ArticlePDF Available

Effect of peak sun hour on energy productivity of solar photovoltaic power system

Authors:

Abstract and Figures

A solar cell is a type of renewable energy engineering technology that can convert photons coming from the sun to be converted into electrical energy. The amount of energy that can be converted by a solar cell is determined by the effective insolation time. Peak sun hours (PSH) are the focus of this research. This PSH analysis aims to determine the potential for solar energy obtained in geographical locations throughout the year. Geographical location and the position of the astronomical coordinates of a certain area affect PSH. Therefore, the orientation of solar panel installation, including the height, slope, and latitude of the solar panel surface needs to be considered in order to get maximum solar energy. The results of this study can be used by technicians in determining the orientation of solar panel development in an area.
Content may be subject to copyright.
Bulletin of Electrical Engineering and Informatics
Vol. 11, No. 5, October 2022, pp. 2442~2449
ISSN: 2302-9285, DOI: 10.11591/eei.v11i5.3962 2442
Journal homepage: http://beei.org
Effect of peak sun hour on energy productivity of solar
photovoltaic power system
Prisma Megantoro1, Muhammad Akbar Syahbani1, Irfan Helmi Sukmawan1, Sigit Dani Perkasa1,
Pandi Vigneshwaran2
1Faculty of Advanced Technology and Multidiscipline, Universitas Airlangga, Surabaya, Indonesia
2Department of CSE, SRM Institute of Science and Technology, Kattankulathur, India
Article Info
ABSTRACT
Article history:
Received Apr 16, 2022
Revised Jun 28, 2022
Accepted Jul 14, 2022
A solar cell is a type of renewable energy engineering technology that can
convert photons coming from the sun to be converted into electrical energy.
The amount of energy that can be converted by a solar cell is determined by
the effective insolation time. Peak sun hours (PSH) are the focus of this
research. This PSH analysis aims to determine the potential for solar energy
obtained in geographical locations throughout the year. Geographical location
and the position of the astronomical coordinates of a certain area affect PSH.
Therefore, the orientation of solar panel installation, including the height,
slope, and latitude of the solar panel surface needs to be considered in order
to get maximum solar energy. The results of this study can be used by
technicians in determining the orientation of solar panel development in an
area.
Keywords:
Orientation
Peak sun hours
Photovoltaic system
Renewable energy
This is an open access article under the CC BY-SA license.
Corresponding Author:
Prisma Megantoro
Faculty of Advanced Technology and Multidiscipline, Universitas Airlangga
St. Airlangga No. 4-6, Airlangga, Surabaya, East Java 60115, Indonesia
Email: prisma.megantoro@ftmm.unair.ac.id
1. INTRODUCTION
The application of renewable energy has begun to increase along with the high demand for
electrification and concerns about climate change. The utilization of renewable energy is also carried out in the
Universitas Airlangga. Universitas Airlangga is a study environment located in East Java with a wet tropical
climate type with coordinates at latitude 7°16'1"S and longitude 112°47'7"E. In the study environment, a
charging station for electric vehicles was built. To fulfill the necessity for electrification of the electric vehicle
charging station, this station is equipped with solar panels with a capacity of 5.4 kW. In obtaining peak sun
hours (PSH) data, output energy data is taken from Hoymiles microinverter data and is taken every 15 minutes
at time intervals of 05:30-18:30.
Solar cells utilize solar energy to be engineered into energy through the photoelectric effect [1], [2].
Materials the amount of energy that can be converted into electrical energy depends on the length of solar
irradiation and the size of the power of a solar panel (Watt peak). However, the length of time that the sun
shines cannot be said to be effective time. The optimum conversion of solar energy occurs during insolation at
the average maximum irradiation time or what is called PSH. PSH is a parameter that states the ratio of the
maximum duration of solar radiation in hours per day to the standard intensity of solar radiation which is
1 kW/m2 [3].
Basically, the solar insolation on the solar panel surface is fluctuating where the intensity increases in
the morning and decreases in the afternoon. The effective duration of solar radiation for solar panels affects
the high and low PSH. In its application, the photovoltaic semiconductor plate will receive maximum solar
Bulletin of Electr Eng & Inf ISSN: 2302-9285
Effect of peak sun hour on energy productivity of solar photovoltaic power system (Prisma Megantoro)
2443
irradiation if the direction of the incident photons is perpendicular to the surface of the solar panel
[4], [5]. Thus, PSH has a value of 3-7 hours per day depending on the geographical and astronomical location
of an area and the slope of the solar panel surface [6][10].
The main focus of this research is to analyze the actual value of PSH in Indonesia by using the location
of Universitas Airlangga, Surabaya as the analyzing point. Second, with the PSH value determined by
analyzing data from the field, it can be used to design a reliable solar photovoltaic power system in Indonesia.
Analyzing the PSH value can be used to determine the size and configuration of solar panel array needed for
the system. In addition, it can also be used to predict and optimize energy production in solar photovoltaic
power systems.
2. METHOD
2.1. Photovoltaic effect
The conversion of solar energy into electrical energy occurs in photovoltaic semiconductor materials
through a photoelectric process [11], [12].
(1)
Where is the kinetic energy needed to move free electron to generate electricity, W is the photon energy and
is the material threshold energy obtained from:
or (2)
(3)
where c is the Speed of light 󰇛󰇜. is wave length in meter. f is wave frequency (Hz).
2.2. Solar declination
The solar declination reading (δ) is obtained from the coordinates of the globe in terms of the equator
coordinates. The value of solar declination is measured by measuring the angle between the equator drawn
from the center of the earth to the center of the sun. The process of the earth around the sun on its polar axis
can form a slope of 0 - 23,45 [13].
