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The Development of Photovoltaic Power Plant for Electricity Demand Fulfillment in Remote Regional of Madura Island using System Dynamics Model

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Lilia Quentara at Sekolah Tinggi Teknologi Nasional, Jambi, Indonesia
Lilia Quentara
  • Sekolah Tinggi Teknologi Nasional, Jambi, Indonesia
Erma Suryani at Sepuluh Nopember Institute of Technology
Erma Suryani
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Abstract and Figures

The main problem of the electrical operational systems in Indonesia is how to maintain the continuity of effective and efficient services to the customers and meet the supply and demand for electrical power, particularly a lot of islands area in Indonesia are far distant from the power generation sources. Based on these problems, it is cleared that an electricity system is required for longterm solutions so that it can enhance the role of new and renewable energy, improve the electricity reliability and reduce the energy costs. Efficiency and effectiveness is expected to increase the sustainable electricity supply for remote and isolated area in Madura island by utilizing the available resources like potential solar energy as a new and renewable energy. The development of photovoltaic power plant is a fast and independent solution because the access and infrastructure in Madura island doesn’t support yet for the conventional electrical facilities. System dynamics method is used to analyse the system by creating a scenario model to identify any factors and variables which affect the system. As the result of the scenario model, total demand for electricity supply in the 58 remote villages in Pamekasan is 24,935 MW, which cost Rp 632.812.500.000,- for the photovoltaic power plant investment. To complete the analysis feasibility in order to meet the fulfilment, it is also considered economics aspect with Payback Period, which is need 25 years to return the investment in optimistic scenario.
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ScienceDirect
Available online at www.sciencedirect.com
Procedia Computer Science 124 (2017) 232–238
1877-0509 © 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 4th Information Systems International Conference 2017
10.1016/j.procs.2017.12.151
10.1016/j.procs.2017.12.151 1877-0509
Available online at www.sciencedirect.com
ScienceDirect
Procedia Computer Science 00 (2018) 000–000
www.elsevier.com/locate/procedia
1877-0509 © 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 4th Information Systems International Conference 2017.
4th Information Systems International Conference 2017, ISICO 2017, 6-8 November 2017, Bali,
Indonesia
The Development of Photovoltaic Power Plant for Electricity
Demand Fulfillment in Remote Regional of Madura Island using
System Dynamics Model
Lilia Trisyathia Quentaraa, Erma Suryanib,*
aDepartment of Industrial Engineering, Sekolah Tinggi Teknologi Nasional, Jambi 36125, Indonesia
bDepartment of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo-Surabaya 60111, Indonesia
Abstract
The main problem of the electrical operational systems in Indonesia is how to maintain the continuity of effective and efficient
services to the customers and meet the supply and demand for electrical power, particularly a lot of islands area in Indonesia are
far distant from the power generation sources. Based on these problems, it is cleared that an electricity system is required for long-
term solutions so that it can enhance the role of new and renewable energy, improve the electricity reliability and reduce the energy
costs. Efficiency and effectiveness is expected to increase the sustainable electricity supply for remote and isolated area in Madura
island by utilizing the available resources like potential solar energy as a new and renewable energy. The development of
photovoltaic power plant is a fast and independent solution because the access and infrastructure in Madura island doesn’t support
yet for the conventional electrical facilities. System dynamics method is used to analyse the system by creating a scenario model
to identify any factors and variables which affect the system. As the result of the scenario model, total demand for electricity supply
in the 58 remote villages in Pamekasan is 24,935 MW, which cost Rp 632.812.500.000,- for the photovoltaic power plant
investment. To complete the analysis feasibility in order to meet the fulfilment, it is also considered economics aspect with Payback
Period, which is need 25 years to return the investment in optimistic scenario.
© 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 4th Information Systems International Conference 2017.
Keywords: System Dynamics; Scenario; Electrification Ratio; Photovoltaic Power Plant; Electricity Supply and Demand
* Corresponding author. Tel.: +62-31-5999-944; fax: +62-31-5964-965.
