches to investigate and present conditions as well as
solutions to the identified problems.
RESULTS
Financial Feasibility Study Scenario
Calculation
In
calculating the financial feasibility of adding the Vedic system in order to
obtain an optimal BPP based on elements of Nett Present Value (NPV). Internal
Rate Return (IRR) and Benefit Cost Ratio (BCR). This is necessary in order to
ensure that the scenario created is feasibility. Financial feasibility
indicators if they meet the following criteria:
Table 1. Financial Eligibility Requirements
|
Method |
Criterion |
|
NPV |
≤ 0 |
|
BCR |
≤ 1 |
|
IRR |
< COC
(12.00%) |
The results of the method in each
criterion must meet, because it will affect the speed of investment capital
that has been spent. The scenario calculation was made with the total capable
power of the Weda system now amounting to 7 MW made with the arrangement of
each existing plant plus relocation plants from other units. So that it will be
seen the setting of the engine operation pattern of each machine unit with the
source of the generator to get the optimal BPP.
Self-Generating System (SPD) Relocation
Calculation
In
the calculation on the relocation of the power system itself, there is an
additional scenario of machines using PLN machines located in the Daruba area, Morotai, so it
requires a lot of money. The calculation of the financial feasibility study is
made over a period of 20 years, so the results are as follows.
Table 2. Financial Feasibility Results of SPD Relocation
|
Method |
Result |
Criterion |
Information
|
|
NPV |
(802,467,988,734) |
≤ 0 |
Not
Worth It |
|
BCR |
0.42 |
≤ 1 |
Not
Worth It |
|
IRR |
#NUM! |
< COC
(12.00%) |
Not
Worth It |
|
The project is NOT FEASIBLE. |
|||
In
addition, it was found that the value of the Cost of Supply (BPP) in the
scenario using the relocation plant machine combined with the existing
generating machine amounted to Rp 3,090, -
Calculation of Addition of Power Plant
Rental Machine
In
the scenario of adding machines, the rental plant will use additional machines
from the rental vendor. Additional needs of the machine also have a total
capacity of 5 MW. The rental machine contract includes maintenance costs, so
there are no more such costs that are the burden of PLN. With a more efficient
engine comes cheaper fuel costs. With the scenario of adding with rental
machines, it was found that the results were better than the relocation of
power plants. However, the results found are still Not Feasible because they do
not meet NPV, BCR and IRR. The calculation results are as follows.
Table 3. Financial Feasibility Results of Adding Rental
Machines
|
Method |
Result |
Criterion |
Information
|
|
NPV |
(756,291,279,896) |
≤ 0 |
Not
Worth It |
|
BCR |
0.43 |
≤ 1 |
Not
Worth It |
|
IRR |
#NUM! |
< COC
(12.00%) |
Not
Worth It |
|
The project is NOT
FEASIBLE. |
|||
From
the calculation above, although it occurs more cost-effective with more
efficient machine quality, if calculated from financial studies, it is still
not feasible because the income from the selling price is still not so high. In
addition, it was found that the value of the Cost of Supply (BPP) in the
scenario using additional rental machines combined with existing generating
machines amounted to Rp 2,983, -.
Excess Power Purchase Calculation
In
the scenario of purchasing excess power in collaboration with PT Wedabay Energy
which has its own Power Supply Business License (IUPTLS) in the Weda Area,
whose production is carried out by PT IWIP. The total operating machines are
2,200 MW with a total of 6x250 MW and 2x350 MW units. To supply excess power of
5 MW using a Connect Substation (GH) from PT Wedabay Energy which is connected
to the PLN Weda system. The PLN system connection is connected to the 20 kV
Medium Voltage (TM) air network system.
Figure 1. Excess Power
Interconnect Points
A
different type of plant compared to the previous two scenarios that use PLTD,
this scenario uses a power plant with a capacity of 250 MW with an excess power
of 5 MW. Investment needs are used to create interconnection lines from the
Excess Power place to the PLN System and other costs. After calculating
everything, the NPV, BCR, and IRR numbers are as follows.