󰇛 
 ) (4)
Where n is Julian day.
2.3. Latitude and longitude effect
The influence of the intensity of the sun is determined by the location of the area on the earth's surface
[14], [15]. The position refers to the astronomical coordinates of latitude and longitude. Figure 1 below explains
the solar path of the selected location. The solar path diagram illustrates the comparation of the azimuth to sun
height in degrees for an annual cycle. It can be used as a reference for an overview of solar resources within a
particular location.
2.4. Tilt
Solar energy can convert maximally into electrical energy if the surface of the solar panel is
perpendicular to the direction of the sun's rays (source). The orientation of the construction of solar panels must
pay attention to the position of the sun, longitude and latitude [16][18]. This is because each region based on
geographical and astronomical aspects has a different position.
 (5)
Where:
 : Optimal tilt angle
: Longitude area
: Declination angle
Figure 2 shows the tilt angle of the installed solar cell in Universitas Airlangga. The measurement of
the solar panel is conducted by applying magnetic water pass directly into the solar panel. This method can be
reassured by using (5).
ISSN: 2302-9285
Bulletin of Electr Eng & Inf, Vol. 11, No. 5, October 2022: 2442-2449
2444
Figure 1. Solar paths based on coordinate of Surabaya, East Java (PVsyst 7.2)
Figure 2. Tilt angle of solar cell in Airlangga University
2.5. Determine peak sun hour
PSH take the solar irradiation interval when energy output increases by 60% until the output decreases
by 60% [19], [20]. The process of obtaining Peak Sun Hour (PSH) value can be done by using the equation of
nominal peak power or (5). after the maximum output value is obtained, the PSH value can be determined by
substituting the peak power value into the equation.
 
 (6)
Where:
 : Nominal peak power (W)
 : Total energy demand (W)
PSH : Peak Sun Hours (hour)
 : System efficiency (%)
2.6. Irradiance factor
Solar radiation is the power per unit area received from the sun in the form of electromagnetic
radiation measured in the wavelength range of the measuring instrument [21]. Irradiation can be measured in
space or at the earth's surface after absorption and scattering of the atmosphere. Irradiation plays a role in
predicting the energy productivity of solar power plants. The distribution of irradiation levels across the Java
Archipelago is described in Figure 3, with the selected location represented in the figure as the blue mark. The
figure explains the irradiation factor within a color range from yellow as lower to orange as the higher value.
Bulletin of Electr Eng & Inf ISSN: 2302-9285
Effect of peak sun hour on energy productivity of solar photovoltaic power system (Prisma Megantoro)
2445
Figure 3. Solar map in Java Archipelago (map solar irradiance on data of year 2021, ENERGYDATA.INFO)
3. RESULTS AND DISCUSSION
In this section will explain the PSH analysis of solar cells found at Universitas Airlangga. In the
previous section, the method to get the PSH value was explained and the things that affect the PSH value such
as the photovoltaic effect, solar declination, longitude and latitude, tilt surface, and irradiance factor. Through
the described method, a graph of the PSH value will be displayed at the observation location. The installed
photovoltaic system in the observation location is equipped with a monocrystalline type solar cell which is
shown in Figure 4(a), and a panel box with a display to present solar measurement parameters, which are shown
in Figure 4(b).
(a)
Figure 4. 5.4 kWp photovoltaic power plant installation in Universitas Airlangga (a) the photovoltaic array,
and (b) the control panel
3.1. Peak sun hours analysis
The energy output produced by the solar cell shows a different amount of energy conversion every
day. The fluctuating energy output is due to the PSH factor [22]. The PSH value that is less makes the need for
solar cells increase. The location of Airlangga University, Surabaya, Indonesia, has an average PSH value of
4.5 hours/day.
Figure 5 shows the data for calculating the PSH solar cell of 5.4 kWh which is calculated manually
through real-time solar power station monitoring (S-miles cloud). The value shown by the graph is the PSH
value measured at 12 hour intervals. From the graph, it can be seen that the PSH value fluctuates. This
fluctuating value is caused by weather factors that can make insolation not optimal and have an impact on low
solar irradiation values.
Figure 6 shows the results of the energy output that can be used for electrification of electricity needs.
The measurement results are obtained through real time measurements for 3 months. The results obtained, are
the results obtained from the average energy output at the PSH interval (4.5 hours) according to the PSH value
of the research results. Based on the results shown in Figures 5 and 6, there is a correlation that shows results
that are directly proportional to PSH and energy output. From the graph shown, it can be seen that the low PSH
in a period will affect the low energy output (and vice versa).
ISSN: 2302-9285
Bulletin of Electr Eng & Inf, Vol. 11, No. 5, October 2022: 2442-2449
2446
Figure 5. PSH data collection from hoymiles microconverter
Figure 6. Energy output based on PSH data
Figure 7 shows the results of the power output starting from sunrise to sunset. The power output shown
every hour is the result of the average power output for 3 months. The first red line showed in the Figure 7 (the
left one) is the time of PSH start point, which more than 60% of the peak power is reached. Besides, the second
red line (the right one) is the time when PSH is ended. This means the power decrease into less than 60% of
peak power. Based on this average value, the PSH zone can be determined, namely in the graph area bounded
by the red line. The PSH solar cells are at intervals from 09:30 to 14:00 (4.5 hours). This PSH value will be
used to determine the optimal hour for converting solar energy into electrical energy.
