Submitted:
28 October 2024
Posted:
29 October 2024
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Factors for Assessing Suitable Regions for Solar PV Projects Across Oman
2.1. Solar PV irradiation level and Temperature coefficient
2.2 Humidity level
2.3 Dust accumulation
2.4. Population Density
2.5. Discussion on Solar PV project suitability in various regions across Oman
3. Design and Assess the Rooftop solar PV performance in Selected Regions
3.1. Energy Demand of the Smart Bus stop
3.2. Design of Solar PV system for Smart bus stop load
3.2.1. Sizing of Solar PV Panel
3.2.2. Sizing of Inverter
3.2.2. Voltage matching between the array voltage and the inverter input voltage
3.2.3. Cable sizing
4. Performance analysis and Economic analysis of Solar PV System
4.1. Performance analysis
4.1.1. Solar Array output
4.1.2. Specific Energy yield
4.1.3. Performance ratio
4.1.4 DC Capacity factor
4.2. Levelised Cost of Electricity of the Solar PV system
4.3. Performance analysis and Economic analysis of solar powered smart bus stop at various UTAS branches
4.3.1. Performance analysis
4.3.2. Economic analysis
5. Results and Discussion
5.1 Design and Analysis of Solar PV system for smart bus stop using SAM software
5.2. Comparison of Analytical method results and SAM results
5.2.1. Annual Energy yield:
5.2.2. Performance ratio:
5.2.3. DC Capacity factor
5.2.4 LCOE
5.3. Attractive Solar PV strategies for Oman
- Design a dynamic FiT to export solar power to the grid, allowinghomeowners can sell their excess solar power through net metering at a dynamic tariff.
- Allocating subsides to install rooftop solar PV systems in home reduces the financial burden on homeowners.
- Implementing a solar PV business model for economically weaker sections to help financially by allowing them to sell the solar power.
- Introducing an incentive to compensate for solar electricity as it is expensive compared to existing electricity tariff makes it economically sustainable.
- Allocate special funding and launch a public awareness program onresidential solar PV
6. Conclusion
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Darby, Sarah J., Geoffrey P. Hammond, and Jianzhong Wu. "Briefing: Stocktaking global warming: the outcomes of the 2023 Dubai Climate Summit (COP28)." Proceedings of the Institution of Civil Engineers-Energy (2024): 1-12.
- Power and water Procurement’s 7-year statement (2023 -2029), Issue 17, NAMA Power and Water Procurement Co. Available Online: 7 Year Statement - Nama Power & Water Procurement (Accessed on 21 October 2024).
- Renewable Energy | Authority for Public Services Regulation. (Accessed on 21 October 2024).
- Charabi, Yassine. Deep near-term mitigation of short-lived climate forcers in Oman: grand challenges and prospects. Environmental Science and Pollution Research 2023, 30, 3918–3928. [Google Scholar] [CrossRef] [PubMed]
- The Sultanate of Oman’s National Strategy for an Orderly Transition to Net Zero November 2022(oma223284E.pdf (fao.org)) (Accessed on 21 October 2024).
- Sahim Page | Authority for Public Services Regulation (apsr.om) (Accessed on 21 October 2024).
- Al Siyabi, Idris, et al. "Effect of soiling on solar photovoltaic performance under desert climatic conditions." Energies 14.3 (2021): 659.
- Kazem, Hussein A., and Miqdam T. Chaichan. The effect of dust accumulation and cleaning methods on PV panels’ outcomes based on an experimental study of six locations in Northern Oman. Solar Energy 2019, 187, 30–38. [Google Scholar] [CrossRef]
- Abdul-Wahab, Sabah; et al. Selection of the best solar photovoltaic (PV) for Oman. Solar Energy 2019, 188, 1156–1168. [Google Scholar] [CrossRef]
- Honnurvali, Mohamed Shaik. "Photovoltaic challenges and recommendations-A case study for Oman." PhD diss., 2023.
- Al-Badi, A. H. Selection of the best solar photovoltaic (PV) for Oman. Energy for Sustainable Development 2018, 47, 107–113. [Google Scholar] [CrossRef]
- AlBusaidi, Ahmed Said, Neha Cherattuparabil Anil. Performance Analysis of a 22.8 kW PV solar system of the HCT ECO house in Oman. International Journal of Renewable Energy Research (IJRER) 2022, 12, 48–57. [Google Scholar]
- Al-Saadi, Saleh Nasser, and Awni K. Shaaban. Zero energy building (ZEB) in a cooling dominated climate of Oman: Design and energy performance analysis. Renewable and Sustainable Energy Reviews 2019, 112, 299–316. [Google Scholar] [CrossRef]
- Al-Badi, Abdullah. Performance assessment of 20.4 kW eco-house grid-connected PV plant in Oman. International Journal of Sustainable Engineering 2020, 13, 230–241. [Google Scholar] [CrossRef]
- Al-Saqlawi, Juman, Kaveh Madani. Techno-economic feasibility of grid-independent residential roof-top solar PV systems in Muscat, Oman. Energy Conversion and Management 2018, 178, 322–334. [Google Scholar] [CrossRef]
- Alhousni, Fadhil Khadoum; et al. A review of PV solar energy system operations and applications in Dhofar Oman. AIMS Energy 2022, 10, 858–884. [Google Scholar] [CrossRef]
- Kazem, Hussein A.; et al. Techno-economic feasibility analysis of 1 MW photovoltaic grid connected system in Oman. Case studies in thermal engineering 2017, 10, 131–141. [Google Scholar] [CrossRef]
- Mishrif, Ashraf, and Asharul Khan. Non-Industrial Solar Energy Use, Barriers, and Readiness: Case Study of Oman. Energies 2024, 17, 3917. [Google Scholar] [CrossRef]
- AnnualReport2022EN.pdf (apsr.om) (Accessed on 21 October 2024).
