skip to main content

Electrical power output potential of different solar photovoltaic systems in Tanzania

1Nelson Mandela African Institution of Science and Technology (NM-AIST), School of Materials, Energy, Water and Environmental Sciences (MEWES), Tanzania, United Republic of

2Sokoine University of Agriculture, Department of Forest Engineering and Wood Sciences, Tanzania, United Republic of

Received: 18 Oct 2023; Revised: 16 Apr 2024; Accepted: 5 May 2024; Available online: 11 May 2024; Published: 1 Jul 2024.
Editor(s): H Hadiyanto
Open Access Copyright (c) 2024 The Author(s). Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Abstract

This study examines the photovoltaic (PV) energy output and levelized cost of energy (LCOE) in seven regions of Tanzania across five different tilt adjustments of 1 MW PV systems. The one-diode model equations and the PVsyst 7.2 software were used in the simulation. The results reveal variations in energy output and LCOE among the regions and tilt adjustments indicating a strong correlation between PV energy output and solar irradiance incident on the PV panel. For horizontal mounting, the annual energy output ranges from 1229 MWh/year in Kilimanjaro to 1977 MWh/year in Iringa. Among the three optimal tilt adjustments, annually, monthly and seasonal, the last two are predicted to yield larger energy outputs, whereas the two axis tracking configuration consistently provides the maximal energy output in all regions, ranging from 1533 MWh/year in Kilimanjaro to 2762 MWh/year in Iringa. The LCOE analysis demonstrates the cost-effectiveness of solar PV systems compared to grid-connected and isolated mini-grid tariffs. The LCOE values across the regions and tilt adjustments range from $0.07/kWh to $0.16/kWh. In comparison, the tariff for grid-connected solar PV is $0.165/kWh, while for isolated mini-grids; it is $0.181/kWh. The monthly optimal tilt configuration proves to be the most cost-effective option for energy generation in multiple regions, as it consistently exhibits the lowest energy cost compared to the other four configurations. The results provide valuable insights into the performance and economic feasibility of various system setups. Through meticulous simulation and data analysis, we have gained a comprehensive understanding of the factors influencing energy generation and costs in the context of solar photovoltaic systems.

Fulltext View|Download
Keywords: Solar PV; system configuration; energy output; energy cost; Tanzania

Article Metrics:

  1. Alfayo, R. and Uiso, C. (2002). Global solar radiation distribution and available solar energy potential in Tanzania. Physica Scripta. 2002(T97): 91. https://iopscience.iop.org/article/10.1238/Physica.Topical.097a00091/pdf
  2. Barbose, G.L., Elmallah, S. and Gorman, W. (2021). Behind the meter solar+ storage: Market data and trends. LBL Publications, p. 44. https://escholarship.org/content/qt8vk3h91x/qt8vk3h91x.pdf
  3. Chouder, A., Silvestre, S., Sadaoui, N. and Rahmani, L. (2012). Modeling and simulation of a grid connected PV system based on the evaluation of main PV module parameters. Simulation Modelling Practice and Theory. 20(1), 46-58. https://doi.org/10.1016/j.simpat.2011.08.011
  4. Dubey, S., Sarvaiya, J.N. and Seshadri, B. (2013). Temperature dependent photovoltaic (PV) efficiency and its effect on PV production in the world–a review. Energy Procedia. 33, 311-321. https://doi.org/10.1016/j.egypro.2013.05.072
  5. Duffie, J.A., Beckman, W.A. and Blair, N. (2020). Solar engineering of thermal processes, photovoltaics and wind. John Wiley & Sons. 919pp. https://doi.org/10.1002/9781119540328
  6. Fu, R., Feldman, D.J. and Margolis, R.M. (2018). US solar photovoltaic system cost benchmark: Q1 2018. National Renewable Energy Lab.(NREL), Golden, CO (United States). 63pp. https://www.nrel.gov/docs/fy19osti/72399.pdf
  7. Gurupira, T. and Rix, A. (Ed.) (2017). Pv simulation software comparisons: Pvsyst, nrel sam and pvlib. In: Conf.: saupec, 2017. https://orcun.baslak.com/wp-content/uploads/2020/12/SAUPEC_2017_paper_165.pdf
  8. Hernández-Moro, J. and Martinez-Duart, J.M. (2013). Analytical model for solar PV and CSP electricity costs: Present LCOE values and their future evolution. Renewable and Sustainable Energy Reviews. 20, 119-132. http://dx.doi.org/10.1016/j.rser.2012.11.082
  9. Hernandez, R.R., Easter, S., Murphy-Mariscal, M.L., Maestre, F.T., Tavassoli, M., Allen, E.B., Barrows, C.W., Belnap, J., Ochoa-Hueso, R., Ravi, S. (2014). Environmental impacts of utility-scale solar energy. Renewable and Sustainable Energy Reviews. 29,766-779. https://doi.org/10.1016/j.rser.2013.08.041
  10. IEC (1998). Photovoltaic system performance monitoring-Guidelines for measurement, data exchange and analysis. BS EN. 61724. https://law.resource.org/pub/in/bis/S05/is.iec.61724.1998.pdf
  11. Iheanetu, K.J. (2022). Solar Photovoltaic Power Forecasting: A Review. Sustainability. 14(24), 17005. https://doi.org/10.3390/su142417005
  12. Ilyushin, P.V., Shepovalova, O.V., Filippov, S.P. and Nekrasov, A.A. (2021). Calculating the sequence of stationary modes in power distribution networks of Russia for wide-scale integration of renewable energy based installations. Energy Reports. 7, 308-327. https://doi.org/10.1016/j.egyr.2021.07.118
  13. Jacobson, M.Z. and Jadhav, V. (2018). World estimates of PV optimal tilt angles and ratios of sunlight incident upon tilted and tracked PV panels relative to horizontal panels. Solar Energy. 169, 55-66. https://doi.org/10.1016/j.solener.2018.04.030
  14. Jagadale, P.R., Choudhari, A.B. and Jadhav, S.S. (2022). Design and simulation of grid connected solar Si-poly photovoltaic plant using PVsyst for Pune, India location. Renewable Energy Research and Applications. 3(1), 41-49. https://doi.org/10.22044/rera.2021.11057.1069
  15. Khalid, A.M., Mitra, I., Warmuth, W. and Schacht, V. (2016). Performance ratio–Crucial parameter for grid connected PV plants. Renewable and Sustainable Energy Reviews. 65, 1139-1158. https://doi.org/10.1016/j.rser.2016.07.066
  16. Komilov, A. (2021). Location and orientation based LCOE: Simplified visual analysis and generalization of the levelized cost of electricity from storageless photovoltaic systems. International Journal of Energy Research. 45(4), 5649-5658. https://doi.org/10.1002/er.6190
  17. Kumi, E.N. and Brew-Hammond, A. (2013). Design and analysis of a 1 MW grid-connected solar PV system in Ghana. African Technology Policy Studies Network, ATPS, p. 24. https://policycommons.net/artifacts/1446554/design-and-analysis-of-a-1-mw-grid-connected-solar-pv-system-in-ghana/2078321/
  18. Lane, C. (2020). What Is a Solar Tracker and Is It Worth the Investment? Hämtat från Solar Reviews: https://www.solarreviews.com/
  19. Mayanjo, S. and Justo, J. (2023). Development of Solar PV Systems for Mini-Grid Applications in Tanzania. Tanzania Journal of Engineering and Technology. 42(1), 200-212. https://doi.org/10.52339/tjet.v42i1.899