Figure 7. Energy output based on PSH data
Bulletin of Electr Eng & Inf ISSN: 2302-9285
Effect of peak sun hour on energy productivity of solar photovoltaic power system (Prisma Megantoro)
2447
3.2. Energy output from solar cell
The on grid solar cell photovoltaic installed in the Airlangga University study area has a capacity of
5.4 kWh a 24 Volt system. The normalized energy, performance ratio, global incident in coll, and power
injected into grid values are values analyzed using PVsyst software. The orientation of the PVsyst has been
adjusted including geographical and astronomical coordinates, the slope of the solar cell surface, and solar
irradiation data for the area (Airlangga University, East Java) for one year. Thus, the PSH value and energy
output from solar panels can be analyzed regarding the relationship between analyzed from the software.
Figure 8 explains the system’s capability in producing power month-by-month in a year. The figure
shows the system’s daily useful energy referred to the nominal power and the losses that occurred. Those losses
include the collection losses that happened because of thermal, wiring, shading, or other inefficiencies [23],
[24]. Also, the system loss which in the case of the proposed method happened because of inverter
inefficiencies [25][27]. While Figure 9 shows the system’s effectiveness in producing energy if the system
continuously working.
Figure 8. Energy productivity every month
Figure 9. Monthly performance ratio
Figure 10 shows a graph that represents the photovoltaic daily production. The graph shows a
correlation between daily irradiation and system daily productivity. While Figure 11 shows the accumulations
of all energies registered by the system during the simulation period, with the instantaneous output power
injected into the grid [28][30].
Figure 10. Daily energy supply to daily irradiation
Figure 11. Power and energy supply
4. CONCLUSION
PSH is an indicator that determines the amount of energy output required in the installation of solar
panels, especially on 5.4 kWh solar panels in the Airlangga University area, Surabaya, East Java. Based on
PSH data collection using the observation method, the average PSH in the observation area was 4.5 hours. The
PSH value can produce an average energy of 3.28 kWh/day and a performance ratio value of 0.831. Thus, the
analysis of the PSH value can be a reference for technicians and renewable energy consumers in solar panel
installations.
ISSN: 2302-9285
Bulletin of Electr Eng & Inf, Vol. 11, No. 5, October 2022: 2442-2449
2448
ACKNOWLEDGEMENTS
The authors would like to thank Universitas Airlangga for providing facilities. We also thank all
colleagues and students of Electrical Engineering from the Faculty of Advance Technology and
Multidiscipline, Airlangga University for their support for this research.
REFERENCES
[1] G. H. Wang et al., “Performance characterization for bifacial photovoltaic modules,” 2019 IEEE 46th Photovoltaic Specialists
Conference (PVSC), pp. 27782780, 2019, doi: 10.1109/PVSC40753.2019.8980710.
[2] A. C. Killam, J. F. Karas, A. Augusto, and S. G. Bowden, “Monitoring of photovoltaic system performance using outdoor suns-
VOC,” Joule, vol. 5, no. 1, pp. 210227, Jan. 2021, doi: 10.1016/j.joule.2020.11.007.
[3] C. Pica, R. Munteanu, S. Pavel, and H. Beleiu, "Modeling of photovoltaic panels," 2018 International Conference and Exposition
on Electrical And Power Engineering (EPE), 2018, pp. 07690773, doi: 10.1109/ICEPE.2018.8559884.
[4] S. Yoshida, S. Ueno, N. Kataoka, H. Takakura, and T. Minemoto, “Estimation of global tilted irradiance and output energy using
meteorological data and performance of photovoltaic modules,” Solar Energy, vol. 93, pp. 9099, Jul. 2013, doi:
10.1016/j.solener.2013.04.001.
[5] C. F. Abe, J. B. Dias, G. Notton, and P. Poggi, “Computing solar irradiance and average temperature of photovoltaic modules from
the maximum power point coordinates, IEEE Journal of Photovoltaics, vol. 10, no. 2, pp. 655663, 2020, doi:
10.1109/JPHOTOV.2020.2966362.
[6] L. Tian, Y. Huang, S. Liu, S. Sun, J. Deng, and H. Zhao, “Application of photovoltaic power generation in rail transit power supply
system under the background of energy low carbon transformation,” Alexandria Engineering Journal, vol. 60, no. 6, pp. 5167
5174, 2021, doi: 10.1016/j.aej.2021.04.008.
[7] S. Jain, C. Karmann, and J. Wienold, “Behind electrochromic glazing: Assessing user’s perception of glare from the sun in a
controlled environment,” Energy and Buildings, vol. 256, p. 111738, 2022, doi: 10.1016/j.enbuild.2021.111738.
[8] N. Pichel, M. Vivar, and M. Fuentes, “Optimization study of a photovoltaic-photochemical hybrid system (SOLWAT) for meeting the
needs of electricity and clean water,” 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC)(A Joint
Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC), Jun. 2018, pp. 12221224, doi: 10.1109/PVSC.2018.8547320.
[9] O. F. Alrawi, T. Al-Siddiqi, A. Al-Muhannadi, A. Al-Siddiqi, and S. G. Al-Ghamdi, “Determining the influencing factors in the
residential rooftop solar photovoltaic systems adoption: Evidence from a survey in Qatar,” Energy Reports, vol. 8, pp. 257262,
2022, doi: 10.1016/j.egyr.2022.01.064.
[10] A. R. Jensen, I. Sifnaios, S. Furbo, and J. Dragsted, “Self-shading of two-axis tracking solar collectors: Impact of field layout,
latitude, and aperture shape,” Solar Energy, vol. 236, pp. 215224, 2022, doi: 10.1016/j.solener.2022.02.023.
[11] P. Bharadwaj and V. John, "Shading fraction based global maximum power prediction for photovoltaic energy conversion systems,"
2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th
PVSEC & 34th EU PVSEC), 2018, pp. 11631168, doi: 10.1109/PVSC.2018.8547361.
