Optimal Investment Strategy for Solar PV Integration in Residential Buildings: A Case Study in The Philippines

Charmaine Samala Guno orcid scopus  -  College of Teacher Education, Mindoro State College of Agriculture and Technology, Calapan City, Philippines
*Casper Boongaling Agaton orcid scopus  -  Utrecht University School of Economics, Utrecht University, Utrecht;, Netherlands
Resy Ordona Villanueva orcid scopus  -  Senior High School Department, Ceriaco A. Abes Memorial National High School, Calapan City, Philippines
Riza Ordona Villanueva orcid scopus  -  English Department, Oriental Mindoro National High School, Calapan City, Philippines
Received: 3 Sep 2020; Revised: 13 Oct 2020; Accepted: 20 Oct 2020; Published: 1 Feb 2021; Available online: 25 Oct 2020.
Open Access Copyright (c) 2021 The Authors. 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

In developing countries, particularly in rural areas, long periods of power outages are experienced as the electricity grid is technically or economically unfeasible.  As solar photovoltaic (PV) is the most potential and suitable source of renewable energy for these areas, this paper analyzes the economic viability of its integration in different types of residential buildings. Applying real optionsapproach under uncertainty in electricity prices, this study compares the attractiveness of adopting solar PV over continuing electricity from the grid focusing on various investment payment schemes including (i) full payment, (ii) distributed payment for 5 or 10 years without a down payment, and (iii) distributed payment for 5 or 10 years with 20% or 40% down payment. Applying the model with the case of the Philippines, the resultswith the full payment strategy obtain option values of USD 6888 for building type-I, USD 15349 for building type-II, USD 21204 for building type-III, USD 27870 for building type-IV, and USD 34251 for building type-V. These option values increase by 21.6% and 22.5% with distributed payment scheme to a 5- or 10-year period and increase by 5% and 13% for distributed payment with 40% and 20% down payment. These option values decrease with investments at later periods. Contrary to the conventional option valuation results of an optimal decision to wait, our findings show the otherwise as earlier investment reduces the risk of opportunity loss from delaying the adoption of solar PV. Among the payment schemes analyzed, the distribution of PV system cost in a 10-year installment periodwithout down payment shows to be the most optimal investment strategy which may encourage lower-income and risk-averse consumers whose decision to adopt solar PV is affected by cost barriers, economic status, and household income. The study suggests the government, particularly in developing countries, to support the integration of own-use solar PV in buildings through incentives and subsidies, as well as financial institutions to offer more affordable terms of payment that encourages low to medium income households to adopt solar PV.Further, this will not only augment the energy deficiency in these countries but also support the global aspirations of reducing greenhouse gas emissions and its adverse effects through gradually shifting to renewable sources of energy.

Keywords: investment strategy; investment under uncertainty; real options; renewable energy; residential building; solar PV
Funding: Utrecht University; Mindoro State College of Agriculture and Technology

Article Metrics:

Article Info
Section: Original Research Article
Language: EN
In Vol 10, No 1 (2021): February 2021
Statistics: 1231 444
Related articles
Techno-Economic Evaluation of Solar Irrigation Plants Installed in Bangladesh Techno-Economic Analysis for Bioethanol Plant with Multi Lignocellulosic Feedstocks Solmap: Project In India's Solar Resource Assessment Tax Incentive Policy for Geothermal Development: A Comparative Analysis in ASEAN Analysing the Possibility of Extracting Energy from Ocean Waves in Cabo-Verde to Produce Clean Electricity - Case-Study: the Leeward Islands VCO Production from Fresh Old Coconut Bunch by Circulating and Pumping Method
  1. Abensur, E. O., Moreira, D. F., & de Faria, A. C. R. (2020). Geometric Brownian motion: an alternative to high-frequency trading for small investors. Independent Journal of Management & Production, 11(3), 1434-1453. http://dx.doi.org/10.14807/ijmp.v11i3.1114
  2. Abdul-Wahab, S., Charabi, Y., Al-Mahruqi, A. M., Osman, I., & Osman, S. (2019). Selection of the best solar photovoltaic (PV) for Oman. Solar Energy, 188, 1156-1168. https://doi.org/10.1016/j.solener.2019.07.018
  3. Abdul-Wahab, S., Mujezinovic, K., & Al-Mahruqi, A. M. (2019). Optimal design and evaluation of a hybrid energy system for off-grid remote area. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 1-13. https://doi.org/10.1080/15567036.2019.1656308
  4. Adebayo, V., & Koçyiğit, K. (2017) Techno-economic Analysis of an Off-grid Solar Photovoltaic Energy System for a Typical Rural Household in Adamawa State, Nigeria. https://www.researchgate.net/publication/319470224_Techno-economic_Analysis_of_an_Off-grid_Solar_Photovoltaic_Energy_System_for_a_Typical_Rural_Household_in_Adamawa_State_Nigeria
  5. Agaton, C. B. (2018). Use coal or invest in renewables: a real options analysis of energy investments in the Philippines. Renewables: Wind, Water, and Solar, 5(1), 1-8. https://doi.org/10.1186/s40807-018-0047-2
  6. Agaton, C. B., Collera, A. A., & Guno, C. S. (2020). Socio-Economic and Environmental Analyses of Sustainable Public Transport in the Philippines. Sustainability, 12(11), 4720. https://doi.org/10.3390/su12114720
  7. Agaton, C. B., & Karl, H. (2018). A real options approach to renewable electricity generation in the Philippines. Energy, Sustainability and Society, 8(1), 1. https://doi.org/10.1186/s13705-017-0143-y
  8. Agaton, C. B., Guno, C. S., Villanueva, R. O., & Villanueva, R. O. (2019). Diesel or Electric Jeepney? A Case Study of Transport Investment in the Philippines Using the Real Options Approach. World Electric Vehicle Journal, 10(3), 51. https://doi.org/10.3390/wevj10030051
  9. Agaton, C. B., Guno, C. S., Villanueva, R. O., & Villanueva, R. O. (2020). Economic analysis of waste-to-energy investment in the Philippines: A real options approach. Applied Energy, 275, 115265. https://doi.org/10.1016/j.apenergy.2020.115265
  10. Allouhi, A. (2020). Solar PV integration in commercial buildings for self-consumption based on life-cycle economic/environmental multi-objective optimization. Journal of Cleaner Production, 122375. https://doi.org/10.1016/j.jclepro.2020.122375
  11. Andreis, L., Flora, M., Fontini, F., & Vargiolu, T. (2020). Pricing Reliability Options under different electricity price regimes. Energy Economics, 87, 104705. https://doi.org/10.1016/j.eneco.2020.104705
  12. Bertolini, M., D'Alpaos, C., & Moretto, M. (2018). Do Smart Grids boost investments in domestic PV plants? Evidence from the Italian electricity market. Energy, 149, 890-902. https://doi.org/10.1016/j.energy.2018.02.038
  13. Borovkova, S., & Schmeck, M. D. (2017). Electricity price modeling with stochastic time change. Energy Economics, 63, 51-65. https://doi.org/10.1016/j.eneco.2017.01.002
  14. Cheng, C., Wang, Z., Liu, M., Chen, Q., Gbatu, A. P., & Ren, X. (2017). Defer option valuation and optimal investment timing of solar photovoltaic projects under different electricity market systems and support schemes. Energy, 127, 594-610. https://doi.org/10.1016/j.energy.2017.03.157
  15. D’Adamo, I. (2018). The profitability of residential photovoltaic systems. A new scheme of subsidies based on the price of CO2 in a developed PV market. Social Sciences, 7(9), 148. https://doi.org/10.3390/socsci7090148