E-mail address: erma.suryani@gmail.com
2 Lilia Trisyathia Quentara and Erma Suryani / Procedia Computer Science 00 (2018) 000–000
1. Introduction
Indonesia is a vast archipelagic country, that’s why the fulfillment of electricity supply and demand in remote areas,
outer islands, and border areas is an important issue that requires a special review in its completion [2][5]. People in
un-electrified areas tend to be isolated from economic developments, knowledge insights, and technology advances.
In 2008, an articles of Indonesia Government Electricity Association (PLN) states in point number 3 that the purpose
and business field is to provide electricity supply business for the public interest in sufficient quantity and quality as a
form of implementation the Government's duties in order to support the national development [23]. Electrification
ratio value showed increasing chart in Indonesia over the last five years (2010-2014). At the end of 2014 the ratio has
reached 81.70%, which is 74.41% for Indonesia outside Java and 86, 69% for the Java island [3]. In 2015 there are
still provinces in Indonesia with electrification ratio below 50%, Jambi (43.88%) and Papua (47.21%), whereas for
Jakarta the capital region of Indonesia and its surroundings has been reached 100%.
Nowadays, the condition of East Java's electricity supply in 2016 still has surplus around 2,600 MW (Mega Watt)
and the excess is channeled to West Java, Central Java, and Bali. Although in 2013 the electrification ratio of East
Java was still 79.21%, then increased to 83.14% in 2014, and by the end of 2015 has reached 86.67% [18]. The number
of new demand for electricity in 2014 of 605,832 households has decreased from the year 2013 which amounted to
657,536 households, but because of the electricity supply and demand that can’t be met, this caused the waiting list
surge from the previous 30,920 households in 2013 increased to 45,296 households by the end of 2014. However, the
amount of electricity surplus is still very possible to increase the supply for Situbondo area whose electrification ratio
is still 64.88% and also for Madura in particular. This program will support the achievement of 100% national
electrification ratio target in 2020 by the government.
For Madura region its self, from a total of 219,439 households, which has been electrified is only about 129,522.
The electrification ratio in 2014 reached only 59.02%, which increased to 60.55% by the end of 2015. But for the
archipelago region, the electrification ratio still has not touched 40%. Data from the Department of Energy of Human
Resources of East Java Province as December 2015 stated that the number of un-electrified villages in Madura spread
in 4 districts, namely 50 villages in Bangkalan Regency, 78 villages in Sampang Regency, 58 villages in Pamekasan
District, and 32 Village in Sumenep regency [21] [22] [24] [25]. Prior to the construction of the Suramadu bridge,
which connected Java Island and Madura, in 2010, the available of electricity supply in Madura was 80MW, increasing
to 200MW in 2012, and going to 260MW by the earlier 2016.
The majority of the un-electrified villages are on the North Coast of Madura (Pantura) and also some unreached
islands from the main electricity source. For the archipelago, five islands are powered by Diesel Power Plant (PLTD),
including Sapeken, Gili Genting, Mandangin which have been operating for 24 hours, while Kangean and Sapudi are
still operating for 12 hours only. Based on data at the PLN office in Pamekasan area that takes care whole electricity
operational in Madura, the uneven flow of electricity in the southern and northern regions is caused by the less
supportive road infrastructure. Powerful electricity is in the southern region of Madura because the transmission
networks are built in the south, ranging from Suramadu, Bangkalan, Blega, Sampang, Pamekasan and Sumenep. To
provide the services to the northern region, namely Ambunten, Waru, Ketapang and Tanjung Baru, PLN requires long
power lines for infrastructure revamping process. Madura topography becomes an investment constraint in building
electricity infrastructure because in one village has only about 10 houses, and the distance of the villages are far from
each other [11]. In addition to many villages located in the highlands and also some islands that are difficult to reach.