  20. Mesquita, D.d.B., Silva, J.L.d.S., Moreira, H.S., Kitayama, M. and Villalva, M.G. (Ed.) (2019). A review and analysis of technologies applied in PV modules. In: 2019 IEEE PES Innovative Smart Grid Technologies Conference-Latin America (ISGT Latin America). IEEE, pp. 1-6, 2019. https://www.researchgate.net/profile/Joao-Lucas-De-Souza-Silva/publication/337195909_
  21. Milosavljević, D.D., Kevkić, T.S. and Jovanović, S.J. (2022). Review and validation of photovoltaic solar simulation tools/software based on case study. Open Physics. 20(1), 431-451. https://doi.org/10.1515/phys-2022-0042
  22. Perez, R., Ineichen, P., Seals, R. and Zelenka, A. (1990). Making full use of the clearness index for parameterizing hourly insolation conditions. Solar Energy. 45(2), 111-114. https://doi.org/10.1016/0038-092X(90)90036-C
  23. PVsyst, S.2023. PVsyst Help Content. https://www.pvsyst.com/help/index.html?contents_table.htm. Accessed on 17/07 2023
  24. Ramasamy, V., Feldman, D., Desai, J. and Margolis, R. (2021). US solar photovoltaic system and energy storage cost benchmarks: Q1 2021. National Renewable Energy Lab.(NREL), Golden, CO (United States). 63pp. https://www.osti.gov/biblio/1829460
  25. Sadeq, M. and Abdellatif, S. (2021). PV‐ON: An online/bilingual PV sizing tool for grid‐connected system, case studies in Egypt. International Transactions on Electrical Energy Systems. 31(7), 12910. https://onlinelibrary.wiley.com/doi/abs/10.1002/2050-7038.12910
  26. Sagonda, A.F. and Folly, K.A. (Ed.) (2019). Maximum power point tracking in solar PV under partial shading conditions using stochastic optimization techniques. In: 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE, pp. 1967-1974, 2019. https://ieeexplore.ieee.org/abstract/document/8790105
  27. Sohail, M., Afrouzi, H.N., Mehranzamir, K., Ahmed, J., Siddique, M.B.M. and Tabassum, M. (2022). A comprehensive scientometric analysis on hybrid renewable energy systems in developing regions of the world. Results in Engineering. 16, 100481. https://doi.org/10.1016/j.rineng.2022.100481
  28. Stapleton, G. and Neill, S. (2012). Grid-connected solar electric systems: the earthscan expert handbook for planning, design and installation. Routledge. 244pp. https://doi.org/10.4324/9780203588628
  29. Tanu, M., Amponsah, W., Yahaya, B., Bessah, E., Ansah, S.O., Wemegah, C.S. and Agyare, W.A. (2021). Evaluation of global solar radiation, cloudiness index and sky view factor as potential indicators of Ghana's solar energy resource. Scientific African. 14(61). https://doi.org/10.1016/j.sciaf.2021.e01061
  30. Tyagi, V., Rahim, N.A., Rahim, N., Jeyraj, A. and Selvaraj, L. (2013). Progress in solar PV technology: Research and achievement. Renewable and Sustainable Energy Reviews. 20, 443-461. https://doi.org/10.1016/j.rser.2012.09.028
  31. TMA. 1999. Tanzania Meteorogocal Agency. TMA. https://www.idare-portal.org/sites/default/files/I-DARE_PORTAL_TANZANIA.pdf. Accessed on 9/12/2019 2019
  32. Westbrook, O.W. and Collins, F.D. (Ed.) (2013). Energy model validation for large-scale photovoltaic systems. In: 2013 IEEE 39th Photovoltaic Specialists Conference (PVSC). IEEE, pp. 0830-0835, 2013. https://ieeexplore.ieee.org/abstract/document/6744274
  33. Wiser, R.H., Bolinger, M. and Seel, J. (2020). Benchmarking utility-scale PV operational expenses and project lifetimes: results from a survey of US solar industry professionals. Lawrence Berkeley National Lab.(LBNL), Berkeley, CA (United States). 9pp. https://escholarship.org/uc/item/2pd8608q
  34. Wood, M. and SEIA. 2021. U.S. Solar Market Insight Report, Q2 2021. Solar Energy Industries Association. https://www.woodmac.com/industry/power-and-renewables/us-solar-market-insight/. Accessed on October 4 2021
  35. Yakubu, R.O., Ankoh, M.T., Mensah, L.D., Quansah, D.A. and Adaramola, M.S. (2022). Predicting the potential energy yield of bifacial solar PV systems in low-latitude region. Energies. 15(22), 8510. https://www.mdpi.com/1996-1073/15/22/8510
  36. Zazoum, B. (2022). Solar photovoltaic power prediction using different machine learning methods. Energy Reports. 8, 19-25. https://doi.org/10.1016/j.egyr.2021.11.183

Last update:

No citation recorded.

Last update: 2024-11-04 23:43:49

No citation recorded.