- Bakhshi-Jafarabadi, Reza, and Seyed Mahdi Seyed Mousavi. Peak Load Shaving of Air Conditioning Loads via Rooftop Grid-Connected Photovoltaic Systems: A Case Study. Sustainability 2024, 16, 5640. [Google Scholar] [CrossRef]
- Hereher, Mohamed, and Ahmed M. El Kenawy. Exploring the potential of solar, tidal, and wind energy resources in Oman using an integrated climatic-socioeconomic approach. Renewable Energy 2020, 161, 662–675. [Google Scholar] [CrossRef]
- Gastli, Adel, and Yassine Charabi. Solar electricity prospects in Oman using GIS-based solar radiation maps. Renewable and Sustainable Energy Reviews 2010, 14, 790–797. [Google Scholar] [CrossRef]
- Al-Dousari, Ali, Domenico Doronzo. Types, indications and impact evaluation of sand and dust storms trajectories in the Arabian Gulf. Sustainability 2017, 9, 1526. [Google Scholar] [CrossRef]
- Chaichan, Miqdam T.; et al. Sand and dust storms’ impact on the efficiency of the photovoltaic modules installed in baghdad: a review study with an empirical investigation. Energies 2023, 16, 3938. [Google Scholar] [CrossRef]
- Solar resource maps & GIS data for 200+ countries | Solargis (Accessed on 21 October 2024).
- Cotfas, Daniel T., and Petru A. Cotfas. Comparative study of two commercial photovoltaic panels under natural sunlight conditions. International journal of photoenergy 2019, 2019, 8365175. [Google Scholar] [CrossRef]
- Bertrand, Cédric, et al. "Solar irradiation from the energy production of residential PV systems." Renewable Energy 125 (2018): 306-318.
- Honnurvali, Mohamed Shaik; et al. Case study of PV output power degradation rates in Oman. IET Renewable Power Generation 2019, 13, 352–360. [Google Scholar] [CrossRef]
- Kwarteng, Andy Y., Atsu S. Dorvlo, and Ganiga T. Vijaya Kumar. "Analysis of a 27-year rainfall data (1977-2003) in the Sultanate of Oman." International Journal of Climatology 29.4 (2009): 605.
- Ponnusamy, Lakshmi, and Dhass Desappan. "An investigation of temperature effects on solar photovoltaic cells and modules." International Journal of Engineering 27.11 (2014): 1713-1722.
- Tripathi, Abhishek Kumar, et al. "Evaluation of solar PV panel performance under humid atmosphere." Materials Today: Proceedings 45 (2021): 5916-5920.
- Kazem, Hussein A., and Miqdam T. Chaichan. "Effect of humidity on photovoltaic performance based on experimental study." International Journal of Applied Engineering Research (IJAER) 10.23 (2015): 43572-43577.
- Garni, Hassan Z. Al. "The Impact of Soiling on PV Module Performance in Saudi Arabia." Energies 15.21 (2022): 1-25.
- Papi, Ramin, et al. "Characterization of hydrologic sand and dust storm sources in the Middle East." Sustainability 14.22 (2022).
- Thornton, John Preston. The effect of sandstorms on PV arrays and components. No. NREL/TP-411-4787; CONF-920678-1. National Renewable Energy Lab., Golden, CO (United States), 1992.
- Al Senafi, Fahad, and Ayal Anis. "Shamals and climate variability in the Northern Arabian/Persian Gulf from 1973 to 2012." International Journal of Climatology 35.15 (2015).
- Vedulla, Gowtham, Anbazhagan Geetha, and Ramalingam Senthil. "Review of strategies to mitigate dust deposition on solar photovoltaic systems." Energies 16.1 (2022): 109.
