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MAPPING OF RENEWABLE ENERGY POTENTIAL IN ASMAT REGENCY

MAPPING OF RENEWABLE ENERGY POTENTIAL IN ASMAT REGENCY
Indonesia is a developed country with a growing population growth. Because of the increase of the population demand of electricity will be more increase. Because of that Indonesia need more resources which can generate electrical energy. Therefore, we need

Edo Bintang Napitupulu
School of Electrical Engineering and
Informatics - Institut Teknologi Bandung






Abstract –- Indonesia is a developed country with a growing population growth. Because
of the increase of the population demand of electricity will be more increase.
Because of that Indonesia need more resources which can generate electrical
energy. Therefore, we need renewable energy potential for generate electrical
energy especially in rural areas. Rural areas have problems about logistic so
that development in the area doesn’t improve. So we need offgrid powerplant
which generate by renewable energy sources.
So, we take an objective that is Pirien Village that located in
Fayit Sub-District. From Homer application and Google Earth we can decide the
characteristics of the village. The characteristics that we get among others
irradiance data, wind velocity, clear index and temperature. From that
characteristics we can conclude that Pirien Village have potential for solar
and wind renewable energy which might be implemented with further research.

Keywords— Hybrid Power Plant; Irradiance,
Temperature, Wind Speed;
Rural Areas;
HOMER Pro

I.
Introduction
Population growth is a sure thing in the
times. With that increasing population, the community's needs for the amount of
electricity used will definitely increase. In increasing energy demand, in this
case electricity, the operational costs will be more expensive. To be able to
balance the electricity needs of the community with electricity that can be
produced, assistance from Reneweable Energy Resources (RES) is needed to
generate more electricity.[1]

The power plant in Indonesia on average is
still a power plant that uses fossils as fuel. This fuel is a fuel that cannot
be renewed or can run out and emit pollution as well. To prevent this we must
replace or add a generator that uses renewable energy (RES). Especially in
Indonesia, its natural wealth is very supportive of this.
[2]
In the construction of
electricity infrastructure, equal distribution of infrastructure must be
considered in both large cities and small cities. Based on [1] electrofication in
Indonesia has only reached 65%, in increasing electrofication in small areas we
can use new renewable energy plants (EBT). The construction of electricity
infrastructure in remote areas is usually hampered due to economic problems and
separate development from the center (offgrid) [3]. This can also be helped by
using the application so that we can correctly estimate the generator that we
will build so that we will not experience losses and can optimize the plant
built. [ Zambrut Journal ]

Power plants with EBT
sources will always develop every year.[4] This means that in designing this
EBT generator, it must still calculate the capabilities of this plant so that
the plant can last for decades. In choosing this EBT generator, we also have to
pay attention to environmental factors, namely both in terms of the economy,
public acceptance, technology and environmental factors so that the plant works
optimally and lasts long. [5]Renewable energy is a renewable energy source.
Generally renewable energy sources are wind energy, water energy, and biomass
[6]

Every thing has its
disadvantages as well as plants with renewable energy. This renewable energy is
intermittent and non-dispatchable energy, which means that the plant with
renewable energy is very dependent on the nature / environment. While the needs
of the community for electricity needs cannot depend on environmental
conditions because human needs are dynamic.[7] To overcome this we can use
batteries to store energy from renewable energy sources when the energy
produced by the plant is greater than the use of the community at that time. In
determining the battery we must be able to regulate / determine the battery so
that the effective battery work is neither excessive nor less. [8]