[12] P. Li, X. Gao, Z. Li, and X. Zhou, “Effect of the temperature difference between land and lake on photovoltaic power generation,”
Renewable Energy, vol. 185, pp. 8695, 2022, doi: 10.1016/j.renene.2021.12.011.
[13] N. F. B. Ibrahim, Z. Bin Abu Bakar and W. S. B. W. Ibrahim, "The feasibility study of solar PV lighting: In Universiti Teknologi
MARA Sarawak," 2016 IEEE Industrial Electronics and Applications Conference (IEACon), 2016, pp. 9296, doi:
10.1109/IEACON.2016.8067362.
[14] J.-R. Rodríguez-Ossorio, A. González-Martínez, M. de Simón-Martín, A.-M. Diez-Suárez, A. Colmenar-Santos, and E. Rosales-
Asensio, “Levelized cost of electricity for the deployment of solar photovoltaic plants: The region of León (Spain) as case study,”
Energy Reports, vol. 7, pp. 199203, 2021, doi: 10.1016/j.egyr.2021.06.034.
[15] E. Ndzibah, G. A. Pinilla-De La Cruz, and A. Shamsuzzoha, “Collaboration towards value creation for end-of-life solar photovoltaic
panel in Ghana,” Journal of Cleaner Production, vol. 333, p. 129969, 2022, doi: 10.1016/j.jclepro.2021.129969.
[16] C. Stanciu and D. Stanciu, “Optimum tilt angle for flat plate collectors all over the world-a declination dependence formula and
comparisons of three solar radiation models, Energy Conversion and Management, vol. 81, pp. 133143, 2014, doi:
10.1016/j.enconman.2014.02.016.
[17] Z. Wang, H. Zhang, B. Dou, G. Zhang, and W. Wu, “Theoretical and experimental evaluation on the electrical properties of multi-
junction solar cells in a reflective concentration photovoltaic system,” Energy Reports, vol. 8, pp. 820831, 2022, doi:
10.1016/j.egyr.2021.12.018.
[18] N N. Ramli and S. Walker, "Pan-global, annualized determination of solar collector optimum tilt angle," 2015 7th International
Conference on Modelling, Identification and Control (ICMIC), 2015, pp. 14, doi: 10.1109/ICMIC.2015.7409455.
[19] U. Y. Tito, L. Quispe-Huaman, and O. -A. Vilca-Huayta, "Evaluation of the peak-sun hour on a tilted surface in the City of Juliaca,"
2020 IEEE XXVII International Conference on Electronics, Electrical Engineering and Computing (INTERCON), 2020, pp. 14,
doi: 10.1109/INTERCON50315.2020.9220191.
[20] D. H. W. Li and T. N. T. Lam, “Determining the optimum tilt angle and orientation for solar energy collection based on measured
solar radiance data,” International Journal of Photoenergy, vol. 2007, 2007, doi: 10.1155/2007/85402.
[21] G. Etxegarai, A. López, N. Aginako, and F. Rodríguez, “An analysis of different deep learning neural networks for intra-hour solar
irradiation forecasting to compute solar photovoltaic generators’ energy production,” Energy for Sustainable Development, vol. 68,
pp. 117, 2022, doi: 10.1016/j.esd.2022.02.002.
[22] L. L. Li, S. Y. Wen, M. L. Tseng, and C. S. Wang, “Renewable energy prediction: A novel short-term prediction model of
photovoltaic output power,” Journal of Cleaner Production, vol. 228, pp. 359375, 2019, doi: 10.1016/j.jclepro.2019.04.331.
[23] C. J. Smith, P. M. Forster, and R. Crook, “Global analysis of photovoltaic energy output enhanced by phase change material
cooling,” Applied energy, vol. 126, pp. 2128, 2014, doi: 10.1016/j.apenergy.2014.03.083.
[24] M. Alam, K. Kumar, J. Srivastava, and V. Dutta, "A study on DC microgrids voltages based on photovoltaic and fuel cell power
generators," 2018 7th International Conference on Renewable Energy Research and Applications (ICRERA), 2018, pp. 643648,
doi: 10.1109/ICRERA.2018.8566854.
[25] Y. Liu, "Research of automatic monitoring and control strategy of photovoltaic power generation system," 2018 International
Conference on Virtual Reality and Intelligent Systems (ICVRIS), 2018, pp. 343347, doi: 10.1109/ICVRIS.2018.00090.
[26] C. A. Saleel, “Forecasting the energy output from a combined cycle thermal power plant using deep learning models,” Case Studies
in Thermal Engineering, vol. 28, p. 101693, 2021, doi: 10.1016/j.csite.2021.101693.
Bulletin of Electr Eng & Inf ISSN: 2302-9285
Effect of peak sun hour on energy productivity of solar photovoltaic power system (Prisma Megantoro)
2449
[27] S. M. Aarakit, J. M. Ntayi, F. Wasswa, M. S. Adaramola, and V. F. Ssennono, “Adoption of solar photovoltaic systems in households:
evidence from Uganda,” Journal of Cleaner Production, vol. 329, p. 129619, 2021, doi: 10.1016/j.jclepro.2021.129619.
[28] S. P. Koko, “Optimal battery sizing for a grid-tied solar photovoltaic system supplying a residential load: A case study under South
African solar irradiance,” Energy Reports, vol. 8, pp. 410418, 2022, doi: 10.1016/j.egyr.2022.02.183.
[29] Y. Cao, A. Sha, Z. Liu, J. Li, and W. Jiang, “Energy output of piezoelectric transducers and pavements under simulated traffic
load,” Journal of Cleaner Production, vol. 279, p. 123508, 2021, doi: 10.1016/j.jclepro.2020.123508.