According to Solarex (1996), Indonesia as a tropical country has high solar energy potential with an average
radiation of 4.5 kWh2 / m2 / day - 5.0 kWh2 / m2 / day, which means for 1 Kw photovoltaic (PV) can produce 4 to 5
kWh of electrical energy in one day [7]. These, became an advantage solution for PLN to build up some photovoltaic
power plants in order to electrified the remote areas in Madura Island which far from the main power generation
sources. The independency of photovoltaic power plant by processing the solar potency into electricity is a new trend
in Indonesia to overcome the un-electrified islands [4].
From the observation of the situation, conditions and issues in electrical operational system in Indonesia, the
research questions are: (1). How is the fulfillment condition of the electricity demand in remote area Madura Island?
(2). What are the constraints and obstacles for electricity supply? (3). What kind of renewable power plant could be
invested in remote area and how many capacity is needed?
Lilia Trisyathia Quentara et al. / Procedia Computer Science 124 (2017) 232–238 233
Available online at www.sciencedirect.com
ScienceDirect
Procedia Computer Science 00 (2018) 000–000
www.elsevier.com/locate/procedia
1877-0509 © 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 4th Information Systems International Conference 2017.
4th Information Systems International Conference 2017, ISICO 2017, 6-8 November 2017, Bali,
Indonesia
The Development of Photovoltaic Power Plant for Electricity
Demand Fulfillment in Remote Regional of Madura Island using
System Dynamics Model
Lilia Trisyathia Quentaraa, Erma Suryanib,*
aDepartment of Industrial Engineering, Sekolah Tinggi Teknologi Nasional, Jambi 36125, Indonesia
bDepartment of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo-Surabaya 60111, Indonesia
Abstract
The main problem of the electrical operational systems in Indonesia is how to maintain the continuity of effective and efficient
services to the customers and meet the supply and demand for electrical power, particularly a lot of islands area in Indonesia are
far distant from the power generation sources. Based on these problems, it is cleared that an electricity system is required for long-
term solutions so that it can enhance the role of new and renewable energy, improve the electricity reliability and reduce the energy
costs. Efficiency and effectiveness is expected to increase the sustainable electricity supply for remote and isolated area in Madura
island by utilizing the available resources like potential solar energy as a new and renewable energy. The development of
photovoltaic power plant is a fast and independent solution because the access and infrastructure in Madura island doesn’t support
yet for the conventional electrical facilities. System dynamics method is used to analyse the system by creating a scenario model
to identify any factors and variables which affect the system. As the result of the scenario model, total demand for electricity supply
in the 58 remote villages in Pamekasan is 24,935 MW, which cost Rp 632.812.500.000,- for the photovoltaic power plant
investment. To complete the analysis feasibility in order to meet the fulfilment, it is also considered economics aspect with Payback
Period, which is need 25 years to return the investment in optimistic scenario.
© 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 4th Information Systems International Conference 2017.
Keywords: System Dynamics; Scenario; Electrification Ratio; Photovoltaic Power Plant; Electricity Supply and Demand
* Corresponding author. Tel.: +62-31-5999-944; fax: +62-31-5964-965.
E-mail address: erma.suryani@gmail.com
1. Introduction
Indonesia is a vast archipelagic country, that’s why the fulfillment of electricity supply and demand in remote areas,
outer islands, and border areas is an important issue that requires a special review in its completion [2][5]. People in
un-electrified areas tend to be isolated from economic developments, knowledge insights, and technology advances.
In 2008, an articles of Indonesia Government Electricity Association (PLN) states in point number 3 that the purpose
and business field is to provide electricity supply business for the public interest in sufficient quantity and quality as a
form of implementation the Government's duties in order to support the national development [23]. Electrification
ratio value showed increasing chart in Indonesia over the last five years (2010-2014). At the end of 2014 the ratio has
reached 81.70%, which is 74.41% for Indonesia outside Java and 86, 69% for the Java island [3]. In 2015 there are
still provinces in Indonesia with electrification ratio below 50%, Jambi (43.88%) and Papua (47.21%), whereas for
Jakarta the capital region of Indonesia and its surroundings has been reached 100%.