- Al Kindi, M.; et al. Stratigraphy, palaeoclimatic context and fossils of the Southern Rub Al Khali (the Empty Quarter): results of a geo-archaeological survey around the area of Maitan in the Sultanate of Oman. Historical Biology 2021, 33, 1534–1555. [Google Scholar] [CrossRef]
- Hereher, Mohamed, et al. "Formation of the Wahiba Sand Sea in the Sultanate of Oman: implications of change in wind energy." Arabian Journal of Geosciences 13 (2020): 1-14.
- Hereher, Mohamed E. "Assessment of infrastructure vulnerability to tsunamis upon the coastal zone of Oman using GIS." Geosciences 10.5 (2020): 175.
- Oman Population (2024) - Worldometer (worldometers.info) (Accessed on 21 October 2024).
- WorldPop :: Population Density (Accessed on 21 October 2024).
- Tarigan, Elieser, and Fitri Dwi Kartikasari. "Techno-economic simulation of a grid-connected PV system design as specifically applied to residential in Surabaya, Indonesia." Energy Procedia 65 (2015): 90-99.
- Marion, B. , Adelstein, J., Boyle, K., Hayden, H., Hammond, B., Fletcher, T., & Canada, B. (2005). "Performance parameters for grid-connected PV systems." Proceedings of the 31st IEEE Photovoltaic Specialists Conference, 1601-1606.
- Emery, Keith. "Measurement and characterization of solar cells and modules." Handbook of photovoltaic science and engineering (2011): 797-840.
- Canadian_Solar Panel -Datasheet(Accessed on 21 October 2024).
- Council, Clean Energy. "Grid-Connected Solar PV Systems: Design Guidelines for Accredited Installers." Clean Energy Council: Melbourne, Australia (2013): 1-18.
- Sun grow inverter data sheet(Accessed on 21 October 2024).
- Grid Connect PV system Design Guide, SEIAPI, Issue 1 September 2012(Accessed on 21 October 2024).
- Directorate General of Meteorology, Oman(Accessed on 21 October 2024).
- Tran, Thomas TD, and Amanda D. Smith. Evaluation of renewable energy technologies and their potential for technical integration and cost-effective use within the US energy sector. Renewable and Sustainable Energy Reviews 2017, 80, 1372–1388. [Google Scholar] [CrossRef]
- Tran, Thomas TD, and Amanda D. Smith. Incorporating performance-based global sensitivity and uncertainty analysis into LCOE calculations for emerging renewable energy technologies. Applied energy 2018, 216, 157–171. [Google Scholar] [CrossRef]
- Inmaculada, Guaita-Pradas, and Ana Blasco-Ruiz. Analyzing profitability and discount rates for solar PV plants. A Spanish case. Sustainability 2020, 12, 3157. [Google Scholar] [CrossRef]
- Renewable Hydrogen from Oman, IEA report(Accessed on 21 October 2024).
- Sheng, Chunhong, Yun Cao. Residential Energy Sustainability in China and Germany: The impact of national energy policy system. Sustainability 2018, 10, 4535. [Google Scholar] [CrossRef]
- Liu, Y.; Li, J. German renewable energy legal selection and its implications. Environ. Prot. 2012, 15, 68–70. [Google Scholar]
- Market Incentive Programme (MAP) – Policies - IEA(Accessed on 21 October 2024).
- Matschoss, Patrick; et al. The German incentive regulation and its practical impact on the grid integration of renewable energy systems. Renewable Energy 2019, 134, 727–738. [Google Scholar] [CrossRef]
- Report on the long-term strategy for mobilise investment in the renovation of the national building stock, The Government of the Federal Republic of Germany.
- Wrede, Matthias. The influence of state politics on solar energy auction results. Energy Policy 2022, 168, 113130. [Google Scholar] [CrossRef]
- Zhang Sufang, Li Xingmei. Large scale wind power integration in China: analysis from a policy perspective. Renewable and Sustainable Reviews 2012, 16, 1110–5. [Google Scholar] [CrossRef]
- Zhang, Sufang, and Yongxiu He. Analysis on the development and policy of solar PV power in China. Renewable and Sustainable Energy Reviews 2013, 21, 393–401. [Google Scholar] [CrossRef]
- Xiong, Yongqing, and Xiaohan Yang. "Government subsidies for the Chinese photovoltaic industry." Energy Policy 99 (2016): 111-119.
- Zhang, Sufang. "Analysis of Distributed Solar Photovoltaic (DSPV) Power Policy in China." Chapters (2016): 137-159.
- Wen, Daoyuan, et al. "Development of solar photovoltaic industry and market in China, Germany, Japan and the United States of America using incentive policies." Energy Exploration & Exploitation 39.5 (2021): 1429-1456.
- Tabassum, Sanzana, et al. "Solar energy in the United States: Development, challenges and future prospects." Energies 14.23 (2021): 8142.
- Stolte, Justin. "The Energy Policy Act of 2005: The Path to Energy Autonomy." J. Legis. 33 (2006): 119.
- IEA (2011) National Survey Report of PV Power Applications in the United States 2010. Paris: International Energy Agency.
