Rendy Adhi Rachmanto
| Wibawa Endra Juwana | Anugrah Akbar | Singgih Dwi Prasetyo | Watuhumalang Bhre Bangun | Zainal Arifin*
© 2023 IIETA. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
The increasing demand for electrical energy is causing conventional energy supplies to become insufficient, leading to power outages especially in remote areas. Additionally, the reliance on fossil fuels for energy contributes to global warming. There is a pressing need for additional renewable energy sources to meet these energy needs. Hybrid Energy Systems (HES), which combine two or more energy sources, offer a promising solution. This study aims to analyze a PV-generator hybrid system connected to the grid in several cities in East Nusa Tenggara. The hybrid system configurations are modeled using the Hybrid Optimization Model for Electric Renewable (HOMER) software. Simulation results indicate that the performance varies across cities due to environmental parameters. Among the cities studied, Alor demonstrated the highest efficiency and best energy production according to economic analysis and energy output data.
energy, HES, on grid PV-wind turbine, HOMER, NPC
The growth of the human population, along with technological advancements and increasingly modern lifestyles, is driving up energy demand [1]. In Indonesia, energy needs continue to rise year by year. Conventional energy supplies, such as steam and diesel power plants, are becoming more necessary than ever. However, in some areas, particularly the most remote rural areas of Indonesia, electricity is still lacking, and power outages frequently occur due to insufficient electricity generation [2]. This highlights the need for a more efficient energy source to meet the increasing demand. Conventional power plants still rely on finite fossil fuels such as coal, gas, and oil, which emit significant greenhouse gases and contribute to global warming [3]. If this reliance on fossil fuels continues, it is predicted that the world will face severe disasters in the coming decades [4-6].
Renewable energy, obtained from naturally replenishing resources such as solar, wind, water, geothermal energy, and biomass, is seen as the right solution [7]. Being located near the equator, Indonesia has enormous potential for solar energy, which is a virtually infinite renewable energy source with minimal emissions [8]. Photovoltaic (PV) solar panels, which convert sunlight into electricity, could be particularly effective in areas of Indonesia that have many sunlit days, such as East Nusa Tenggara and Papua [9, 10].
Indonesia is in the form of an archipelago that stretches or extends. Expanding the national electricity network is challenging and has many problems. Therefore, renewable energy hybrid systems must be considered and developed significantly to compensate for the shortage of energy generated by power plants, especially in the outermost rural areas. In areas with a shortage of electricity, power outages often occur. Renewable resources are sometimes fluctuating and limited, making them less reliable because they are affected by natural conditions. This can be overcome by utilizing a Hybrid Energy Systems (HES) system [11].
Hybrid Energy Systems (HES) integrate two or more energy sources to satisfy electrical needs more efficiently and effectively than a single power source [12]. On a global scale, the primary role of HES is to ensure maximum energy production while maintaining service quality [13]. Environmentally, HESs can reduce greenhouse gas emissions by encouraging the use of renewable energy sources [14]. Furthermore, it has been demonstrated that HESs can effectively lower the overall life cycle cost of standalone systems in various scenarios, while also improving the reliability of electricity supply [15]. Energy management is a critical aspect of HES as it significantly influences the system's performance [16]. Improper configuration and management can cause the system to operate outside of safe parameters [17]. On-grid hybrid power generation systems have been widely implemented in numerous countries, particularly for smart cities [18]. Techno-economic analysis has validated the feasibility of implementing standalone, grid-connected hybrid energy systems. Furthermore, optimizing the size of each component can help to reduce system costs [19].
The main power plants in Indonesia use coal as the primary network [20], supplemented by renewable energy sources such as solar energy with photovoltaic technology. Diesel generators are also employed, and due to their lower emissions compared to coal, the government has allocated more subsidies for imported diesel [21]. These generators serve as a backup during power outages in the main network, ensuring uninterrupted energy supply.
The Hybrid Optimization Model for Electric Renewables (HOMER) software can be utilized to model these HES configurations [22]. HOMER can model hybrid systems from technological, economic, and environmental perspectives [23], simulating the performance of HES systems daily over the year based on energy supply sources and lifecycle costs [24]. This study aims to model the potential use of solar energy HES systems with photovoltaic-diesel generator technology connected to the grid in the outermost areas of Indonesia using HOMER software.