[30] G. G. Dranka, P. Ferreira, and A. I. F. Vaz, “Integrating supply and demand-side management in renewable-based energy systems,”
Energy, vol. 232, p. 120978, 2021, doi: 10.1016/j.energy.2021.120978.
BIOGRAPHIES OF AUTHORS
Prisma Megantoro is a lecturer in Electrical Engineering, School of Advanced
Technology, and Multidiscipline, Universitas Airlangga since 2020. He received a bachelor's
degree and master's degree from Universitas Gadjah Mada, Yogyakarta, Indonesia in 2014
and 2018. His current research is focused on solar photovoltaic technology, embedded
system, and the internet of things. He can be contacted at email:
prisma.megantoro@ftmm.unair.ac.id.
Muhammad Akbar Syahbani was born in Nusa Tenggara Barat, Indonesia in
2001, after graduating from high school he continued his studies in electrical engineering at
the Universitas Airlangga in 2020. Now he is active in reseach on reneawable energy in
Universitas Airlangga Research Community. He can be contacted at email:
muhammad.akbar.syahbani-2020@ftmm.unair.ac.id.
Irfan Helmi Sukmawan was born in East Java, Indonesia in 2001. He has
completed his high school education and continued his study of electrical engineering at
Airlangga University in 2020. Now he is active in renewable energy research in the
Airlangga University research community. He can be contacted at email: irfan.helmi.f-
2020@ftmm.unair.ac.id.
Sigit Dani Perkasa was born in Surabaya, Indonesia in 2002. He is a second
year Electrical Engineering student at Universitas Airlangga. He is active in the
Instrumentation Research Group. He is also a member of Research and Development
division in Universitas Airlangga's Robotic Community and participating in the Indonesian
Soccer Robot Contest. He can be contacted at email: sigit.dani.perkasa-
2020@ftmm.unair.ac.id.
Pandi Vigneshwaran has obtained his Doctoral Degree in Anna University
Chennai during 2016 and Master of Engineering under Anna University Chennai during
June 2005. He is having 18.4 years of experience and specialization in Cybersecurity.
Presently, He is working as Associate Professor in SRM Institute of Science and
Technology, Chennai. His area of interest includes security, routing, and intelligent data
analysis. He can be contacted at email: vigenesp@srmist.edu.in.
... In PV installations, the irradiation level indicates a good level for PV energy output. In addition, the Peak Sun Hours (PSH) or the optimum insolation level of the area is at 4.5 hours-5 hours [20]. Figure 5 describes the distribution of the points where solar irradiation data is collected. ...
... Gili Iyang island map (Google Earth)030006-220.9%, so based on 2011 data from the LAPAN (Indonesia space research institute), Gili I is the area with the secondbest oxygen quality in the world. ...
... GHI is essential for a photovoltaic system [13]. Peak Solar Hours (PSH) significantly influence electricity production, but geographic location, astronomical coordinates, and panel orientation also affect PSH [14]. Observe the PSH during the initial five hours, specifically from 09:00 to 14:00 UTC+7. ...
Article
Full-text available
On the northern coast of Java, some fishermen catch the blue swimming crab (BSC) for more than one day, which risks damaging the BSC; therefore, the fishermen will perform the initial steps of steaming and cold storage on the boat. As an alternative initial process, fishermen can use electrical devices for BSC processing by converting solar energy into electrical energy using a solar power plant (PLTS). We have designed an off-grid PLTS for the initial processing of BSC and lighting. This research aims to determine the performance ratio (PR) of the off-grid PLTS for the initial processing of the BSC compared to simulations using PVsyst software. The method used was qualitative, testing the off-grid PLTS on a boat in Rembang and comparing the PR with the simulation results from the PVsyst software. The off-grid PLTS system exhibited a PR of 0.379, whereas the simulation result was 0.710. The economic analysis indicated that the off-grid PLTS system cost for every kilowatt-hour (kWh) of electricity generated by the PLTS system is IDR 19,497,90. The testing results of the off-grid PLTS system showed low PR, but we hope fishermen can use this system for the initial handling of BSC on the boats.
... Based on this requirement, a capacity of 2.2 kWp is chosen for the photovoltaic (PV) system. This site can generate 9.9 kWh/day, assuming 4.5 peak sun hours per day [13]. ...
Article
Full-text available
Solar-powered pumping systems are an alternative to providing a sustainable and independent water source. This system declines the dependency on fossil fuels, which generate no greenhouse gas emissions while operating. This paper presents the design, implementation, and performance testing of a solar-powered submersible water pump in Bumi Harapan and Bukit Raya Village to provide a supplementary water source for residents. To meet the daily water supply requirement of 10 m3 in two identical water towers, a 1.1 kW rated power water pump and a 2.2 kW photovoltaic system are chosen. A solar pump controller with the ability to switch power sources from photovoltaic to grid is used in the system to maintain a consistent water supply if needed. Based on performance simulations using PVSyst software, the designed systems cannot fulfill daily water requirements. However, they are expected to fill both water towers with a daily average supply of 5.78 m3 for the Bumi Harapan site and 9.23 m3 for the Bukit Raya site. These inabilities occurred because the pumps must operate with an elevation head that is more remarkable than the specifications. Performance tests using a solar power meter (SPM) and power quality analyzer (PQA) showed that the electric submersible pump (ESP) will supply water with a flow rate that depends on solar irradiance. Based on the data collection, the ESP successfully operates near its rated capacity during the peak sun hour.
... The results indicate that the highest power conversion efficiency (PCE) is associated with AM1.5G, while AM0 performances are the least favorable for all X-sun concentrations. These findings align well with reported literature, such as the work by Wang et al. [54], who investigated electrical properties in high-concentration photovoltaic systems. Similarly, Abu Kowsar et al. [55]and Outes et al. [56]explored the impact of material band gap energy, X-sun concentration, and surface recombination velocity on multijunction solar cells, showing efficiency improvements with increased concentration. ...