- U.S. DOE (2015) The SunShot Initiative: Making Solar Energy Affordable for all Americans. USA: U. S. DOE, pp.1–2.
- U.S. DOE (2017) The SunShot 2030 Goals: 3¢ per Kilowatt Hour for PV and 5 ¢ per Killowatt Hour for Dispatchable CSP. USA: U.S. DOE, pp.2–6.
- Solar for All | US EPA (Accessed on 21 October 2024).
- DSIRE (Accessed on 21 October 2024).
- Mills, Andrew, et al. "The impact of retail rate structures on the economics of commercial photovoltaic systems in California." Energy Policy 36.9 (2008): 3266-3277.
- Muhammad-Sukki, Firdaus; et al. Feed-in tariff for solar photovoltaic: The rise of Japan. Renewable energy 2014, 68, 636–643. [Google Scholar] [CrossRef]
- Myojo S & Ohashi, H. “Effects of consumer subsidies for renewable energy on industry growth and Welfare: Japanese solar energy” 39th Annual Conference of European Association for Research in Industrial Economics, Rome 2012: 1-24.
- Kuwahara, Ryoichi, Hyuntae Kim, and Hideki Sato. "Evaluation of zero-energy building and use of renewable energy in renovated buildings: A case study in Japan" Buildings 12.5 (2022): 561.
- Yamaura, Koichi, et al. "Public perceptions on net zero energy houses in Japan." Sustainability Science (2024): 1-12.
- National Portal for Rooftop Solar - Ministry of New and Renewable Energy (Accessed on 21 October 2024).
- Goel, Malti. "Solar rooftop in India: Policies, challenges and outlook." Green Energy & Environment 1.2 (2016): 129-137.
- Hussain, Akhtar, and Hak-Man Kim. Enhancing Renewable Energy Use in Residential Communities: Analyzing Storage, Trading, and Combinations. Sustainability 2024, 16, 891. [Google Scholar] [CrossRef]













| Types of Sand | Characteristics | Areas covered |
|---|---|---|
| Rub'al Khali (Empty Quarter) [38] | Fine, reddish sand. | Thumrait, Southern Oman |
| Wahiba Sands (Sharqiya Sands) [39] | Fine to medium-grained sand. | Bidiyah, sur, North east corner |
| Coastal Areas [40] | Coarse, white sand | Al-Batinah North and South, Muscat, Ash Sharqiya South, Al-Wusta, Dhofar, Musandam |
| Desert Plains and Gravel Deserts | Mixed coarse sand and gravel. | Ibra, Adam, Ibri, Buraimi |
| Mountain Regions | Coarse sand with rock fragments | Nizwa, Rustaq |
| Alluvial Fans and Wadis | Silty sand and fine gravel | Sohar, Buraimi, Nizwa, Rustaq |
| Region | Solar Irradiance | Humidity Level | Dust Level | Population Density | Suitability |
|---|---|---|---|---|---|
| Northern Oman | High | Moderate (higher near coast, lower inland) | Moderate to High | High | High |
| Southern Oman (Dhofar, Salalah) | Moderate to High (varies with season) | High during Khareef, moderate otherwise | Low to Moderate | Low to Moderate (highest in Salalah) | Moderate |
| Central Oman | High | Low | High | Very low | Low |
| Western Oman | Moderate to High | Moderate to High near coast, low inland | Low to Moderate | Low | Moderate |
| Coastal Areas | High | High | Moderate | High | High |
| Mountain Areas | Moderate to High (depending on altitude and location) | Low to Moderate | Low | Low | Low to Moderate |
| UTAS Branch Name | Location, Region | Latitude | Longitude |
|---|---|---|---|
| UTAS – Muscat | Al Khoud, Muscat | 23.5803 | 58.4328 |
| UTAS – Salalah | Salalah, Dhofar | 17.0473 | 54.1427 |
| UTAS – Nizwa | Nizwa, Ad Dakhiliyah | 22.8903 | 57.5560 |
| UTAS – Ibra | Ibra, Ash Sharqiyah North | 22.7764 | 58.4934 |
| UTAS – Shinas | Shinas, Al Batinah North | 24.7422 | 56.4292 |
| UTAS – Sur | Sur, Ash Sharqiyah South | 22.5667 | 59.4715 |
| UTAS – Ibri | Ibri, Ad Dhahirah | 23.2424 | 56.4196 |
| UTAS - Al Mussanah | Al Mussanah, Al Batinah South | 23.7432 | 57.5779 |
| Load | Number in Use | Power Rating (W) | Winter (Nov-Mar) |
Summer (Apr, Sep, Oct) |
Peak Summer (May, Jun) |
Vacation (Jul, Aug) |
||||
|---|---|---|---|---|---|---|---|---|---|---|
| T* (Hr) |
E** (W- Hr) |