Table 4. Financial Feasibility Results of Excess Power
Purchase
|
Method |
Result |
Criterion |
Information
|
|
NPV |
29,810,800,952 |
≤ 0 |
Proper |
|
BCR |
1.05 |
≤ 1 |
Proper |
|
IRR |
33.49% |
< COC
(12.00%) |
Proper |
|
The project is FEASIBLE. |
|||
So
from the calculation of the financial review, the excess power purchase
scenario is considered FEASIBLE. In addition, it was found that the
value of the Cost of Supply (BPP) in the scenario using Excess Power from the
Wedabay Energi PLTU combined with the existing generating machine amounted to
Rp 1,244,-
Project Scenario Simulation Using Homer
The
use of the Homer application has advantages compared to other applications. In
Homer, simulations are carried out using data on machine conditions, loading,
and production financing; from this, it is believed to find process results
that are closer to accurate. In addition, Homer is the optimal engine unit when
operated. This implementation was done in the Veda area, Halmahera Island,
North Maluku province.
The
Homer application will automate simulations to determine optimal conditions to
ensure efficient Nett Present Cost (NPC) values. Other indicators can be seen
in the cost of production and Cost of Goods Provided from the project period
undertaken (LCOE).
The
simulation calculation combines existing power plants with additional sources
of other power plants. With a capable load of 7 MW, there is expected to be an
option to simulate the generating unit that operates optimally so that an
optimal BPP value will be found. The daily load used in the operation of the
plant is as follows.
Figure 3. Homeric
Design Daily Loading
Self-Generating System (SPD) Relocation
Simulation
In
the simulation that added the generating machine unit from the relocation of
the Daruba unit with the distribution of plants in PLTD Weda. The data is entered
into the field parameters in the Homer application so that it looks like below.
After the data is entered, it can immediately be run by clicking the calculate
logo in the upper right corner. From the results of running, it was found that
there were 206 options calculated to get optimal costs.
Figure 4. Results of Financial Feasibility Value of SPD
Relocation Machine Scenario
Figure 5. Production
Results of SPD Relocation Machine Scenarios
From
the results of the option options, it was found that the optimal one was found
in the first row with an NPC value of Rp 1,645 trillion within 20 years, an
operation cost of Rp 142 billion in a year and an LCOE of Rp 3,072, -.
Simulation of Adding a
Power Plant Rental Machine
In
the simulation with the scenario of adding a rental machine, the plant added a
rental machine unit with an installed capacity of 800 kW and 1,100 kW. The
distribution is as follows:
Figure 6. Results of Financial Feasibility Value of Rental
Machine Addition Scenario
Figure 7. Production Results of Rental Machine Addition
Scenario
From
the results of the option options, it was found that the optimal was found in
the first row with an NPC value of Rp 1,594 trillion within a period of 20
years, an operation cost of Rp 137 billion in a year and an LCOE of Rp 2,976,-
Excess Power Purchase Simulation
In
the simulation of purchasing excess power, adding a generating machine from PT
Wedabay Energy with a power capacity of 5 MW is taken. The plant used is a
coal-fired Steam Power Plant.
Table 5. Excess Power
Purchasing Machine Unit Capacity
|
NO |
UNIT |
MACHINE NAME |
INSTALLED CAPACITY (kW) |
CAPABLE CAPACITY (kW) |
|
1 |
PLN WEDA |
VOLVO PENTA |
100 |
80 |
|
2 |
PLN WEDA |
MAN |
400 |
300 |
|
3 |
PLN WEDA |
CATERPILLAR |
800 |
500 |
|
4 |
PLN WEDA |
CATERPILLAR |
800 |
500 |
|
5 |
PLN WEDA |
MAN |
400 |
300 |
|
6 |
PLN WEDA |
MITSUBISHI |
635 |
400 |
|
7 |
PLN WEDA |
VOLVO PENTA |
500 |
REBUKE |
|
|
PLTU |
|
|
|
|
1 |
PT WEDA BAY |
|
5,000 |
5,000 |
From
the results of the option, it was found that the optimal one was found in the
first row with an NPC value of Rp 619 billion within a period of 20 years, an
operation cost of Rp 53.5 billion in a year, and an LCOE of Rp 1,156, -.
Project Sensitivity Analysis
Sensitivity
analysis in project management (also known as risk analysis and sensitivity in
project management) is a method for modeling risk in each assignment. Project
sensitivity looks at the big picture to see what, of all the elements involved,
could potentially hinder you from achieving your goals or objectives.
In
this study, factors that affect the value of the project scenario will be
calculated. This is to strengthen the initial calculation that the selected one
is already in accordance with the parameters that are likely to affect the
change. In this case, the parameters used in influencing are Discount Rate and
Fuel Price.
Interest
Rate Value Sensitivity
Interest
Rate is a value used to calculate the present value of a value in the future
because the present value is different or less than the value in the future.