Chapter
This book chapter presents a thorough investigation into the integration of nanomaterials, specifically quantum wells (QWs), within the active region of intermediate band solar cells (IBSCs) based on III-Nitride (III-N) materials. The central focus is on harnessing the distinctive properties of QWs to establish intermediate bands, with the overarching goal of improving optical absorption and subsequently enhancing photovoltaic conversion efficiency. The exploration delves into the complex interplay of various factors, including the thickness and mole fraction of indium ternary alloys (InGaN) as the absorber material, and their impact on optical absorption, refractive index change, and key solar cell characteristics. Through meticulous examination at the nanoscale, the chapter elucidates the influence of these physical and chemical parameters on open-circuit current, current density, and overall solar cell performance. Furthermore, this work not only contributes to the advancement of our understanding of III-N-based solar cells but also provides crucial insights essential for optimizing their efficiency in the context of next-generation photovoltaic technologies. The chapter concludes by offering significant recommendations aimed at further refining the IBSC technology. These recommendations serve as valuable guidelines for future research and development endeavors, fostering the continuous improvement of IBSCs and their potential role in sustainable and efficient solar energy solutions.
... The main focus of this research is to predict the PV output at low solar irradiance level. There are many factors that cause the low level of irradiation, some of them are shading and weather [18]- [20]. Low irradiation level impacts the output of PV as the electromagnetic radiation on the surface of the PV Array is not optimal [21], [22]. ...
Article
Full-text available
Solar Power Plant is a photovoltaic system to convert electromagnetic energy from sunlight into electrical energy. This solar power plant is one of the recommended solutions for fulfilling electricity needs in remote rural areas where the PLN electricity network does not enter and has abundant sunlight and fuel is difficult to obtain. Based on data from the Global Solar Atlas, Lembung Mangrove Ecotourism, Galis, Pamekasan Regency has a sunlight potential of 4,603 kWh/m² per day. Therefore, it is unfortunate if this potential is not optimally utilised to build an off-grid solar power plant. The purpose of the research is to assess the feasibility of installing PLTS in Lembung Mangrove Ecotourism in terms of technical, economic, and investment feasibility analysis. From the research results, to meet the electricity demand of 15,055 kWh, it needs 12 200 Wp PV modules assembled in 6 series 2 parallel, 8 12V 200Ah batteries with 4 series 2 parallel, and 1 3 kW hybrid inverter are needed. From the simulation results, the estimated energy that can be produced is 35 kWh with a performance of the system is 61.42%. In terms of investment, the initial capital required is Rp89,954,000 so that the NPV value is obtained at Rp1,725,979, PI is 1.01, and PBP is estimated to fall in year 22 month 11.
Article
Full-text available
Solar is a promising renewable energy source for Indonesia's increasing electricity demand, which grows at the rate of 3.3% annually. However, high investment costs and unclear policies hinder Solar Power Plant (SPP) development. Considering the potential for growth in energy demand and the low long-term operational costs, it is imperative to foster SPP expansion in Indonesia. This study aims to identify location criteria and potential SPP development sites in Indonesia. We employ Multi-Criteria Decision-Making (MCDM) combining Fuzzy-AHP and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies to assign criteria weights and prioritize alternative SPP locations. Results show that, from all respondents using the geometric mean in the Fuzzy Analytic Hierarchy Process (AHP), it is found that the Economic criteria give the highest weight at 31%, and subcriteria of Land Availability, Peak Sun Hours, Geographic Location, Distance from Transportation Networks, Construction Costs, and Government Regulations contribute significantly. The ranking of alternative solutions indicates that South Sumatra Province holds the highest priority for SPP development with a 0.572 score, closely followed by North Sumatra at 0.571
Chapter
Efficient management of renewable energy sources is crucial for grid integration. This paper proposes an integrated energy management system (IEMS) that combines supply and demand-side management to manage the use of solar energy. An off-grid residential load supplied by a 7.5 kVA diesel generator (DG) and 10 kW photovoltaic (PV) supply is considered. The main objective of the IEMS framework is to increase PV usage through solar energy forecasting (SEF), time-of-use (TOU) criteria, direct load control (DLC) and generator control (GC). First, the PV is optimally sized using the Performance Ratio method. Next, a three-step SEF approach predicts the next-day ahead PV generation. Finally, the IEMS’s decision algorithm sets the TOU, initiates DLC to reduce excess load, and/or increase supply by calling up the DG. The performance of three configurations is compared: DG, DG/PV, and DG/PV/IEMS. The DG/PV/IEMS configuration showed an increase PV usage over the DG/PV by 132%. In addition, the IEMS reduces CO2 emissions by 47% and 35% when compared to the DG and DG/PV configurations respectively.
Article
Panel surya merupakan komponen utama dalam pembangkit listrit tenaga surya. Energi matahari yang diterima dapat dikonversikan menjadi energi listrik yang dapat dipakai untuk menunjang aktivitas kehidupan. Beragam jenis panel surya telah dikembangkan agar dapat menghasilkan listrik dengan kapasitas besar dan mempunyai skala konversi dengan efisiensi yang tinggi. Penggunaan panel surya sebagai penghasil listrik juga perlu mempertimbangkan beragam faktor yang akan berdampak terhadap jumlah listrik yang dihasilkan. Paper ini menyajikan hasil eksperimen pada panel surya Policrystalline kapasitas 100 Wp yang terdampak oleh perubahan cuaca dalam menghasilkan listrik. Melalui pengujian yang dilakukan dalam kondisi cuaca yang cerah, cuaca mendung dan hujan diperoleh hasil bahwa performa panel surya ketika diuji dalam cuaca cerah akan mampu menghasilkan daya listrik hingga mencapai 600 W sehari dimana rata-rata daya yang dihasilkan sebesar 84,4 W di waktu peak sun hours (PSH). Sedangkan dalam pengujian yang dilakukan pada kondisi cuaca mendung serta hujan, panel surya hanya dapat menghasilkan listrik tidak sampai 200 W sehari dengan rata-rata daya listrik terukur sebesar 19 W di waktu PSH. Hasil penelitian ini memberikan gambaran bahwa panel surya masih bekerja untuk menghasilkan listrik ketika cuaca mendung namun sangat kecil ketika cuaca hujan.