T* (Hr) |
E** (W- Hr) |
T* (Hr) |
E** (W- Hr) |
T* (Hr) |
E** (W- Hr) |
|||
| Smart AC | 1 | 1000 | 7 | 7000 | 10 | 10000 | 13 | 13000 | 0 | 0 |
| Smart LED light | 10 | 18 | 13 | 2340 | 13 | 2340 | 13 | 2340 | 4.5 | 810 |
| Water Dispenser | 1 | 50 | 7 | 350 | 10 | 500 | 13 | 650 | 0 | 0 |
| Smart TV | 1 | 17 | 13 | 221 | 13 | 221 | 13 | 221 | 4.5 | 76.5 |
| Daily Energy Consumption (kW- Hr) |
9.911 | 13.061 | 16.211 | 8.86 | ||||||
| Monthly Energy Consumption (kW- Hr) |
198.22 | 261.22 | 324.22 | 17.73 | ||||||
| Type of Loss | Description | % range of loss |
|---|---|---|
| Reflection Losses | The glass on solar PV surface reflects the part of solar irradiance on it. | ~2-3% |
| Temperature Losses | Increased temperature reduces the open circuit voltage much more significant. | ~5-10% |
| DC Cable Losses | Due to resistance of the wires | ~1-3% |
| Inverter Losses | During conversion process of DC to AC | ~2-5% |
| AC Cable Losses | Due to resistance of the wires | ~1-2% |
| Shading Losses | Shading due to trees, buildings and clouds. | ~0-1% |
| Losses due to Dust and Dirt | Accumulation of dust due to sandstorm, Industries, and Vehicles | ~2-6% |
| Module Mismatch | Differences in the performance between individual solar panels within a string | ~1-3% |
| Model | CS6W-550MB-AG |
|---|---|
| Nominal Maximum Power (Pmax) | 550 Wp |
| Operating Voltage (Vmp) | 41.7 V |
| Operating Current (Imp) | 13.20 A |
| Open Circuit Voltage (Voc) | 49.6 V |
| Short circuit current (Isc) | 14.00 A |
| Panel Efficiency(η) | 21.4% |
| Cell Type | Mono-crystalline |
| Cell Arrangement | 144 [2 x (12 x 6) ] |
| Dimensions | 2266 ˣ 1134 ˣ 35 mm |
| Weight | 32.2 kg |
| Model | CS6W-550MB-AG |
| Sun hours, Ibri () | 6.5Hrs (Eq. (2)) |
| Solar PV system required ( | (Eq. (3)) |
| Number of Panels required () | 5 (Eq. (4)) |
| Number of Panels that can be accommodated on the Rooftop () | 4 |
| Total capacity of Solar PV Array () | 2.2kWp |
| Tilt angle | 21° facing south |
| Azimuth angle | 180° |
| Parameter | Values |
|---|---|
| Solar PV Peak power (PVarray) | 2.2 kW (Eq. (5)) |
| Manufactures tolerance of the panel (PVtol) | 0.95 from data sheet |
| Average Temperature, Ibri | 37.37°C [50] |
| Cell temperature (Tcell-temp) | 62.37°C (Eq. (6)) |
| Derate due to dirt deposition (PVderate-dust) | 0.95 (Assumed) |
| Derate due to Temperature (PVderate-temp) | 0.87 (Eq. (7)) |
| Derating power of the solar PV panel (PVderated) | 0.79 (Eq. (8)) |
| Rating of on-grid solar inverter (Invrating ) | 2kW (Eq. (9)) |
| Model | Maximum PV input voltage (Vmax-inv) |
Minimum PV input voltage (Vmin-inv) |
Maximum PV input current (Imax-inv) |
Maximum Efficiency |
Nominal AC output power (Invrating) |
|---|---|---|---|---|---|
| SG2K-S | 600V | 90V | 10A | 98.2% | 2000W |
| Temperature Coefficient (β) |
Temperature Coefficient (Voc-tempcoeff) |
Temperature Coefficient (Isc-tempcoeff) |
Nominal Panel operating Temperature | Operating Temperature (tpanel-max) | Temperature Coefficient (Vmp-tempcoeff) |
|---|---|---|---|---|---|
| -0.34 % / °C | -0.26 % / °C | 0.05 % / °C | 41 ± 3°C | 85°C | 0.15 % / °C |
| Parameter | Values |
|---|---|
| Maximum power point voltage at Maximum temperature ( Vmp-tmax) | 32.7V (Eq. (10)) |
| Maximum voltage drop in the cables (Vdrop-cable) | 3% assumed |
| Minimum input voltage allowed to the inverter (Vmp-inv) | 31.719V (Eq. (11)) |
| Minimum number of panels (Nmin-module) in a string to maintain Vmin-inv | ~3 Panels (Eq. (12)) |
| Oman lowest temperature (tmin) | ~20°C |
| Maximum open circuit voltage at Minimum temperature ( Voc-tmin) | 50.9 V (Eq. (13)) |
| Maximum number of panels (Nmax-module) in a string to maintain Vmax-inv | ~12 Panels (Eq. (14)) |
| Parameter | Values |
|---|---|
| Derating factor of the solar PV array ( PVderated) | 0.79 (Eq. (8)) |
