Paragraphs Environmental Design

Seasonal Solar Resource Variability and Its Implications for Residential Photovoltaic Design in Selected Tropical Cities

Review Article · Environmental Design · 2024, Volume 2, Issue 2: 42–58

DOI: 10.5281/zenodo.24158783

Dhanoe Iswanto*

Retired lecturer, Department of Architecture, Universitas Diponegoro

*Correspondence: dhanoe43@hotmail.com

Received: June 2024 | Accepted: August 2024 | Published: September 2024

View / Download PDF

Abstract

Residential photovoltaic design in tropical cities requires an account of when solar energy is available and when households can use it. Annual irradiation provides an essential measure of resource abundance, but it conceals seasonal shortages, persistent cloudy periods, and mismatches between generation and demand. This article critically synthesizes literature published before 1 May 2023 concerning Singapore, Kuala Lumpur, Jakarta, and Bangkok. It combines local observational and modeling studies with established photovoltaic performance and storage methods, while retaining distinctions between regional evidence, site measurements, and analytical inference. The comparison identifies different design questions within a shared tropical setting: uncertain orientation gains under equatorial cloudiness, spatially differentiated Malaysian seasonality, modeled wet-season exposure in Jakarta, and the interaction of Thailand's monsoon cycle with temperature and demand. A proposed assessment framework separates annual yield, monthly energy adequacy, and chronological supply reliability. An explicitly hypothetical calculation demonstrates that identical annual generation can coexist with substantially different seasonal deficits, and that additional battery capacity cannot sustainably compensate for insufficient charging energy. The resulting design approach evaluates roof geometry, demand timing, array capacity, thermal behavior, and storage against a declared service objective. The contribution is a conditional decision framework rather than a ranking of city performance or a new empirical dataset. It supports residential systems that remain useful across uncertain weather and household operating conditions while identifying the measurements required for defensible city-specific optimization.

Keywords: tropical photovoltaics; solar resource seasonality; residential energy; monsoon; battery sizing; self-consumption

Citation

Iswanto D. (2024). Seasonal Solar Resource Variability and Its Implications for Residential Photovoltaic Design in Selected Tropical Cities. Paragraphs Environmental Design, 2(2), 42–58. DOI: 10.5281/zenodo.24158783