II.
Research Methodology
A.
Data
This final project research aims to provide electricity solutions to villages that have not been electrified by PLN itself. The object of this research is one of the areas in the most disadvantaged and outermost areas in Indonesia. The left behind area is an area that has a low electrification ratio. The solution to this area is also the construction of a hybrid power plant. The hybrid plant will also use diesel-solar wind as its main source. This hybrid plant will not be connected to the PLN network so that research on the optimization of hybrid plants in the area. The area chosen is a village in Fayit Subdistrict, Asmat Regency, Papua. Papua is an area that has a lot of natural resources and biodiversity, so we have to take advantage of this by providing electricity services like those in urban areas. This village is one of 23 villages in Fayit District, namely Pirien Village. This Pirien village is a village consisting of 103 families and is geographically adjacent to the coastline. This area has an average air temperature of 24,630. The average wind speed in this area is 3.35 m / s with the average irradiation in this area if in units of kWh is 4.74 kWh / m2 / day. This study aims to determine the type of solar-wind-diesel hybrid generator that will be used. This is influenced by the natural conditions in the village and is influenced by the peak load in the area. For that we need primary data and secondary data. Primary data is the result of data obtained directly by the author from a hybrid generator system simulation by the Homer Pro and PVSyst programs. These primary data are obtained from NASA through software such as the HOMER Pro and Pvsyst that we use. Secondary data is data obtained from various kinds of sources and literature that have been read or done. An example of this secondary data is potential load. Potential load data can be seen from the Asmat Regency Central Bureau of Statistics. The primary and secondary data will be processed using HOMER Pro software. The data obtained in this study will be presented in the form of a simulation data table about natural data and renewable energy sources and graphs to find out the relationship of related parameters. Analysis related to processing and presenting data will be as objective as possible. The analysis carried out on the results will be based on the basic theories related and about the condition of renewable energy in the area.
B.
Methods
The methodology used in the study is found
in 4 main components, namely regional selection, primary data search, secondary
data search and validation. For regional elections, a search for disadvantaged
areas was targeted by us in Asmat District. We get the data from this lagging
village from the PLN statistics center in Asmat Regency. After obtaining the
village, a search for its coordinate point which is longitude and latitude from
Google Earth processing is carried out. Search for primary data itself is done
by entering the coordinates that have been obtained and entered into the HOMER
Pro program. From the HOMER Pro program we will get data such as the speed of
the wind, sunlight and others. Secondary data search is obtained through BPS
statistics and the provisions of the Ministry of Energy and Mineral Resources
(ESDM) for the energy of underdeveloped regions. After that, a peak load
analysis will be carried out by the HOMER Pro software and re-checking using
PVSyst. The results obtained from both software are expected to be relevant to
one another.

Methodology points :
1. Conduct literature studies on PV, wind
turbines, controllers, converter circuits (DC-DC converters, rectifiers,
inverters), and batteries along with the characteristics of each component.

2. Conduct literature studies on PV-wind hybrid
systems that already exist in Indonesia.

3. Make PV modeling simulations, wind turbines,
controllers, converter circuits (DC-DC converters, rectifiers, inverters), and
batteries.

4. Parameterizing components based on existing
systems.

5. Simulate a typical PV-wind hybrid system and
analyze the work of each component.

6. Conduct an observation of the PV-wind hybrid
system according to the criteria of the research object, namely in the Amaru
Village, Asmat Regency.

7. Making modeling of research objects and
simulating hybrid PV-wind systems in the object of research.

8. Parameterizing components in accordance with
the components in the object of research.

9. Analyze system performance which is the
object of research.

10.Comparing the results of the system performance
studied with a typical system by considering the influence of external
variables.

11.Perform system optimization in the object of
research by considering these external variables.


C. Instrumentation
Instrumentation used is computer
software namely Google Earth, HOMER Pro and PVSyst. Google Earth is used to get
digital images of the shape of the earth from areas that are the object of
research. From Google Earth we will also get a coordinate point for input to
HOMER Pro.

After obtaining coordinate data from
Google Earth then HOMER is used (Hybrid Optimization of Multiple Energy
Resources) which is a desktop application with global standards to model
microgrid systems both off-grif and grid-connected especially for systems with
renewable energy sources. HOMER helps in searching data by retrieving relevant
data from NASA (irradiance data, wind speed, and wave data). HOMER modeling
aims to provide a suitable model for the generation system both physically and
the life cycle costs.

There are three basic things that
HOMER does, namely, simulation, optimization and sensitivity analysis. In the
simulation phase, HOMER will conduct performance modeling of the generating
system at every hour of the year and determine the technical possibilities and
costs in its life cycle. In the optimization phase, HOMER simulates different
system configurations to obtain the most optimum technical and financial system
configuration model. For sensitivity analysis, HOMER does a lot of optimization
with input made in a period to get results from uncertainty of input or change
of model from input. This helps to determine the fixed generator that we will
use so as to minimize errors and losses.

III.
Discussion
A. Research Object
In the research stages of this Final
Project, the object of research is an area that has the criteria, the foremost
and outermost in Indonesia. Based on Presden Regulation No. 131 of 2015, which
relates to underdeveloped regions is a district area that has also not
developed with other categories on a national scale. One of the indicators used
is the facility in this case is an electrical facility / electrofication ratio.
Papua is an area that has electrofication which is quite low at the moment,
which is 72.04% in 2018 [10]. The area which is the object of research in Asmat
Regency, Papua Province, more precisely Pirien Village.

Pirien Village is one of the villages in
Asmat Regency, Papua Province and is included in the 3T category because it
does not have electricity facilities either from PLN or Non-PLN (private).
Pirien village is located at coordinates 5o57'8.45 "South Latitude and
138o18'32.63" East Longitude. This village is one of the villages that has
no electricity facilities at all. The villages that have not been electrified
in Asmat Regency are as many as 58 villages with a total of 211 villages [11].