| Panel derated power (Pderated) | 434.5 W (Eq. (16)) |
| Sun hour (Hrsun) | 6.5 (Eq. (2)) |
| DC Energy output from array per day (Parray) | 13.035 kWh (Eq. (17) |
| Cable loss () | 3% (Assumed) |
| AC system loss | 1%(Assumed) |
| Total AC Energy output per day (Pac) | 12.29kWh (Eq. (18)) |
| Annual energy form solar PV array ( | 4485.85 kWh (Eq. (19)) |
| Parameter | Values |
|---|---|
| Total Solar PV cost | $2400 |
| Inverter cost | $1700 |
| Installation Labor cost and Miscellaneous cost | $220.08 |
| Total Investment cost (It) | $4320.08 |
| Operation cost (Ot) | 0.5% of total Installation cost |
| Maintenance cost (Mt) | $43.2/kW+$3 for every year |
| Replacement cost (Rt) | For every 10th year 10% of the total investment cost |
| Discount (r) | 3% |
| Annual AC energy output (St) | 12.29kWh |
| Degradation rate (d) | 0.5% |
| Lifetime of the project (N) | 25 years |
| UTAS branches | Tavg-temp (approx.) | PVderate-temp | PVderate-dirt | PVderated | Pderated (W) | Parray (kW) | Pac (kW) | EAC (kWh/Ns*) |
CF | Especific-yield (kWh/kW) | PR | |
| Muscat | 40.38 | 0.86 | 0.85 | 0.70 | 383.15 | 9.09 | 13.93 | 13.14 | 1576.49 | 0.26 | 716.59 | 0.66 |
| Salalah | 34.52 | 0.88 | 0.92 | 0.77 | 424.28 | 7.32 | 12.42 | 11.72 | 1405.80 | 0.24 | 639.00 | 0.73 |
| Nizwa | 42.02 | 0.86 | 0.80 | 0.65 | 358.28 | 8.86 | 12.70 | 11.97 | 1436.87 | 0.24 | 653.12 | 0.61 |
| Ibra | 40.55 | 0.86 | 0.80 | 0.66 | 360.37 | 8.89 | 12.81 | 12.08 | 1450.14 | 0.24 | 659.16 | 0.62 |
| Shinas | 40.28 | 0.86 | 0.82 | 0.67 | 369.77 | 8.68 | 12.84 | 12.11 | 1452.83 | 0.24 | 660.38 | 0.63 |
| Sur | 41.22 | 0.86 | 0.85 | 0.69 | 381.88 | 8.88 | 13.56 | 12.79 | 1534.98 | 0.26 | 697.72 | 0.65 |
| Ibri | 42.69 | 0.85 | 0.78 | 0.63 | 348.40 | 9.26 | 12.90 | 12.17 | 1460.30 | 0.24 | 663.77 | 0.60 |
| Al Mussanah | 41.03 | 0.86 | 0.82 | 0.67 | 368.68 | 8.99 | 13.26 | 12.50 | 1500.27 | 0.25 | 681.94 | 0.63 |
| UTAS branches | Tavg-temp (approx..) | PVderate-temp | PVderate-dirt | PVderated | Pderated (W) | Parray (kW) | Pac (kW) | EAC (kWh/Ns*) |
CF | Especific-yield (kWh/kW) | PR | |
| Muscat | 40.38 | 0.86 | 0.95 | 0.78 | 428.23 | 9.09 | 15.57 | 14.68 | 1761.96 | 0.29 | 800.89 | 0.73 |
| Salalah | 34.52 | 0.88 | 0.95 | 0.80 | 438.12 | 7.32 | 12.83 | 12.10 | 1451.64 | 0.24 | 659.84 | 0.75 |
| Nizwa | 42.02 | 0.86 | 0.95 | 0.77 | 425.46 | 8.86 | 15.08 | 14.22 | 1706.28 | 0.29 | 775.58 | 0.73 |
| Ibra | 40.55 | 0.86 | 0.95 | 0.78 | 427.94 | 8.89 | 15.22 | 14.35 | 1722.04 | 0.29 | 782.75 | 0.73 |
| Shinas | 40.28 | 0.86 | 0.95 | 0.78 | 428.40 | 8.68 | 14.87 | 14.03 | 1683.16 | 0.28 | 765.07 | 0.73 |
| Sur | 41.22 | 0.86 | 0.95 | 0.78 | 426.81 | 8.88 | 15.16 | 14.30 | 1715.56 | 0.29 | 779.80 | 0.73 |
| Ibri | 42.69 | 0.85 | 0.95 | 0.77 | 424.33 | 9.26 | 15.72 | 14.82 | 1778.58 | 0.30 | 808.44 | 0.73 |
| Al Mussanah | 41.03 | 0.86 | 0.95 | 0.78 | 427.13 | 8.99 | 15.36 | 14.48 | 1738.12 | 0.29 | 790.05 | 0.73 |
| UTAS branches | Tavg-temp (approx..) | PVderate-temp | PVderate-dirt | PVderated | Pderated (W) | Parray (kW) | Pac (kW) | EAC (kWh/Nns*) |
CF | Especific-yield (kWh/kW) | PR | ||||
| Muscat | 29.06 | 0.90 | 0.94 | 0.80 | 442.62 | 7.11 | 12.59 | 11.87 | 2908.36 | 0.24 | 1321.98 | 0.76 | |||
| Salalah | 26.88 | 0.91 | 0.97 | 0.84 | 460.51 | 6.56 | 12.08 | 11.40 | 2791.79 | 0.23 | 1269.00 | 0.79 | |||
| Nizwa | 29.59 | 0.90 | 0.90 | 0.77 | 422.94 | 7.11 | 12.03 | 11.34 | 2779.03 | 0.23 | 1263.19 | 0.73 | |||
| Ibra | 28.13 | 0.90 | 0.90 | 0.77 | 425.27 | 7.18 | 12.21 | 11.52 | 2821.88 | 0.23 | 1282.67 | 0.73 | |||
| Shinas | 28.91 | 0.90 | 0.91 | 0.78 | 428.74 | 7.01 | 12.02 | 11.34 | 2777.51 | 0.23 | 1262.50 | 0.74 | |||
| Sur | 29.83 | 0.90 | 0.94 | 0.80 | 441.34 | 7.05 | 12.45 | 11.74 | 2875.43 | 0.24 | 1307.02 | 0.76 | |||
| Ibri | 28.11 | 0.90 | 0.90 | 0.77 | 425.31 | 7.23 | 12.30 | 11.60 | 2841.74 | 0.23 | 1291.70 | 0.73 | |||