Article
Full-text available
Renewable energies are the alternative that leads to a cleaner generation and a reduction in CO 2 emissions. However, their dependency on weather makes them unreliable. Traditional energy operators need a highly accurate estimation of energy to ensure the appropriate control of the network, since energy generation and demand must be balanced. This paper proposes a forecaster to predict solar irradiation, for very short-term, specifically , in the 10 min ahead. This study develops two tools based on artificial neural networks, namely Long-Short Term Memory neural networks and Convolutional Neural Network. The results demonstrate that the Convolutional Neural Network has a higher accuracy. The tool is tested examining the root mean square error, which was of 52.58 W/m 2 for the testing step. Compared against the benchmark, it has obtained an improvement of 8.16%. Additionally, for the 82% of the tested days it has given a less than 4% error between the predicted and the actual energy generation. Results indicate that the forecaster is accurate enough to be implemented on a pho-tovoltaic generation plan, improving their integration into the electrical grid, not only for providing power but also ancillary services.
Article
Full-text available
In this paper, an open source method for calculating self-shading in fields of two-axis tracking solar collectors of arbitrary geometry was developed and validated. The method was used to investigate the impact of latitude and collector aperture shape on annual shading loss. Simulations were carried out for the entire design space of field layouts by uniformly discretizing the layout parameters, i.e., aspect ratio, offset, rotation, and ground cover ratio. Results showed shading losses generally increase with latitude, and the optimum aspect ratio decreases with distance from the equator. Aperture shape was shown to significantly impact power output; the annual shading loss was lowest for the rectangular collector and highest for the square collector. Also, the impact of sub-optimal rotation of rectangular arrays was presented.
Article
Full-text available
Renewable energy sources have developed rapidly, decreased in cost, and proven to have the potential to limit global warming. Renewable energy in the form of solar energy can be collected through decentralized rooftop solar systems. Solar energy development in Qatar is still at an early stage. The abundance of solar radiation, high GDP, and plentiful access to rooftop spaces make rooftop photovoltaic (PV) systems suitable. Unfortunately, the early development and adoption of residential rooftop solar PV systems are expected to face numerous constraints. This paper investigates the factors that impact the residential rooftop solar photovoltaic adoption in Qatar. Through analyzing the response of a general public sample, we hope to prove the hypothesized factors by aiming at testing their solar systems knowledge and awareness. The result of the study will provide insights on how the public perceives solar panels, along with factors the government needs to address to ensure successful public adoption of residential solar rooftop systems in Qatar.
Article
Full-text available
This paper identifies value creation strategies and the role of stakeholders in advancing sustainable practices for end-of-life (henceforth EOL) solar photovoltaic panels (solar PV) in Ghana. This is preceded by an overview of the global outlook of sustainable practices for EOL solar PV as well as how these can be promoted in a developing country like Ghana. The framework discusses and promotes efficient collaboration towards value creation by stakeholders in advancing sustainable practices for end-of-life solar PV in Ghana. The methodology centers on an integrative review aimed at identifying the different aspects leading to a value creation framework for EOL solar PV. The paper discusses a hybrid public-private partnership (HPPP), which includes the types of synergy between different actors as well as their clear roles. The core options available to government, businesses and end-users in the value creation includes the provision of a technical solution, improved logistics and innovative business opportunities. The aforementioned options will achieve reduction, reuse, repair and/or recycling, targeted at promoting a unique collaboration between all relevant stakeholders. Furthermore, such options present an opportunity to promote awareness utilizing education in sustainability, thus promoting the need for extending the useful lifecycle of the products.
Article
Full-text available
The rapid development of photovoltaic plays an important role in achieving the carbon-neutral goal. How to improve the conversion efficiency and power generation of solar photovoltaic has always been a focus issue. However, more attention is paid to the impact of photovoltaic panel working temperature on the performance of photovoltaic power generation, and how air temperature affects photovoltaic power generation has been ignored. This paper compared and analyzed the impact of the difference in air temperature between lake and land on the revenue of photovoltaic power generation, and established the functional equation between photovoltaic power generation, air temperature and solar radiation, and revealed the relationship between air temperature, solar radiation, and photovoltaic power generation.
Article
Full-text available
The adaptable transmittance of electrochromic glazing allows to control the solar radiation entering buildings, yet the level of transmittance needed to protect from glare is still an unanswered question. To bridge this gap, this study evaluates the level of visible light transmittance (τv) required for blue-tinted low transmittance glazing to prevent discomfort glare when the sun is visible through the glazing. Twenty participants were exposed to four visual scenarios with varying viewing directions and window transmittance. Results indicate that when the sun is close to the central field of view, a normal-hemispherical transmittance, τv, n-h of 0.6% prevents disturbing glare for most users but does not provide a comfortable situation (this condition corresponds to a “seen” sun disc’s luminance of 4.8M cd/m²). To achieve comfortable situations, a τv, n-h of 0.14% was found suitable. For non-critical viewing directions, τv n-h of 0.6% is sufficient to achieve visually comfortable space for most participants. This study also examined the reliability of five discomfort glare metrics by comparing their objective output to subjective responses for the tested conditions. The contrast-based metrics (Daylight Glare Probability, CIE Glare Index, Unified Glare Probability, Daylight Glare Index) possess a valid positional sensitivity and show higher Spearman’s rank correlations (ρ∼0.56-0.59) compared to solely saturation-based metrics as the vertical illuminance (Ev) (ρ∼0.44).