Nowadays, the condition of East Java's electricity supply in 2016 still has surplus around 2,600 MW (Mega Watt)
and the excess is channeled to West Java, Central Java, and Bali. Although in 2013 the electrification ratio of East
Java was still 79.21%, then increased to 83.14% in 2014, and by the end of 2015 has reached 86.67% [18]. The number
of new demand for electricity in 2014 of 605,832 households has decreased from the year 2013 which amounted to
657,536 households, but because of the electricity supply and demand that can’t be met, this caused the waiting list
surge from the previous 30,920 households in 2013 increased to 45,296 households by the end of 2014. However, the
amount of electricity surplus is still very possible to increase the supply for Situbondo area whose electrification ratio
is still 64.88% and also for Madura in particular. This program will support the achievement of 100% national
electrification ratio target in 2020 by the government.
For Madura region its self, from a total of 219,439 households, which has been electrified is only about 129,522.
The electrification ratio in 2014 reached only 59.02%, which increased to 60.55% by the end of 2015. But for the
archipelago region, the electrification ratio still has not touched 40%. Data from the Department of Energy of Human
Resources of East Java Province as December 2015 stated that the number of un-electrified villages in Madura spread
in 4 districts, namely 50 villages in Bangkalan Regency, 78 villages in Sampang Regency, 58 villages in Pamekasan
District, and 32 Village in Sumenep regency [21] [22] [24] [25]. Prior to the construction of the Suramadu bridge,
which connected Java Island and Madura, in 2010, the available of electricity supply in Madura was 80MW, increasing
to 200MW in 2012, and going to 260MW by the earlier 2016.
The majority of the un-electrified villages are on the North Coast of Madura (Pantura) and also some unreached
islands from the main electricity source. For the archipelago, five islands are powered by Diesel Power Plant (PLTD),
including Sapeken, Gili Genting, Mandangin which have been operating for 24 hours, while Kangean and Sapudi are
still operating for 12 hours only. Based on data at the PLN office in Pamekasan area that takes care whole electricity
operational in Madura, the uneven flow of electricity in the southern and northern regions is caused by the less
supportive road infrastructure. Powerful electricity is in the southern region of Madura because the transmission
networks are built in the south, ranging from Suramadu, Bangkalan, Blega, Sampang, Pamekasan and Sumenep. To
provide the services to the northern region, namely Ambunten, Waru, Ketapang and Tanjung Baru, PLN requires long
power lines for infrastructure revamping process. Madura topography becomes an investment constraint in building
electricity infrastructure because in one village has only about 10 houses, and the distance of the villages are far from
each other [11]. In addition to many villages located in the highlands and also some islands that are difficult to reach.
According to Solarex (1996), Indonesia as a tropical country has high solar energy potential with an average
radiation of 4.5 kWh2 / m2 / day - 5.0 kWh2 / m2 / day, which means for 1 Kw photovoltaic (PV) can produce 4 to 5
kWh of electrical energy in one day [7]. These, became an advantage solution for PLN to build up some photovoltaic
power plants in order to electrified the remote areas in Madura Island which far from the main power generation
sources. The independency of photovoltaic power plant by processing the solar potency into electricity is a new trend
in Indonesia to overcome the un-electrified islands [4].
From the observation of the situation, conditions and issues in electrical operational system in Indonesia, the
research questions are: (1). How is the fulfillment condition of the electricity demand in remote area Madura Island?
(2). What are the constraints and obstacles for electricity supply? (3). What kind of renewable power plant could be
invested in remote area and how many capacity is needed?
234 Lilia Trisyathia Quentara et al. / Procedia Computer Science 124 (2017) 232–238
Lilia Trisyathia Quentara and Erma Suryani / Procedia Computer Science 00 (2018) 000–000 3
2. Methodology
Based on the problems that have been described previously, the purpose of this study is to identify the factors that
caused obstacles in electricity supply in Madura Island by developing a simulation for an effective, efficient and
reliable solutions in electrical operational systems. We used system dynamics method based on consideration that
system dynamics enable us to accommodate internal and external factors that have significant impact to electricity
demand and operational process, as well as the determination of the appropriate and targeted electrical operational
system. As the first step, we defined and identified the currently problems in electrical operational system to
understanding the whole system before make a new model which represented the real system. Ventana Simulation
tools figured out the predominant factors and variables in the simulation system.