| Al Mussanah | 29.06 | 0.90 | 0.92 | 0.79 | 433.20 | 7.03 | 12.18 | 11.49 | 2814.45 | 0.23 | 1279.29 | 0.74 | |||
| UTAS branches | Tavg-temp (approx..) |
PVderate-temp | PVderate-dirt | PVderated | Pderated (W) | Parray (kW) | Pac (kW) | EAC (kWh/Nns*) |
CF | Especific-yield (kWh/kW) | PR | |
| Muscat | 29.06 | 0.90 | 0.97 | 0.83 | 456.75 | 7.11 | 12.99 | 12.25 | 3001.18 | 0.25 | 1364.17 | 0.78 |
| Salalah | 26.88 | 0.91 | 0.97 | 0.84 | 460.51 | 6.56 | 12.08 | 11.40 | 2791.79 | 0.23 | 1269.00 | 0.79 |
| Nizwa | 29.59 | 0.90 | 0.97 | 0.83 | 455.84 | 7.11 | 12.96 | 12.23 | 2995.17 | 0.25 | 1361.44 | 0.78 |
| Ibra | 28.13 | 0.90 | 0.97 | 0.83 | 458.35 | 7.18 | 13.16 | 12.41 | 3041.36 | 0.25 | 1382.43 | 0.79 |
| Shinas | 28.91 | 0.90 | 0.97 | 0.83 | 457.01 | 7.01 | 12.81 | 12.08 | 2960.64 | 0.24 | 1345.75 | 0.78 |
| Sur | 29.83 | 0.90 | 0.97 | 0.83 | 455.42 | 7.05 | 12.84 | 12.11 | 2967.20 | 0.24 | 1348.73 | 0.78 |
| Ibri | 28.11 | 0.90 | 0.97 | 0.83 | 458.39 | 7.23 | 13.26 | 12.50 | 3062.77 | 0.25 | 1392.17 | 0.79 |
| Al Mussanah | 29.06 | 0.90 | 0.97 | 0.83 | 456.75 | 7.03 | 12.84 | 12.11 | 2967.41 | 0.24 | 1348.82 | 0.78 |
| Design Flow | Selection of Devices / Set the parameters |
|---|---|
|
Input Data for Location and Resources: Set the location of the university. Download weather file data and calculate the annual averages of solar irradiance for that location. |
Refer Table 3 |
|
Panel selection Select the suitable panel from the panel database |
Alexus Solar ALEX-550-b-72-S |
|
Inverter selection Select the suitable inverter from the inverter database |
Inverter HMS-2000-4T-NA |
|
Design a System: Set the number of inverters. Configure the number of panels per string in the subarray Set tracking and orientation. |
Number of Inverters: 1 Panels per string in sub array: 1 Number of Panels in sub array: 4 Tilt angle = Latitude angle Azimuth =180 degree Tracking = Fixed |
|
Calculate losses: Irradiance loss due to soiling, DC loss, AC loss, Transformer loss, Transmission loss Set the percentage of soiling loss |
Soiling losses = 5 % DC wiring loss = 3% AC loss = 1% |
| Set grid limit | It is set to export the power when it is not utilised. |
| Set annual Degradation rate | 5% |
| Installation cost Set investment cost: Set operation and maintenance cost Set inflation rate, real discount rate Set sales tax and incentives |
Investment cost = $4320 Operation and maintenance cost : 43.2 $/kW-yr Indirect capital cost, inflation rate, real discount rate = $0 Sales Tax = $0 |
| Upload Electricity Tariff | [46] |
| Upload smart bus stop load | Table 4 |
| Simulate the software and collect the summary report | |
| Country | Policies Followed | Findings | Reference |
|---|---|---|---|
| Germany | Feed in Tariff (FiT) | Series of legalization has been applied for most effective feed in tariff. | [55-56] |
| Market Incentive Program |
Bank provides extra funding for small size renewable powered installation. | [57-58] | |
| Hauswende policy | Low-interest rate loans to renovate their buildings to install solar panels. | [59] | |
| Solar energy auction |
Instead of FiT, solar PV developers can participate in competitive auctions to sell their solar generated electricity. | [60] | |
| China | Renewable Energy law | In 2005, government framed renewable energy law under this the following mechanism established: 1. Ensures the market scale and direct investment of renewable energy by protecting strong policy. 2. Framed purchase policies to grid companies to purchase all renewable electricity. 3. Renewable energy producers favored feed in tariff system. 4. Introduced a cost sharing mechanism to sell renewable electricity to the utilities and end users. 5. The renewable energy special fund to support renewable energy research projects. | [61-62] |