This Pirien village had 109 families in 2014
[11]. Located in the District of Fayit and is one of the villages that have not
been electrified from 4 villages that have not been electrified in the District
of Fayit. The locations of Asmat and Pirien Districts are included as follows:

Daily Irradiation
states the large amount of daily sunlight radiation in the area. Daily
Irradiation is expressed in units of kWh / m2 / day. The Clearness Index states
how bright the area is, in terms of the abundance / density of clouds in a
particular period in the area. Wind Speed ​​states the wind speed in the area
based on height. Wind Speed ​​is expressed in units of m / s. Daily Temperature
stated the high and low average temperature in the area. Daily Temperature is
expressed in units of oC.

From the data we
get, we can see that the climate and weather characteristics change every
month.

From the average
data obtained, it can be seen that the overall average can be a general
description for Pirien village, as follows.

From the data above, we can see that solar
irradiation is obtained at an average of 4.745 kWh / m2 / day and the average
temperature is 24.63 oC, where with irradiation above 1kWh / m2 / day and a
suitable temperature then the construction of the generator off -grid with solar energy can be done [12]. With an
average wind speed of above 2m / s, we can say that a plant with wind energy is
also quite possible [13]. It can be concluded that for the Pirien village there
is potential for solar and wind renewable energy which might be implemented
with further research.


B.
Follow-Up Activity
By completing and
knowing the potential of renewable energy sources through HOMER Pro, we know
how much energy can be generated. We also conduct verification through MathLab
based on data from the Central Statistics Agency (BPS) to compare the energy
that might be generated based on data from BPS with the energy determined by
Homer.

Then after we find
out that the use of solar and wind renewable energy (EBT) plants can be used,
we conduct further studies and research on generation with the potential of
other renewable energy sources such as water. After seeing the potential of
water from the Bappeda data, further research will be conducted to look for the
most possible regional potential for an off-grid hybrid power plant.

IV. Conclusion
Based on the results of the analysis already described,
there are some important things that will be elaborated as follows,

1. The resulting solar radiation is 4.745 kWh / m2
/ day and the average temperature of the data is 24.63 0C, so the
construction of an off grid generator with solar energy allows.


2. The resulting wind speed is 3.35m/s, thus enabling the construction of wind
energy plants.


3. With solar radiation and the resulting wind
speed it is possible to build PV-wind
plants


References
[1] M. N. Hidayat and F. Li,
“Implementation of Renewable Energy Sources for Electricity Generation in
Indonesia,” in 2011 IEEE, 2011.

[2] S. Mishra, H. Koduvere, Dr. I.
Palu, Dr. R. Kuhi-Thalfeldt, “Modelling of Solar-Wind Hybrid Renewable Energy
System Architecture,” in 2016 IEEE, 2016.

[3] A. P. Kumar, “Analysis of Hybrid
Systems: Software Tools,” in 2016 International Conference on Advances in
Electrical, Electronics, Information, Communication and Bio-Informatics
(AEEICB16), 2016.

[4] D.K. Yadav, S. P. Girimanji, T.
S. Bhatti, “Optimal Hybrid Power System Design Using HOMER,” in 2012 IEEE, 2012

[5] K. Salovaara, S. Honkapuro, M.
Makkonen, and O. Gore, “100% Renewable Energy System - Challenge and
Opportunities for Electricity Market Design” in Neo-Carbon Energy Project,
2016.

[6] A. Banshwar, N. Kr. Sharma, Y. R. Sood,
“Optimal Approach for Efficient Utilization of Renewable Energy Sources in
Power System,” in 2016 IEEE Students’ Conference on Electrical, Electronics and
Computer Science, 2016.

[7] A. Das, and Shabbirudidin,
“Renewable Energy Source Selection Using Analytical Hierarchy Process and
Quality Function Deployment: A Case Study,” in 2016 Second International
Conference On Science Technology Engineering and Management (ICONSTEM), 2016.

[8] A. Kumar, M. Zaman, N. Goel, N.
Goel, and R. Church, “In Search of An Optimization Tool for Renewable Energy
Resources: Homer vs. In-House Model,” in 2013 IEE Electrical Power & Energy
Conference (EPEC), 2013.

[9] A. Banshwar, N. Kr. Sharma, Y.
R. Sood, “Optimal Approach for Efficient Utilization of Renewable Energy
Sources in Power System,” in 2016 IEEE Students’ Conference on Electrical,
Electronics and Computer Science, 2016.

[10] Oktaviani, Khoiria. 2018.
Dorong Elektrifikasi, Papua Jadi Prioritas Program LTSHE.

[11] BPS. 2014. Data Asmat_Podes
2014 (BPS)_ . (16 Oktober 2018)

[12] Huld, Thomas. “Estimating Solar
Radiation and Photovoltaic System Performance, the PVGIS Approach,” in 2011
AFRETEP 1st Regional Workshop Kempala, Ugenda , 2018.
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