2.1 Regional selection
NTT, or East Nusa Tenggara, is a province in Indonesia that is located east of the islands of Java and Bali. Geographically, NTT is between 7°08'-11°13' South Latitude and 116°33'-124°28' East Longitude. NTT is located around the equator, so the availability of sunlight throughout the year solar energy can be used as a substitute for conventional energy which is starting to be limited, and the price is relatively high. The electrification ratio value in East Nusa Tenggara is quite low, at 21.34%, due to the region consisting of small islands with limited access and infrastructure [25]. The potential for solar energy in NTT is 6.07 kWh/m2, causing NTT to have the potential to utilize solar energy as a source of electrical energy [26]. It also has a large enough area with sufficient land to build solar panel installations. Limited and quite expensive conventional energy requires additional energy based on renewable energy with the HES system.
2.2 Model description
This research was carried out by modeling a Photovoltaic-Generator system connected to the network in several regions in NTT, namely Alor, East Sumba, Manggarai, Kupang, and Nagekeo for technological-economic analysis. This system is modeled with HOMER software.
HOMER software performs modeling and analyzes the techno-economic feasibility of the proposed HES configuration system [27]. Parameters considered in HOMER simulation modelling include profile loads, energy sources, technical and economic components, and location determination. Figure 1 below is the HOMER simulation framework that was carried out. A schematic diagram of the proposed HES system configuration is shown in Figure 2.
Figure 1. HOMER simulation framework
Figure 2. Schematic configuration of the on-grid PV-generator hybrid system
The average consumption load was obtained for each region in East Nusa Tenggara, assuming the average usage in Indonesia was 11.26 kWh/day, with the maximum load being 2.09 kW. The estimated electrical load profile is validated by Homer software is shown in Figure 3. This electricity consumption expense is calculated for each month [28]. The network input parameters include electricity prices and network selling prices, which are set by the central government. The selling price set by the government is Rp 911.00 while the price of network electricity is Rp 1,500.00 [29].
A grid-connected PV-Generator Hybrid System requires several critical components to establish the best design and cost. The main components of the hybrid system are connected to the PV circuit network, generator, and converter. Table 1 shows the types and specifications of the components of this system.
Figure 3. Estimated electric load profile in East Nusa Tenggara
Table 1. System components [3]
|
Parameter |
Capital Cost |
Replacement Cost |
O&M (Years) |
Life Span (Years) |
|
PV flat plates |
Rp 9,840,188.00 |
Rp 9,840,188.00 |
Rp 149,320.00 |
25 |
|
Generic Converter |
Rp 8,434,800.00 |
Rp 8,434,800.00 |
Rp 140,580.00 |
20 |
|
Generic Generator |
Rp 7,425,500.00 |
Rp 7,425,500.00 |
Rp 3,810,240.00 |
15 |
2.3 Environmental parameters
Environmental parameters are factors that influence environmental conditions in an area to determine the renewable energy potential of that area. In order to assess the renewable energy potential of the East Nusa Tenggara region and identify areas with a comparative advantage, various environmental parameters have been considered. These parameters include solar irradiance, and temperature. By analyzing and comparing these parameters, it is possible to identify specific areas within the region that have a higher potential for harnessing renewable energy resources. This information will assist in directing future energy planning and development strategies, as well as ensuring the optimal utilization of hybrid energy systems from renewable energy sources in East Nusa Tenggara. Data on environmental temperature and solar radiation in several areas in East Nusa Tenggara were obtained from NASA predictions of worldwide energy resources, which can be obtained from the resources feature in design HOMER. This data is needed to determine the energy potential characteristics of each region from environmental parameters.