Causal Loop Diagram (CLD) is a model development in representation the real system, and it was used to analyze
the electrical operational systems by determined all variables which interacts each other and also have impact to the
system [11]. Fig. 1 below shows the variables in electrical operational system and their relevancy in electricity deficit
supply in Madura island.
E
Fig. 1. Causal loop diagram electricity deficit supply in Madura.
Otherwise, the development model should pass two step of validation process to determine whether it is acceptable
to represent the real system or not. The first validation test is a statistical comparison of the average (mean
comparison), and the second test is amplitude variation ratio (percentage of error variance) [1] [6].
The Payback Period (PP) calculation is considered to study the feasibility investment of photovoltaic power plant
as the solution for the deficit electricity supply which created an independent electricity system in remote area.
ELECTRICITY
DEFICIT SUPPLY in
MADURA
Electricity Supply in
Madura
Number of Electrified
Household
Number of
Household in Madura
Number of
un-electrified villages in
Madura
Bangkalan
Regency
Sampang Regency
Number of
un-electrified
household
Electricity Demand
in Madura
Electricity Demand
Prediction
Total of electricity
demand di Madura
Pamekasan
regency
Sumenep Regency
Standard of Household
Power Subscribe
Electrification
Ration
Renewable
Power Plant
Electricity Customer
other sectors
(1)
(2)
Lilia Trisyathia Quentara et al. / Procedia Computer Science 124 (2017) 232–238 235
Lilia Trisyathia Quentara and Erma Suryani / Procedia Computer Science 00 (2018) 000–000 3
2. Methodology
Based on the problems that have been described previously, the purpose of this study is to identify the factors that
caused obstacles in electricity supply in Madura Island by developing a simulation for an effective, efficient and
reliable solutions in electrical operational systems. We used system dynamics method based on consideration that
system dynamics enable us to accommodate internal and external factors that have significant impact to electricity
demand and operational process, as well as the determination of the appropriate and targeted electrical operational
system. As the first step, we defined and identified the currently problems in electrical operational system to
understanding the whole system before make a new model which represented the real system. Ventana Simulation
tools figured out the predominant factors and variables in the simulation system.
Causal Loop Diagram (CLD) is a model development in representation the real system, and it was used to analyze
the electrical operational systems by determined all variables which interacts each other and also have impact to the
system [11]. Fig. 1 below shows the variables in electrical operational system and their relevancy in electricity deficit
supply in Madura island.
E
Fig. 1. Causal loop diagram electricity deficit supply in Madura.
Otherwise, the development model should pass two step of validation process to determine whether it is acceptable
to represent the real system or not. The first validation test is a statistical comparison of the average (mean
comparison), and the second test is amplitude variation ratio (percentage of error variance) [1] [6].
The Payback Period (PP) calculation is considered to study the feasibility investment of photovoltaic power plant
as the solution for the deficit electricity supply which created an independent electricity system in remote area.
ELECTRICITY
DEFICIT SUPPLY in
MADURA
Electricity Supply in
Madura
Number of Electrified
Household
Number of
Household in Madura
Number of
un-electrified villages in
Madura
Bangkalan
Regency
Sampang Regency
Number of
un-electrified
household
Electricity Demand
in Madura
Electricity Demand
Prediction
Total of electricity
demand di Madura
Pamekasan
regency
Sumenep Regency
Standard of Household
Power Subscribe
Electrification
Ration
Renewable
Power Plant
Electricity Customer
other sectors
(1)
(2)
4 Lilia Trisyathia Quentara and Erma Suryani / Procedia Computer Science 00 (2018) 000–000
3. Result and Discussion
3.1. Electricity Demand Model for Madura
Historical data that were collected from PLN in 2011 to 2015 show an average that electrical power increased 7.5%
annually, which for households increase 6.4% on average, 13.9% in business, Industry (industry) 12.2%, public and
social (public and social) of 8.3% [23]. Fig. 2 is a base model for representing the electricity demand and its prediction,
that were discussed in our previous research [16].