References

  1. Aldrian, E., & Susanto, R. D. (2003). Identification of three dominant rainfall regions within Indonesia and their relationship to sea surface temperature. International Journal of Climatology, 23(12), 1435–1452. https://doi.org/10.1002/joc.950
  2. Ayala-Gilardón, A., Sidrach-de-Cardona, M., & Mora-López, L. (2018). Influence of time resolution in the estimation of self-consumption and self-sufficiency of photovoltaic facilities. Applied Energy, 229, 990–997. https://doi.org/10.1016/j.apenergy.2018.08.072
  3. Beck, T., Kondziella, H., Huard, G., & Bruckner, T. (2016). Assessing the influence of the temporal resolution of electrical load and PV generation profiles on self-consumption and sizing of PV-battery systems. Applied Energy, 173, 331–342. https://doi.org/10.1016/j.apenergy.2016.04.050
  4. Dewi, R. G., Siagian, U. W. R., Asmara, B., Anggraini, S. D., Ichihara, J., & Kobashi, T. (2023). Equitable, affordable, and deep decarbonization pathways for low-latitude developing cities by rooftop photovoltaics integrated with electric vehicles. Applied Energy, 332, Article 120507. https://doi.org/10.1016/j.apenergy.2022.120507
  5. Dobos, A. P. (2014). PVWatts version 5 manual (NREL/TP-6A20-62641). National Renewable Energy Laboratory. https://doi.org/10.2172/1158421
  6. Energy Sector Management Assistance Program. (2020). Global photovoltaic power potential by country. World Bank. https://documents1.worldbank.org/curated/en/466331592817725242/pdf/Global-Photovoltaic-Power-Potential-by-Country.pdf
  7. Engel-Cox, J. A., Nair, N. L., & Ford, J. L. (2012). Evaluation of solar and meteorological data relevant to solar energy technology performance in Malaysia. Journal of Sustainable Energy & Environment, 3(3), 115–124. https://so04.tci-thaijo.org/index.php/JSEE/article/download/28885/24861
  8. Faiman, D. (2008). Assessing the outdoor operating temperature of photovoltaic modules. Progress in Photovoltaics: Research and Applications, 16(4), 307–315. https://doi.org/10.1002/pip.813
  9. Janjai, S., Masiri, I., Pattarapanitchai, S., & Laksanaboonsong, J. (2013). Mapping global solar radiation from long-term satellite data in the tropics using an improved model. International Journal of Photoenergy, 2013, Article 210159. https://doi.org/10.1155/2013/210159
  10. Jittayasotorn, T., Sadidah, M., Yoshida, T., & Kobashi, T. (2023). On the adoption of rooftop photovoltaics integrated with electric vehicles toward sustainable Bangkok City, Thailand. Energies, 16(7), Article 3011. https://doi.org/10.3390/en16073011
  11. Jordan, D. C., & Kurtz, S. R. (2013). Photovoltaic degradation rates—An analytical review. Progress in Photovoltaics: Research and Applications, 21(1), 12–29. https://doi.org/10.1002/pip.1182
  12. Khatib, T., Mohamed, A., Mahmoud, M., & Sopian, K. (2015). Optimization of the tilt angle of solar panels for Malaysia. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 37(6), 606–613. https://doi.org/10.1080/15567036.2011.588680
  13. Khoo, Y. S., Nobre, A., Malhotra, R., Yang, D., Rüther, R., Reindl, T., & Aberle, A. G. (2014). Optimal orientation and tilt angle for maximizing in-plane solar irradiation for PV applications in Singapore. IEEE Journal of Photovoltaics, 4(2), 647–653. https://doi.org/10.1109/JPHOTOV.2013.2292743
  14. King, D. L., Boyson, W. E., & Kratochvil, J. A. (2004). Photovoltaic array performance model (SAND2004-3535). Sandia National Laboratories. https://doi.org/10.2172/919131
  15. Liu, H., Nobre, A. M., Yang, D., Ye, J. Y., Martins, F. R., Rüther, R., Reindl, T., Aberle, A. G., & Peters, I. M. (2014). The impact of haze on performance ratio and short-circuit current of PV systems in Singapore. IEEE Journal of Photovoltaics, 4(6), 1585–1592. https://doi.org/10.1109/JPHOTOV.2014.2346429
  16. Luthander, R., Widén, J., Nilsson, D., & Palm, J. (2015). Photovoltaic self-consumption in buildings: A review. Applied Energy, 142, 80–94. https://doi.org/10.1016/j.apenergy.2014.12.028
  17. Nasruddin, Budiyanto, M. A., & Nawara, R. (2018). Comparative study of the monthly global solar radiation estimation data in Jakarta. IOP Conference Series: Earth and Environmental Science, 105(1), Article 012111. https://doi.org/10.1088/1755-1315/105/1/012111
  18. National Environment Agency. (2023, January 30). 2022 was another wet and warm year. https://www.nea.gov.sg/media/news/news/index/2022-was-another-wet-and-warm-year
  19. Nobre, A. M., Karthik, S., Liu, H., Yang, D., Martins, F. R., Pereira, E. B., Rüther, R., Reindl, T., & Peters, I. M. (2016). On the impact of haze on the yield of photovoltaic systems in Singapore. Renewable Energy, 89, 389–400. https://doi.org/10.1016/j.renene.2015.11.079
  20. Perez, R., Ineichen, P., Seals, R., Michalsky, J., & Stewart, R. (1990). Modeling daylight availability and irradiance components from direct and global irradiance. Solar Energy, 44(5), 271–289. https://doi.org/10.1016/0038-092X(90)90055-H
  21. Peters, I. M., Karthik, S., Liu, H., Buonassisi, T., & Nobre, A. (2018). Urban haze and photovoltaics. Energy & Environmental Science, 11(10), 3043–3054. https://doi.org/10.1039/C8EE01100A
  22. Reindl, T., Ouyang, J., Khaing, A. M., Ding, K., Khoo, Y. S., Walsh, T. M., & Aberle, A. G. (2012). Investigation of the performance of commercial photovoltaic modules under tropical conditions. Japanese Journal of Applied Physics, 51(10S), Article 10NF11. https://doi.org/10.1143/JJAP.51.10NF11
  23. Sengupta, M., Habte, A., Wilbert, S., Gueymard, C., & Remund, J. (Eds.). (2021). Best practices handbook for the collection and use of solar resource data for solar energy applications (3rd ed., NREL/TP-5D00-77635). National Renewable Energy Laboratory. https://doi.org/10.2172/1778700
  24. Srikranjanapert, M., Junlakarn, S., & Hoonchareon, N. (2021). How an integration of home energy management and battery system affects the economic benefits of residential PV system owners in Thailand. Sustainability, 13(5), Article 2681. https://doi.org/10.3390/su13052681
  25. Suri, M., Cebecauer, T., Suriova, N., Schnierer, B., Skoczek, A., Betak, J., Madlenakova, V., & Chrkavy, D. (2017). Solar resource and photovoltaic power potential of Indonesia. World Bank Group. https://documents1.worldbank.org/curated/en/729411496240730378/pdf/115347-ESM-P145273-PUBLIC-IndonesiaSolarResourcePotentialWBESMAPMay.pdf
  26. Tongsopit, S., Junlakarn, S., Wibulpolprasert, W., Chaianong, A., Kokchang, P., & Hoang, N. V. (2019). The economics of solar PV self-consumption in Thailand. Renewable Energy, 138, 395–408. https://doi.org/10.1016/j.renene.2019.01.087
  27. Waewsak, J., Chancham, C., Mani, M., & Gagnon, Y. (2014). Estimation of monthly mean daily global solar radiation over Bangkok, Thailand using artificial neural networks. Energy Procedia, 57, 1160–1168. https://doi.org/10.1016/j.egypro.2014.10.103
  28. Weniger, J., Tjaden, T., & Quaschning, V. (2014). Sizing of residential PV battery systems. Energy Procedia, 46, 78–87. https://doi.org/10.1016/j.egypro.2014.01.160
  29. Wilcox, S., & Marion, W. (2008). Users manual for TMY3 data sets (NREL/TP-581-43156). National Renewable Energy Laboratory. https://doi.org/10.2172/928611
  30. Yang, D., & Bright, J. M. (2020). Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years. Solar Energy, 210, 3–19. https://doi.org/10.1016/j.solener.2020.04.016