| The brightness program and Township Electrification Program | In 1996, The brightness program provided 100W per person on daily basis through solar PV and wind power to the un electrified area. In 2002 Township electrification program provided standalone solar PV to the un electrified towns. | [62] | |
| Solar subsidy Program | Solar Roof Program: In 2009, rooftop subsidy program provides a subsidy for less than 50 kW rooftop system includes on grid inverter, battery and solar PV. Golden sun demonstration Program: In 2009, this program provides 50% subsidy for the on grid solar PV installation cost and 70% for the off grid solar PV installation cost for more than 300kW system size. |
[63] | |
| Poverty Alleviation Program | This program provides financial help to poor regions by installing rooftop solar PV on their homes and community building and sell the solar PV electricity to the grid and the revenue is shared with the participating homeowners. For installation of solar PV, they can get subsidy 3000 yuan from Government and 70% loan from bank. | [64] | |
| Feed in Tariff | In 2011, national wide stable and fixed FiT policy provides the FiT price is higher than the concession bidding process rate. This FiT rate is vary based on the location and type of renewable energy. | [65] | |
| Free grid connection services | The state grid corporation of China provides the free connection services such as technological assistance, equipment testing, grid integration plan for the installed capacities of less than 6 MW to help struggling domestic solar PV industry. | [62] | |
| USA | Energy Policy Act 2005 | In 2005, this policy provided a 30% investment tax credit for PV system investment. This act was complemented by accelerated depreciation, which was approximately 26% to the tax benefit. It reduces the system cost approximately 56 % over six period of many investors. | [65-67] |
| Solar America Initiative | In 2007, under this scheme 13.7 million USD sponsored to eleven university led advanced solar PV projects in manufacturing process and products. | [68] | |
| Sun shot initiative | In 2011, this program helped to reduce the cost of solar installation and supported the growth of solar energy as a viable mainstream power source. | [69-70] | |
| Greenhouse gas reduction fund - Solar for all program | A part of this fund is aimed to support the under privileged community, low income group to benefit from distributed solar energy. | [71] | |
| State incentives | Each state have different incentives, financing options like state tax credits, performance based incentives and solar renewable energy certificates which solar electricity provider can sell. | [72] | |
| Feed in Tariff | Each state has different feed in Tariff. Through net metering policy, home owners can sell their extra solar electricity. | [73] | |
| Japan | Feed in tariff | In 2012 new FiT scheme was introduced for ten to twenty years contract, it is fixed and above market rate. | [74] |
| National subsidy program | The government introduced in 1994 for residential installation of solar PV. This subsidy was covered 50 % of the installation cost for installed capacity maximum up to 5kW. | [75] | |
| Zero energy houses | One way for zero energy houses is installing solar PV systems on their building. Building owners receive subsidies under this scheme to construct and renovate their houses to Zero energy houses | [76-77] | |
| India | Rooftop Solar Programme Phase-II subsidy | It offers financial incentives for the rooftop solar PVinstallation. Homeowners can receive up to 40% Capital subsidy for system up to 3kW and 20% subsidy for system between 3kW and 10kW. | [78] |
| Net metering policy | This scheme provides to the homeowners can export the solar electricity to the grid and receive credits on their electricity bills. | [79] |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).