Fig. 2. Base model for electricity demand in Madura.
3.2. Validity and Reliability
The electrical power requirement model developed in the simulation can be said to be valid and represent the
system if the calculation has been qualified for mean comparison (E1) and variance error (E2). Data in Table 1 below
present the electricity demand per customer category, where the results obtained is less than the maximum limit
requirement so that the development model in Fig. 2 was valid and reliable.
Table 1. Mean comparison (E1) and error comparison (E2) for electricity demand in Madura.
Variable
Average (Volt Ampere/VA)
Mean
Comparison
Standard Deviation (VA)
Error
Variance
Data
Simulation
E
1
≤5%
Data
Simulation
E
2
≤30%
Household
264.025.145
264.455.266
0,0016
82.914.338
83.728.208
0,0098
Business
24.184.634
23.547.630
0,0263
16.233.000
13.572.250
0,1639
Industry
9.040.434
9.466.160
0,0449
3.863.645
4.226.355
0,0939
Public and Social
27.455.401
28.035.916
0,0211
10.533.632
10.460.109
0,0070
Total Electricity Needs
325.190.551
325.484.972
0,0009
112.447.581
111.780.423
0,0059
3.3. Scenario Model
The majority of PLN customers in Madura are household category whose electrical power about 450VA - 1300VA,
so the calculation of minimum electrical power requirement for photovoltaic power plant development planning is
still far from the standard 900VA that should be held for household electrical demand [7] [13]. In this research, the
value of electricity demand restricted only in Pamekasan Regency because it is where the main office of PLN that in-
Household
Business
Industry
Public and
Social
Rate in HH
Rate in B
Rate in I
Customer
Electricity
Demand
(Volt
Ampere)
<Time>
Business
rate 2000
- 2015
Industry
rate 2000
- 2015
P&S rate
2000 -
2015
Rate in P&S
HH rate
2000 -
2015
Electr icity
Demand for
Un-electrified
Househo ld
<Number of
Un-electrified
Household>
Standard Electricity
Power for Household
Total
Electricity
Demand in
Madura
236 Lilia Trisyathia Quentara et al. / Procedia Computer Science 124 (2017) 232–238
Lilia Trisyathia Quentara and Erma Suryani / Procedia Computer Science 00 (2018) 000–000 5
charge to control the electrical operational system for whole Madura.
The development planning of photovoltaic power plant for five sub-districts (Waru, Palengaan, Batumarmar,
Pasean, and Pakong) that located in Pamekasan Regency will be divided into two types to adjust the geographical
condition of the un-electrified villages, namely:
Solar Home System (SHS) by using 50Watt peaks (WP) solar panels for villages located in the highlands,
Centralized Photovoltaics (Photovoltaic communal) by using 100Wp solar panels for coastal and lowland
Fig. 3 below was a scenario model to calculate the electricity demand for 58 remote villages in Pamekasan regency
by determining the current electricity supply for Madura island and the capacity of photovoltaic power plant capacity
which is categorized into 2 types solar panel according to the topography landscape.
Fig.3. Scenario model for fulfillment ratio the electricity demand in Madura
The total requirement for electricity supply in the five sub-districts in Pamekasan is 24,935 MW. These, will be
fulfilled by the development of new and renewable power plant with local resources like the Photovoltaic Power Plant
whose electrical supply capacity amount 25 MW.