Article
Full-text available
With over 70% of households without access to clean energy, Uganda presents a huge potential for increased adoption of solar photovoltaic (PV) technologies. However, their uptake is relatively low. This study employs a nationally representative data set from Uganda's National Electrification Survey of 2018 to analyze factors influencing households' choice of solar PV system. Conditional mixed process model was estimated for quantification of associations between flexible payment mechanism, influential persons, access to grid electricity and solar PV adoption in the first stage, then type of solar PV adopted in the second stage. We find that, the determinants of adoption as well as type of solar PV adopted are heterogeneous. Specifically, flexible payment mechanism is positive for uptake of solar home systems and solar kit; Influential people were insignificant in all cases, while grid access was negatively associated with uptake of both solar kits and solar home systems. We further find that, rural residence, income, type of house are significant drivers of solar PV type adopted. Conversely, education attainment was positive and significantly associated with adoption but insignificant for type of solar PV adopted. Sex of household head was significant for uptake of solar kit. Our findings suggest that, solar PV uptake is a rural phenomenon and affordability is the main driver of solar PV type adopted. Flexible payment mechanism enhances the ability of income constrained households to afford relatively expensive solar PV systems. Hence, any policy interventions geared at scaling uptake of solar home systems should address affordability. Solar companies should continue to offer flexible payment modalities and target rural household.
Article
Owing to the global increasing need for clean renewable energy, solar photovoltaic (PV) generation technology has gained more attention. The utilization of a grid-tied solar PV rooftop system may minimize the electricity bills of residential consumers. Battery storage proved to be the most expensive component of a solar PV system. Hence, optimal battery sizing for a grid-tied PV solar system is of fundamental importance to maximize investment returns. This study aims to determine the optimal battery size for the proposed non-interactive grid-tied solar PV-battery system when exposed to South African solar irradiance. The proposed system is investigated for supplying the residential load under the time-of-use (TOU) pricing strategy. Hence, the optimal power flow control model has been developed and utilized to determine the optimal battery size. Optimal power flow management has been achieved through the use MATLAB optimization solver called linprog. Different battery sizes have been analyzed for the selected 4.2-kW solar PV array that supplies a residential load having a peak demand of 4.2-kW. The optimization results indicated that the optimal battery size is 18.3% of the residential load demand, in the context of South African solar irradiance and the TOU tariff scheme. When the selected PV array size matches the peak load demand, the selection of a battery size greater than 18.3% proved to minimize the economic returns as a result of the inflexible electricity cost savings. For PV array size greater than the peak load demand, the optimal battery storage size increases by 11.5% of the daily load energy consumption per kW upsizing.
Article
Solar photovoltaic systems represent an important technology for renewable energy utilization and have broad potential for application and development. However, the further development of solar photovoltaic systems is hindered by their higher generation costs. A high-concentration photovoltaic system (HCPVs) can use an inexpensive concentrator to replace solar cells; this, in turn, reduces the cost of electricity generation, because the solar cell requirement decreases for a given power. This study developed a mathematical model for multi-junction solar cell (MJSC) based on single-diode equivalent circuit, furthermore, an HCPVs with hyperboloid mirrors was established. The electrical properties for an MJSC module, including the short-circuit current (Isc), peak power (Pm), open-circuit voltage (Voc), fill factor (FF), and efficiency (η) were investigated at concentration ratios between 650 X and 800 X and direct solar radiation intensities between approximately 400 W/m2 and 730 W/m². Furthermore, the experimental results and theoretical values were comparatively analyzed. The results demonstrated that Isc, Voc, and Pm of MJSC module increased as the direct solar radiation raised. In contrast, the FF and η of an MJSC module decreased as the direct solar radiation raised. As the direct solar radiation intensity was 700 W/m² and concentration ratio increased from 650 X to 800 X, Isc, Voc, and Pm increased from 1.002 A to 1.243 A, 11.095 V to 11.158 V, and 9.466 W to 11.358 W, respectively. Conversely, the FF and η of the MJSC module decreased from 32.51 % to 31.33 % and 0.851 to 0.819, respectively. The tallied between the numerical and experimental results was evaluated, which indicated that root-mean-square error between the experimental and calculated values increased as the direct solar radiation increased.
Article
The energy output from a combined cycle power plant (CCPP) varying with the operating thermal parameters like ambient pressure, vacuum, relative humidity, and relative temperature is modelling using different approaches. The huge data obtained from the experimental readings is found to be highly non-linear using the data visualization technique. The energy output from the CCPP reduces linearly with the temperature and non-linearly with pressure. A mathematical model is developed for the predictions of the energy output. Modelling using sequential API and functional API based artificial neural network (SANN and FANN) having single hidden layer is carried out. Finally, energy output modelling using sequential API and functional API based deep ANN (SDNN and FDNN) is also performed. The residuals of the predicted and experimental observations indicate that the error is acceptable and it lies uniformly above and below the regression line. The R-squared value of the mathematical model is 0.93 and 0.94 during training and testing. The obtained R-squared value of the ANN and DNN using sequential and functional API is 0.94. The training and testing of all the models are successful and these models have shown a great compatibility in predicting the energy output of a CCPP. The ANN model with single layer and deep layer has no difference in accuracy hence the former one is recommended as it is computationally less expensive.