Figure 4. Average ambient temperature in east Nusa Tenggara
Figure 5. The average intensity of solar radiation in east Nusa Tenggara
Figure 4 shows the average monthly temperature data in several areas that are the research subject in East Nusa Tenggara Province. From the figure, it can be seen that the highest average temperature is in the city of Alor in November at 28.880℃. Figure 5 shows the average intensity of solar radiation each month in East Nusa Tenggara. It can be seen that the highest average intensity of solar radiation is in the city of Alor, also in October, at 7.61 kWh/m2. Photovoltaic systems use solar cell technology to convert photons in sunlight directly into electricity [30]. From these environmental parameters, it can be concluded that the city of Alor is a city that has the best potential compared to others to become the initial place for installing a hybrid PV-generator system with an on-grid system.
2.4 Economic analysis
Economic analysis in HOMER refers to the process of evaluating the financial aspects of hybrid renewable energy systems using the HOMER software. In the context of HOMER, economic analysis involves considering parameters such as capital costs, operating and maintenance expenses, fuel costs, equipment lifetimes, nominal discount rate, the anticipated inflation rate, and the project's lifespan. These parameters are inputted into the software to simulate and optimize the energy system's design and operation.
Figure 6. Economic data
Overall, economic analysis in HOMER Pro plays a crucial role in guiding decision-making processes by providing insights into the economic feasibility, cost-effectiveness, and financial performance of hybrid renewable energy systems. It helps stakeholders, policymakers, and investors make informed decisions and optimize the design and operation of sustainable energy. Figure 6 displays the economic data required for this study in several East Nusa Tenggara areas.
The simulation results from the HOMER application have an output in the form of economic analysis. The cost of the system is determined through the cost of capital owned (Rp), component replacement costs (Rp), and operation & maintenance costs (Rp/year).
2.4.1 Net present cost (NPC)
The present value of all costs incurred during a system's lifetime, less the present value of all revenue received over the same lifetime, is the system's total net present cost (NPC). The cost includes fuel prices, environmental penalties, operating and maintenance expenses, capital expenditures, replacement costs, and grid energy costs. Two sources of income are residual value and money made from selling power to the grid. The cumulative discounted cash flows for each year of the project life cycle are added to determine the total NPC [3].
The total net present cost (NPC) is calculated using Eq. (1) below.
$N P C(R p)=\frac{T A C}{C R F}$ (1)
TAC is the total annual cost, and CRF is the payback factor. The capital recovery factor is the ratio used to determine the annual present value (a series of equal annual cash flows) calculated using Eq. (2).
$C R F(R p)=\frac{i(1+i)^N}{\left[(1+i)^N-1\right]}$ (2)
i is the range of genuine annual interest (%) and N is the number of years.
2.4.2 Cost of Energy (CoE)
The system may employ the Levelised Cost of Energy (CoE), which is the average cost per kWh of electrical energy that can be determined using the HOMER program. The cost of electricity (CoE) is calculated by dividing the yearly cost of producing electricity by the total cost of consuming the thermal load. Eq. (3) is used to determine CoE.
$\operatorname{COE}(R p / k W h)=\frac{C_{\text {tot.ann }}}{E}$ (3)
2.4.3 Salvage value
Salvage value is the value of the generating system components that can still be used at the end of the project's life. The HOMER software uses the following equation to determine the value of each component after the project's life ends. The salvage value can be calculated by Eq. (4).
$S=C_{r e p} \frac{R_{r e m}}{R_{\text {comp }}}$ (4)
S is the residual value, Rrem is the component life remaining, and Rrem is the component life.
2.4.4 Internal rate of return (IRR)
The discount rate at which net cash balances the base case system and the optimized system is the internal rate of return (IRR). The present value of the difference between two cash flow sequences divided by the discount rate yields the IRR.
2.4.5 Return on investment (ROI)
The yearly cost reductions over the original investment are known as return on investment (ROI). ROI may be computed by subtracting the yearly average difference in nominal cash flows throughout the project from the difference in the cost of capital. Eq. (5) may be used to determine the return on investment.
$R O I=\frac{\sum_{i=0}^{R_{\text {proj }}} C_{i, r e f}\quad-C_i}{R_{\text {proj }}\quad\left(C_{\text {cap }}-C_{\text {cap }, \text { ref }}\quad\right)}$ (5)
Ci,ref is the nominal annual cash flow for the base system (reference), Ci is the nominal annual cash flow for the current system, Rproj is the project life in years, Ccap is the cost of capital of the current system, and Ccap,ref is the cost of capital of the base system (reference).