3.4. Economics Aspect
The feasibility study of the economical aspect for the Photovoltaic Power Plant investment is calculated in detail
from the financial valuation of the cash flow of an investment. The Payback Period (PP) method is used to calculate
the amount of time it takes to return the money invested. Profit and cost analysis is needed in deciding whether a
project / activity is feasible or not realized. The depreciation value associated with the economic life in the Photovoltaic
Power Plant system is divided into two categories, namely: 25 years for solar panels, and 5 years for equipment
components (batteries, inverters, etc.). Therefore, there must be a replacement of components every 5 years to maintain
the continuity of power supply whose source of fund is burdened to the community and put into operational cost.
By using the formulation in [8, 9], the capital investment and cost to be borne in detail will be described in the
following calculations for 25MW needs for Photovoltaic Power Plant is:
Solar Panel = 25 MW x US$ 1.875.000 x Rp 13.500,- = Rp 632.812.500.000,-
Power Plant Component = 25% x Rp 632.812.500.000,- = Rp 158.203.125.000,-
Depreciation Component (per 5 year) = Rp 158.203.125.000,- / 5 = Rp 31.640.625.000,- /year
Electrical
Power
Supply in
Madura
(MW)
Madura Electricity
Supply Before 2011
Madura Electricity
Supply After 2011
Madura Electricity
Supply in 2016
<Time>
Scenario
Fulfilment
Ratio for
Electricity
Demand in
Madura
<Total Electricity
Demand in
Madura>
Scn. Total
Electricity
Demand
for Madura
Coefficient VA
to Watt
Coefficient Watt
to MW
<Photovoltaic Capacity
Supply In Pamekasan>
Lilia Trisyathia Quentara et al. / Procedia Computer Science 124 (2017) 232–238 237
Lilia Trisyathia Quentara and Erma Suryani / Procedia Computer Science 00 (2018) 000–000 5
charge to control the electrical operational system for whole Madura.
The development planning of photovoltaic power plant for five sub-districts (Waru, Palengaan, Batumarmar,
Pasean, and Pakong) that located in Pamekasan Regency will be divided into two types to adjust the geographical
condition of the un-electrified villages, namely:
Solar Home System (SHS) by using 50Watt peaks (WP) solar panels for villages located in the highlands,
Centralized Photovoltaics (Photovoltaic communal) by using 100Wp solar panels for coastal and lowland
Fig. 3 below was a scenario model to calculate the electricity demand for 58 remote villages in Pamekasan regency
by determining the current electricity supply for Madura island and the capacity of photovoltaic power plant capacity
which is categorized into 2 types solar panel according to the topography landscape.
Fig.3. Scenario model for fulfillment ratio the electricity demand in Madura
The total requirement for electricity supply in the five sub-districts in Pamekasan is 24,935 MW. These, will be
fulfilled by the development of new and renewable power plant with local resources like the Photovoltaic Power Plant
whose electrical supply capacity amount 25 MW.
3.4. Economics Aspect
The feasibility study of the economical aspect for the Photovoltaic Power Plant investment is calculated in detail
from the financial valuation of the cash flow of an investment. The Payback Period (PP) method is used to calculate
the amount of time it takes to return the money invested. Profit and cost analysis is needed in deciding whether a
project / activity is feasible or not realized. The depreciation value associated with the economic life in the Photovoltaic
Power Plant system is divided into two categories, namely: 25 years for solar panels, and 5 years for equipment
components (batteries, inverters, etc.). Therefore, there must be a replacement of components every 5 years to maintain
the continuity of power supply whose source of fund is burdened to the community and put into operational cost.