The calculation of three scenarios, namely the relocation of the own generation
system, the addition of power rental machines, and the purchase of excess
power, uses an interest rate of 6.10%, based on the value in the 2023 RKAP.
Project sensitivity here uses a reference interest rate value from 5.25% -
6.75%.
Table 6. Interest Rate Condition Mapping
|
No |
Condition |
Interest Rate |
|
1 |
Condition I |
5.25 |
|
2 |
Condition II |
5.50 |
|
3 |
Condition III |
5.75 |
|
4 |
Condition IV |
6.00 |
|
5 |
Condition V |
6.10 |
|
6 |
Condition VI |
6.25 |
|
7 |
Condition VII |
6.50 |
|
8 |
Condition VIII |
6.75 |
The
calculation of a feasible scenario by purchasing excess power at different
interest rate conditions with a value of 6.75%
Condition
VIII: 6.75%
As
for the recap of the conditions above, it was found that all conditions met the
feasibility, both with low to the highest interest rate value. Where the
highest interest rate results in the best NPV, IRR, and BCR.
Table 7. Financial Feasibility Recap of Interest Rate
Conditions
|
No |
Condition |
Interest Rate |
TARIFF (Rp/kWh) |
CF (%) |
Cost Operation
(Rp) |
NPC (Rp) |
NPV (Rp) |
BCR |
IRR (%) |
BPP (IDR) |
Information |
|
1 |
Condition I |
5.25 |
1365 |
80 |
59,637,098,957 |
623,626,881,384 |
23,721,513,188 |
1.04 |
30.54% |
1,267 |
PROPER |
|
2 |
Condition II |
5.50 |
1365 |
80 |
59,341,795,196 |
623,626,881,384 |
25,452,648,492 |
1.05 |
31.43% |
1,260 |
PROPER |
|
3 |
Condition III |
5.75 |
1365 |
80 |
59,036,665,736 |
623,626,881,384 |
27,232,926,553 |
1.05 |
32.30% |
1,254 |
PROPER |
|
4 |
Condition IV |
6.00 |
1365 |
80 |
58,721,373,773 |
623,626,881,384 |
29,063,878,901 |
1.05 |
33.15% |
1,247 |
PROPER |
|
5 |
Condition V |
6.10 |
1365 |
80 |
58,592,333,877 |
623,626,881,384 |
29,810,800,952 |
1.05 |
33.49% |
1,244 |
PROPER |
|
6 |
Condition VI |
6.25 |
1365 |
80 |
58,395,571,081 |
623,626,881,384 |
30,947,085,818 |
1.06 |
34.00% |
1,240 |
PROPER |
|
7 |
Condition VII |
6.50 |
1365 |
80 |
58,058,897,637 |
623,626,881,384 |
32,884,177,861 |
1.06 |
34.83% |
1,233 |
PROPER |
|
8 |
Condition VIII |
6.75 |
1365 |
80 |
57,710,981,232 |
623,626,881,384 |
34,876,837,449 |
1.06 |
35.65% |
1,226 |
PROPER |
Fuel Price Sensitivity
Fuel
price sensitivity only calculates scenarios with decent conditions. This
further strengthens the influence of changes in fuel prices that use coal. The
initial calculation on the excess power purchase scenario uses a coal price of
90.48 USD / Ton. The details of the estimated changes in coal prices are as
follows.
Table 8. Mapping Fuel Price Conditions
|
No |
Case |
|
1 |
Basecase (Coal 90.48 USD/Ton) |
|
2 |
Case I (Coal 100 USD/Ton) |
|
3 |
Case II (Coal 125 USD/ton) |
|
4 |
Case III (Coal 150 USD/Ton) |
|
5 |
Case IV (Coal 200 USD/ton) |
|
6 |
Case V (Coal 250 USD/ton) |
|
7 |
Case VI (Coal 300 USD/Ton) |
|
8 |
Case VII (Purchase Price 90% BPP Kepmen) |
|
9 |
Case VIII (Purchase Price 70% BPP Kepmen) |
The
coal price in the basecase uses coal price data of 90.48 USD / Ton. In other
conditions the price with sensitivity changes from 100 USD/Ton to 300 USD/Ton.
In addition, it is also calculated based on the Minister of Energy and Mineral
Resources No. 19 of 2017 concerning the purchase of excess power allowed with a
maximum value of 90% of the value of the local BPP. Then strengthened by PLN
Perdir no 0005 of 2018 concerning the purchase of excess power is allowed with
a maximum value of 70% of the value of the local BPP.