2.4.6 Simple payback
Simple Payback is the period of time needed for the cumulative cash flow difference between the reference and the optimized case system to become positive. The amount of time needed to recoup the difference in investment expenses between the optimized case system and the base case system is known as the payback period [3].
After the Hybrid Energy System (HES) Photovoltaic (PV)-Generator connected to the grid is assembled in the HOMER software, the obtained environmental parameters are simulated to generate the economic analysis of the system. This configuration consists of PV, generator, converter, and grid components. An overview of the proposed system configuration is depicted in Figure 7.
Figure 8 shows the outcomes of the simulation that was run. Figure 8 compares cost recovery statistics from each location over the last year. The profits realized are increased by a high rate of return on capital. Apart from environmental factors that might alter throughout the year, this profit margin determines the most advantageous site [29]. Each region exhibits distinct outcomes in the simulation of hybrid energy systems. This disparity arises from the diverse potential for energy source development in each respective area. Within this study, the potential of each region is illustrated by employing environmental parameters encompassing varying temperatures and average solar radiation intensity. In comparison to other cities, the Alor region has the potential for highly rapid economic expansion, according to the simulation findings. The city of Alor is an excellent choice for this study because of its economic potential. The city's environmental parameters, which include varied temperatures and the most significant average solar radiation intensity, are also highly favorable. The lowest overall NPC value among the other regions Rp 84,593,072.71 indicates this. A low NPC number means the suggested system configuration is the most effective and should be used [31]. The total NPC values in the Alor area and their details are shown in Table 2.
Figure 7. The proposed hybrid system configuration
Figure 8. The proposed HES PV-Gen sequence
Based on the Total NPC in Table 2, the total system cost is Rp 84,593,072.71. The COE value obtained for buying energy per kWh is Rp 1,443.00. This shows it is cheaper than grid electricity sold at an energy price per kWh of Rp 1,500.00 [32]. The system financing flow over 25 years is shown in Figure 9. The financing flow depends on each component's capital, replacement, salvage, operational, and fuel values.
For the resilience and reliability of this system, each component has a lifespan and requires maintenance to ensure optimal performance. The estimated lifespan of 25 years is based on the average working life of solar panels that can work optimally. To reach 25 years of age, it requires some maintenance and replacement of components as shown in Table 2. The generator component is only used for emergencies when there is a network power outage at night due to high fuel costs. In addition, you still need to pay network electricity costs because this system uses a network-connected system. Based on Figure 8 in the city of Alor, the return on investment in this system is 7.2 years.
Table 2. Total value of NPCs in Alor
|
Components |
Capital |
Replacement |
O&M |
Salvage |
Total |
|
PV |
Rp 12,129,895.00 |
Rp 3,867,099.82 |
Rp 2,379,505.67 |
Rp 2,179,358.75 |
Rp 16,197,142.17 |
|
Grids |
0 |
0 |
Rp 43,162,076.99 |
0 |
Rp 43,162,076.99 |
|
Generator |
Rp 17,078,650.00 |
0 |
0 |
Rp 3,989,041.56 |
Rp 13,089,608.44 |
|
System Converter |
Rp 6,136,192.66 |
Rp 5,420,943.48 |
Rp 1,322,095.54 |
Rp 734,986.56 |
Rp 12,144,245.12 |
|
System |
Rp 35,344,738.09 |
Rp 9,288,043.30 |
Rp 46,863,678.19 |
Rp 6,903,386.87 |
Rp 84,593,072.71 |
Figure 9. System financing flows for 25 years
The HOMER simulation results also analyze the power generated by each energy source. The average monthly electricity production from this system is shown in Figure 10. This figure shows that the electricity generated by the grid is greater than that of PV panels. For generators only for emergencies when there is a power outage, it is assumed that they will not work because of the high fuel cost, making it inefficient to use regularly. The total electrical energy generated per year is 4.85 kWh. From annual electricity production, PV panels have a percentage of 48.9% in meeting electricity needs. At the same time, the grid electricity source plays a role of 51.1% in generating electrical energy. Hence, producing electricity sources from solar and grid electricity is almost balanced. Electricity production and its percentages are shown in Table 3.