By using the formulation in [8, 9], the capital investment and cost to be borne in detail will be described in the
following calculations for 25MW needs for Photovoltaic Power Plant is:
Solar Panel = 25 MW x US$ 1.875.000 x Rp 13.500,- = Rp 632.812.500.000,-
Power Plant Component = 25% x Rp 632.812.500.000,- = Rp 158.203.125.000,-
Depreciation Component (per 5 year) = Rp 158.203.125.000,- / 5 = Rp 31.640.625.000,- /year
Electrical
Power
Supply in
Madura
(MW)
Madura Electricity
Supply Before 2011
Madura Electricity
Supply After 2011
Madura Electricity
Supply in 2016
<Time>
Scenario
Fulfilment
Ratio for
Electricity
Demand in
Madura
<Total Electricity
Demand in
Madura>
Scn. Total
Electricity
Demand
for Madura
Coefficient VA
to Watt
Coefficient Watt
to MW
<Photovoltaic Capacity
Supply In Pamekasan>
6 Lilia Trisyathia Quentara and Erma Suryani / Procedia Computer Science 00 (2018) 000–000
By considering the Photovoltaic Power Plant investment worth Rp 632,812,500,000, - with the economic life of 25
years and Bank Interests 7% per year, then calculated how the value of revenues from the sale of electric power
generated, where the annual income is derived from electricity bills during the year. Table 2 below shows the condition
for payback period scenario.
Table 2. Payback Period Calculation based on Scenario
No.
Scenario
Result Analysis
1 Optimistic Investment value Rp 632.812.500.000,- and income value Rp 24.657.500.000,-/year, so the long term
period needed to investment return is 25,68 years.
2 Most Likely Investment value Rp 632.812.500.000,- and income value Rp 18.478.125.000,- /year, so the long term
period needed to investment return is 34,25 years.
3 Pesimist Investment value Rp 1.740.234.375.000,- and income value Rp 24.657.500.000,-/year, so the long term
period needed to invetsmen return is 70,63 year.
4. Conclusion
Building a new power plant source should be based on good planning as investment in the electricity industry is
demanded for long-term benefits. This should be the main consideration of PT. PLN in conducting an electricity
project. The amount of investment required will be one of the obstacles in determining the priority scale of
infrastructure development in a region. However, a smooth flow of operational funds can be used to support new
investment projects that reach areas in Madura that are still unable to enjoy electricity.
Basically the technical problems that become obstacles in the electrical operational system encountered in Madura
will also be found in other parts of Indonesia, as a vast and rich country of islands as well as small islands far from
the main power source. So in the future, serious and specific assessment of the potential of natural resources for new
and renewable energy that is owned by each remote, outer, and leading areas, in order to create an independent
electrical concept.
Acknowledgements
References
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  • May 2008
  • ENERG ECON
The Chinese economy is in a stage of energy transition: from low efficiency solid fuels to oil, gas, and electric power, from agriculture to urbanization and industrialization, from heavy industry to lighter and high tech industry, from low motorization to rapid growth of the motor vehicle population. Experts fear that continued rapid economic growth in China will translate into a massive need to expand imports of oil, coal, and gas. We build an econometric model of the Chinese energy economy based on the energy balance. We use that model to forecast Chinese energy consumption and imports to 2020. The study suggests that China will, indeed, require rapidly growing imports of oil, coal, and gas. This growth is not so sensitive to the rate of economic growth as to increases in motorization. It can be offset, but probably only in small part, by increasing domestic energy production or by improvements in the efficiency of use, particularly in the production of electric power.
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Does energy consumption cause economic growth?: Evidence from a systematic study of over 100 countries
Article
  • Mar 2008
  • J POLICY MODEL
Energy arguably plays a vital role in economic development. Hence many studies have attempted to test for causality between energy and economic growth; however, no consensus has emerged. This paper, therefore, tests for causality between energy and GDP using a consistent data set and methodology for over 100 countries. Causality from energy to GDP is found to be more prevalent in the developed OECD countries compared to the developing non-OECD countries; implying that a policy to reduce energy consumption aimed at reducing emissions is likely to have greater impact on the GDP of the developed rather than the developing world.
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Manajemen Aset Jaringan Distribusi Energi Listrik untuk Meningkatkan Keandalan Jaringan (Studi Kasus PLN Pamekasan
  • Jan 2015
  • P F Adipraja
Adipraja, P. F. (2015) "Manajemen Aset Jaringan Distribusi Energi Listrik untuk Meningkatkan Keandalan Jaringan (Studi Kasus PLN Pamekasan)". Program Magister Sistem Informasi Institut Teknologi Sepuluh Nopember.