The
calculation of sensitivity to changes in fuel prices below is shown in the base
case condition of coal prices of 90.48 USD / Ton. Below is the result of calculating
all conditions that are likely to change.
Condition
1: Base case (Coal 90.48 USD/Ton). From
the conditions consisting of changes in fuel prices, the results of the project
assessment are as follows:
Table 9. Financial Feasibility Recap of Fuel Condition
|
No |
Case |
Excess
Tariff (Rp/kWh) |
CF (%) |
Interest
Rate |
Cost
Operation (Rp) |
NPC (Rp) |
NPV (Rp) |
BCR |
IRR (%) |
BPP (IDR) |
INFORMATION |
|
1 |
Basecase (Coal 90.48 USD/Ton) |
907.77 |
80 |
6.10% |
58,592,333,877 |
623,626,881,384 |
29,810,800,952 |
1.05 |
33.49% |
1,244
|
PROPER |
|
2 |
Case I (Coal 100 USD/Ton) |
995.30 |
80 |
6.10% |
61,834,876,208 |
652,645,312,799 |
792,369,536 |
1.00 |
9.73% |
1,313
|
PROPER |
|
3 |
Case II (Coal 125 USD/ton) |
1,225.16 |
80 |
6.10% |
70,275,294,714 |
728,181,013,018 |
(74,743,330,683) |
0.89 |
#NUM! |
1,492
|
NOT WORTH |
|
4 |
Case III (Coal 150 USD/Ton) |
1,455.02 |
80 |
6.10% |
78,715,713,219 |
803,716,713,237 |
(150,279,030,902) |
0.79 |
#NUM! |
1,672
|
NOT WORTH |
|
5 |
Case IV (Coal 200 USD/ton) |
1,914.74 |
80 |
6.10% |
95,596,550,229 |
954,788,113,675 |
(301,350,431,340) |
0.66 |
#NUM! |
2,030
|
NOT WORTH |
|
6 |
Case V (Coal 250 USD/ton) |
2,374.46 |
80 |
6.10% |
112,477,387,239 |
1,105,859,514,113 |
(452,421,831,778) |
0.56 |
#NUM! |
2,389
|
NOT WORTH |
|
7 |
Case VI (Coal 300 USD/Ton) |
2,834.18 |
80 |
6.10% |
129,358,224,250 |
1,256,930,914,551 |
(603,493,232,216) |
0.49 |
#NUM! |
2,747
|
NOT WORTH |
|
8 |
Case VII (Purchase Price 90% BPP Kepmen) |
2,085.06 |
80 |
6.10% |
101,850,586,917 |
1,010,757,262,612 |
(357,319,580,277) |
0.62 |
#NUM! |
2,163
|
NOT WORTH |
|
9 |
Case VIII (Purchase Price 70% BPP Kepmen) |
1,621.71 |
80 |
6.10% |
84,836,521,797 |
858,493,566,017 |
(205,055,883,681) |
0.74 |
#NUM! |
1,802
|
NOT WORTH |
Based
on these conditions, the fuel price greatly affects the project's feasibility.
It can be seen that the price of Coal at 90.48 USD / Ton is the best in these
conditions, and the price of Coal at 100 USD / Ton is still included in the
decent category.
Project
Scenario Analysis Results
From
the results of the project scenario consisting of 3 (three) scenarios, namely
the Relocation of the Own Generation System, the Addition of Generating Machine
Leases, and the Purchase of Excess Power, it was found that the Excess Power
Purchase scenario was the only feasible. In addition, in the excess power
purchase scenario, the BPP value was found to be the lowest compared to other
scenarios. The following is the calculation value of the Financial Feasibility
Study of each scenario.
Table
10. Relocation of Own Generation System
|
Method |
Result |
Criterion |
Information
|
BPP |
|
NPV |
(802,467,988,734) |
≤ 0 |
Not
Worth It |
3,090 |
|
BCR |
0.42 |
≤ 1 |
Not
Worth It |
|
|
IRR |
#NUM! |
< COC
(12.00%) |
Not
Worth It |
|
|
The project is NOT FEASIBLE. |
||||
Table
11. Additional Generator Machine Rental
|
Method |
Result |
Criterion |
Information
|
BPP |
|
NPV |
(756,291,279,896) |
≤ 0 |
Not
Worth It |
2,983 |
|
BCR |
0.43 |
≤ 1 |
Not
Worth It |
|
|
IRR |
#NUM! |
< COC
(12.00%) |
Not
Worth It |
|
|
The project is NOT FEASIBLE. |
||||
Table
12. Purchase Excess Power
|
Method |
Result |
Criterion |
Information
|
BPP |
|
NPV |
29,810,800,952 |
≤ 0 |
Proper |
1,244 |
|
BCR |
1.05 |
≤ 1 |
Proper |
|
|
IRR |
33.49% |
< COC
(12.00%) |
Proper |
|
|
The project is FEASIBLE. |
||||
The
calculation results are still influenced by several factors that have been made
in the sensitivity of the project with parameters, namely the influence of
Interest Rate and Fuel Price. The effect of changing the Interest Rate between
5.25% to 6.75% is to ensure the optimal value to get the best BPP. The excess
power purchase scenario produces the best BPP value so that it is calculated
with the effect of changes in the Interest Rate. Here's a recap of the
calculations.