The environmental impact of using a hybrid energy system with an on-grid photovoltaic generator is the ability to reduce air emissions compared to conventional grid systems. This can be observed in Table 4, where simulation results show a significant reduction in air emissions, specifically Carbon Dioxide, Sulfur Dioxide, and Nitrogen Oxides, by 65% compared to conventional grid systems.
Table 3. Electrical energy production and annual percentage
|
Components |
Production (kWh/year) |
Percentage (%) |
|
PV |
2.37 |
48.9 |
|
GRID |
2,481 |
51.1 |
|
Total |
4.85 |
100 |
Table 4. Emission comparison
|
Emission |
HES On-Grid PV-Gen |
Conventionl Grid System |
|
Carbon Dioxide |
1,568 |
2,597 |
|
Sulfur Dioxide |
6.8 |
11.3 |
|
Nitrogen Oxides |
3.32 |
5.51 |
Figure 10. Average monthly electricity production
This study compares PV-Generator hybrid on-grid systems in several cities in the Province of East Nusa Tenggara (NTT), namely Alor, East Sumba, Manggarai, Kupang, and Nagekeo. NTT is the outermost area that has a problem with a shortage of electrical energy needs. Geographically, NTT has the potential to develop renewable energy sources with hybrid systems. Based on the results of simulation modeling using HOMER software under the same load conditions, the PV-Generator hybrid configuration system in each city shows different results. The City of Alor shows the most efficient yield potential for the PV-generator hybrid system because it has favorable environmental parameters. This is indicated by a high return on investment value and the lowest total Net Present Cost (NPC) condition, with a payback period for this system around 7.2 years.
This research was fully supported by the PNBP grant from the Universitas Sebelas Maret, Indonesia, with contract number 228/UN27.22/PT.01.03/2023 of the Hibah Riset Grup Penelitian scheme.
[1] Muzayanah, I.F.U., Lean, H.H., Hartono, D., Indraswari, K.D., Partama, R. (2022). Population density and energy consumption: A study in Indonesian provinces. Heliyon, 8(9): E10634. https://doi.org/10.1016/j.heliyon.2022.e10634
[2] Hertadi, C.D.P., Sulaiman, M., Anwar, P.G.P. (2022). Kajian industri energi terbarukan tenaga listrik di Indonesia berdasarkan arah kebijakan dan potensi alam. G-Tech: Jurnal Teknologi Terapan, 6(2): 276-283. https://doi.org/10.33379/gtech.v6i2.1690
[3] Riayatsyah, T.M.I., Geumpana, T.A., Fattah, I.M.R., Rizal, S., Mahlia, T.M.I. (2022). Techno-economic analysis and optimisation of campus grid-connected hybrid renewable energy system using homer grid. Sustainability, 14(13): 7735. https://doi.org/10.3390/su14137735
[4] Johnson, L. (2014). Geographies of securitized catastrophe risk and the implications of climate change. Economic Geography, 90(2): 155-185. https://doi.org/10.1111/ecge.12048
[5] Prasetyo, S.D., Prabowo, A.R., Arifin, Z. (2023). The use of a hybrid photovoltaic/thermal (PV/T) collector system as a sustainable energy-harvest instrument in urban technology. Heliyon, 9(2): e13390. https://doi.org/10.1016/j.heliyon.2023.e13390
[6] Prasetyo, S.D., Prabowo, A.R., Arifin, Z. (2022). The effect of collector design in increasing PVT performance: Current state and milestone. Materials Today: Proceedings, 63: S1-S9. https://doi.org/10.1016/j.matpr.2021.12.356
[7] Ghorbani, B., Mehrpooya, M., Sadeghzadeh, M. (2018). Developing a tri-generation system of power, heating, and freshwater (for an industrial town) by using solar flat plate collectors, multi-stage desalination unit, and Kalina power generation cycle. Energy Conversion and Management, 165: 113-126. https://doi.org/10.1016/j.enconman.2018.03.040
[8] Arifin, Z., Tribhuwana, B.A., Kristiawan, B., Tjahjana, D.D.D.P., Hadi, S., Rachmanto, R.A., Prasetyo, S.D., Hijriawan, M. (2022). The effect of soybean wax as a phase change material on the cooling performance of photovoltaic solar panel. International Journal of Heat and Technology, 40(1): 326-332. https://doi.org/10.18280/ijht.400139
[9] Ginley, D., Renewable, N.D., Ginley, M.A. Green, R.C. (2008). Solar energy conversion toward. MRS Bulletin, 33: 355-373. https://doi.org/10.1557/mrs2008.71
[10] Ramelan, A., Adriyanto, F., Apribowo, C.H.B., Ibrahim, M.H., Iftadi, I., Ajie, G.S. (2021). Simulation and techno-economic analysis of on-grid battery energy storage systems in Indonesia. Journal of Electrical, Electronic, Information, and Communication Technology, 3(1): 30-34. https://doi.org/10.20961/jeeict.3.1.50492
[11] Suman, G.K., Yadav, S., Roy, O.P. (2021). HOMER based optimal sizing of a PV/diesel/battery hybrid system for a laboratory facility. In 2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies, IEEE, pp. 1-5. https://doi.org/10.1109/ICEPE50861.2021.9404436
[12] Aziz, A.S., Tajuddin, M.F.N., Zidane, T.E.K., Su, C.L., Alrubaie, A.J.K., Alwazzan, M.J. (2022). Techno-economic and environmental evaluation of PV/diesel/battery hybrid energy system using improved dispatch strategy. Energy Reports, 8: 6794-6814. https://doi.org/10.1016/j.egyr.2022.05.021
[13] Madaci, B., Chenni, R., Kurt, E., Hemsas, K.E. (2016). Design and control of a stand-alone hybrid power system. International Journal of Hydrogen Energy, 41(29): 12485-12496. https://doi.org/10.1016/j.ijhydene.2016.01.117
[14] Zhou, W., Lou, C.Z., Li, Z.S., Lu, L., Yang, H.X. (2010). Current status of research on optimum sizing of stand-alone hybrid solar-wind power generation systems. Applied Energy, 87(2): 380-389. https://doi.org/10.1016/j.apenergy.2009.08.012
[15] Nema, P., Nema, R.K., Rangnekar, S. (2009). A current and future state of art development of hybrid energy system using wind and PV-solar: A review. Renewable and Sustainable Energy Reviews, 13(8): 2096-2103. https://doi.org/10.1016/j.rser.2008.10.006
[16] Hafsi, O., Abdelkhalek, O., Mekhilef, S., Soumeur, M.A., Hartani, M.A., Chakar, A. (2022). Integration of hydrogen technology and energy management comparison for DC-Microgrid including renewable energies and energy storage system. Sustainable Energy Technologies and Assessments, 52: 102121. https://doi.org/10.1016/j.seta.2022.102121
[17] Zahraoui, Y., Alhamrouni, I., Mekhilef, S., Basir Khan, M.R., Seyedmahmoudian, M., Stojcevski, A., Horan, B. (2021). Energy management system in microgrids: A comprehensive review. Sustainability, 13(19): 10492. https://doi.org/10.3390/su131910492
[18] Kazerani, M., Tehrani, K. (2020). Grid of hybrid AC/DC microgrids: A new paradigm for smart city of tomorrow. In 2020 IEEE 15th International Conference of System of Systems Engineering (SoSE), pp. 175-180. https://doi.org/10.1109/SoSE50414.2020.9130482
[19] Kanata, S., Baqaruzi, S., Muhtar, A., Prasetyawan, P., Winata, T. (2021). Optimal planning of hybrid renewable energy system using Homer in Sebesi Island, Indonesia. International Journal of Renewable Energy Research (IJRER), 11(4): 1507-1516. https://doi.org/10.20508/ijrer.v11i4.12296.g8303