|
No |
Condition |
Interest Rate |
TARIFF (Rp/kWh) |
CF(%) |
Cost Operation
(Rp) |
NPC (Rp) |
NPV (Rp) |
BCR |
IRR (%) |
BPP (IDR) |
INFORMATION |
|
1 |
Condition I |
5.25 |
1365 |
80 |
59,637,098,957 |
623,626,881,384 |
23,721,513,188 |
1.04 |
30.54% |
1,267 |
PROPER |
|
2 |
Condition II |
5.50 |
1365 |
80 |
59,341,795,196 |
623,626,881,384 |
25,452,648,492 |
1.05 |
31.43% |
1,260 |
PROPER |
|
3 |
Condition III |
5.75 |
1365 |
80 |
59,036,665,736 |
623,626,881,384 |
27,232,926,553 |
1.05 |
32.30% |
1,254 |
PROPER |
|
4 |
Condition IV |
6.00 |
1365 |
80 |
58,721,373,773 |
623,626,881,384 |
29,063,878,901 |
1.05 |
33.15% |
1,247 |
PROPER |
|
5 |
Condition V |
6.10 |
1365 |
80 |
58,592,333,877 |
623,626,881,384 |
29,810,800,952 |
1.05 |
33.49% |
1,244 |
PROPER |
|
6 |
Condition VI |
6.25 |
1365 |
80 |
58,395,571,081 |
623,626,881,384 |
30,947,085,818 |
1.06 |
34.00% |
1,240 |
PROPER |
|
7 |
Condition VII |
6.50 |
1365 |
80 |
58,058,897,637 |
623,626,881,384 |
32,884,177,861 |
1.06 |
34.83% |
1,233 |
PROPER |
|
8 |
Condition VIII |
6.75 |
1365 |
80 |
57,710,981,232 |
623,626,881,384 |
34,876,837,449 |
1.06 |
35.65% |
1,226 |
PROPER |
From
this calculation, it was found that the Interest Rate value was getting bigger,
resulting in the best BPP value of Rp 1,226, - This was influenced by the
improvement in the value of Cost Operation on the kWh of sales produced. The
effect of fuel changes starts with using the price of Coal in January 2023 of
90.48 USD/Ton to a price of 300 USD/Ton. In addition, the purchase price of 90%
BPP and the purchase price of 70% is calculated from BPP according to the
Decree of the Minister of Energy and Mineral Resources.
The
amount of fuel prices greatly affects the cost of operations and impacts the
value of BPP. The cheaper the fuel price, the lower the BPP value produced. Suppose
you look at the Cost of Goods Provided (BPP) in the Vedic system in 2022 of IDR
4,193 -
compared to the calculation of the financial feasibility study using Homer, the
BPP value of IDR 1,156 - with kWh of production in 2023 of 47,088,000 kWh. In that case, there is a
savings of IDR 143,006,256,000 per year.
CONCLUSION
The
financial feasibility calculation for the Excess Power purchase scenario shows
very positive results, with an NPV value of Rp 29 billion, IRR of 33.49%, and
BCR of 1.05. In addition, an analysis of the overall cost of the system over 20
years shows that the use of Homer applications in the Excess Power scenario
provides the highest efficiency, with NPC of Rp 619 billion, CO of Rp 53
billion, and LCOE of Rp 1,156. Furthermore, through the process of the three
scenarios, it was found that the optimal and feasible BPP value was found in
the Excess Power scenario, with a value of Rp 1,244 (based on KKF calculations)
and Rp 1,156 (based on Homer's simulation). The overall results of this
analysis confirm that the investment in Excess Power is financially viable and
efficient in the long run, giving confidence in the success of this project.
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