[20] Al Hakim, R.R. (2020). Model energi Indonesia, tinjauan potensi energi terbarukan untuk ketahanan energi di Indonesia: Sebuah ulasan. ANDASIH Jurnal Pengabdian Kepada Masyarakat, 1(1): 1-11. https://doi.org/10.57084/andasih.v1i1.374
[21] Zhang, J.R., Meerman, H., Benders, R., Faaij, A. (2021). Techno-economic and life cycle greenhouse gas emissions assessment of liquefied natural gas supply chain in China. Energy, 224: 120049. https://doi.org/10.1016/j.energy.2021.120049
[22] Noor, V.P., Jufri, F.H., Naradhipa, A.M., Utomo, A.R. (2020). Optimization and comparative analysis for a stand-alone hybrid model of PV, wind turbine, and natural gas generator system in remote area-a case study in Belu. In IOP Conference Series: Earth and Environmental Science, IOP Publishing, 599(1): 012028. https://doi.org/10.1088/1755-1315/599/1/012028
[23] Krishan, O., Suhag, S. (2019). Techno-economic analysis of a hybrid renewable energy system for an energy poor rural community. Journal of Energy Storage, 23: 305-319. https://doi.org/10.1016/j.est.2019.04.002
[24] Türkay, B.E., Telli, A.Y. (2011). Economic analysis of standalone and grid connected hybrid energy systems. Renewable Energy, 36(7): 1931-1943. https://doi.org/10.1016/j.renene.2010.12.007
[25] Syahputra, H., Prasetyawan, I.B., Ismunarti, D.H., Adhitya, R.B. (2014). Kajian potensi arus laut sebagai energi pembangkit listrik di selat larantuka, flores timur, nusa tenggara timur. Buletin Oseanografi Marina, 3(1): 1-8. https://doi.org/10.14710/buloma.v3i1.11212
[26] Nugraha, I.M.A., Serihollo, L.G.G., Siregar, J.S.M., Desnanjaya, I.G.M.N. (2022). Kajian pemanfaatan dan ketersediaan plts sebagai sumber energi listrik pada Kapal 5 GT di Nusa Tenggara Timur. Jurnal Kelautan Nasional, 17(2): 123-130. http://dx.doi.org/10.15578/jkn.v17i2.8831
[27] Rumbayan, M., Nakanishi, Y. (2019). Prospect of PV-wind-diesel hybrid system as an alternative power supply for Miangas Island in Indonesia. International Journal of Smart Grid and Clean Energy, 8(4): 402-407. https://doi.org/10.12720/sgce.8.4.402-407
[28] Thirunavukkarasu, M., Sawle, Y. (2020). Design, analysis and optimal sizing of standalone PV/diesel/battery hybrid energy system using HOMER. In IOP Conference Series: Materials Science and Engineering, IOP Publishing, 937(1): 012034. https://doi.org/10.1088/1757-899X/937/1/012034
[29] Arifin, Z., Suyitno, S., Tjahjana, D.D.D.P., Muqoffa, M., Prasetyo, S.D., Alfaiz, N.F., Sanusi, A. (2022). Grid-connected hybrid pv-wind system simulation in Urban Java. Journal Européen des Systèmes Automatisés, 55(4): 477-483. https://doi.org/10.18280/jesa.550406
[30] Arifin, Z., Tjahjana, D.D.D.P., Hadi, S., Rachmanto, R.A., Setyohandoko, G., Sutanto, B. (2020). Numerical and experimental investigation of air cooling for photovoltaic panels using aluminum heat sinks. International Journal of Photoenergy, 2020: 1-9. https://doi.org/10.1155/2020/1574274
[31] Sadat, S.A., Faraji, J., Babaei, M., Ketabi, A. (2020). Techno-economic comparative study of hybrid microgrids in eight climate zones of Iran. Energy Science & Engineering, 8(9): 3004-3026. https://doi.org/10.1002/ese3.720
[32] Apribowo, C.H.B., Ibrahim, M.H., Purnomo, M.R.B. (2020). Design and economic analysis of floating PV-wind turbine plant for renewable energy supply in Indonesia. In AIP Conference Proceedings, AIP Publishing, 2217(1): 030191. https://doi.org/10.1063/5.0000829