  16. D’Adamo, I., Falcone, P. M., Gastaldi, M., & Morone, P. (2020). The economic viability of photovoltaic systems in public buildings: Evidence from Italy. Energy, 207, 118316. https://doi.org/10.1016/j.energy.2020.118316
  17. De Schepper, E., Van Passel, S., & Lizin, S. (2015). Economic benefits of combining clean energy technologies: the case of solar photovoltaics and battery electric vehicles. International journal of energy research, 39(8), 1109-1119. https://doi.org/10.1002/er.3315
  18. Do, T. N., Burke, P. J., Baldwin, K. G., & Nguyen, C. T. (2020). Underlying drivers and barriers for solar photovoltaics diffusion: The case of Vietnam. Energy Policy, 144, 111561. https://doi.org/10.1016/j.enpol.2020.111561
  19. DOE (Department of Energy) 2019. Philippine Power Statistics. https://www.doe.gov.ph/sites/default/files/pdf/energy_statistics/2019_power_statistic_01_summary.pdf Accessed 20 March 2020.
  20. Ellabban, O., & Alassi, A. (2019). Integrated Economic Adoption Model for residential grid-connected photovoltaic systems: An Australian case study. Energy Reports, 5, 310-326. https://doi.org/10.1016/j.egyr.2019.02.004
  21. Enteria, N., Awbi, H., & Yoshino, H. (2015). Application of renewable energy sources and new building technologies for the Philippine single family detached house. International Journal of Energy and Environmental Engineering, 6(3), 267-294. https://doi.org/10.1007/s40095-015-0174-0
  22. Gahrooei, M. R., Zhang, Y., Ashuri, B., & Augenbroe, G. (2016). Timing residential photovoltaic investments in the presence of demand uncertainties. Sustainable Cities and Society, 20, 109-123. https://doi.org/10.1016/j.scs.2015.10.003
  23. Gazheli, A., & van den Bergh, J. (2018). Real options analysis of investment in solar vs. wind energy: Diversification strategies under uncertain prices and costs. Renewable and Sustainable Energy Reviews, 82, 2693-2704. https://doi.org/10.1016/j.rser.2017.09.096
  24. GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH) 2013. “It’s more sun in the Philippines. Available from https://www.doe.gov.ph/sites/default/files/pdf/netmeter/policy-brief-its-more-sun-in-the-philippines-V3.pdf
  25. Guta, D. D. (2018). Determinants of household adoption of solar energy technology in rural Ethiopia. Journal of Cleaner Production, 204, 193-204. https://doi.org/10.1016/j.jclepro.2018.09.016
  26. Hagerman, S., Jaramillo, P., & Morgan, M. G. (2016). Is rooftop solar PV at socket parity without subsidies?. Energy Policy, 89, 84-94. https://doi.org/10.1016/j.enpol.2015.11.017
  27. IEA (International Energy Agency) 2019. Renewables 2019: Market analysis and forecast from 2019 to 2024. https://www.iea.org/reports/renewables-2019 Accessed on 12 Aug 2020
  28. IEA (International Energy Agency) 2020. Tracking Buildings. https://www.iea.org/reports/tracking-buildings-2020 Accessed on 27 July 2020
  29. Ioannou, A., Angus, A., & Brennan, F. (2018). Effect of electricity market price uncertainty modelling on the profitability assessment of offshore wind energy through an integrated lifecycle techno-economic model. J Physics: Conference Series, 1102(1), 012027. https://doi.org/10.1088/1742-6596/1102/1/012027
  30. IRENA (International Renewable Energy Agency) 2017. Renewables Readiness Assessment: The Philippines. https://www.irena.org/publications/2017/Mar/Renewables-Readiness-Assessment-The-Philippines Accessed on 12 Aug 2020
  31. Jäger-Waldau, A., Kougias, I., Taylor, N., & Thiel, C. (2020). How photovoltaics can contribute to GHG emission reductions of 55% in the EU by 2030. Renewable and Sustainable Energy Reviews, 126, 109836. https://doi.org/10.1016/j.rser.2020.109836
  32. Kabir, E., Kim, K. H., & Szulejko, J. E. (2017). Social impacts of solar home systems in rural areas: A case study in Bangladesh. Energies, 10(10), 1615. https://doi.org/10.3390/en10101615
  33. Kavlak, G., McNerney, J., & Trancik, J. E. (2018). Evaluating the causes of cost reduction in photovoltaic modules. Energy policy, 123, 700-710. https://doi.org/10.1016/j.enpol.2018.08.015
  34. Khan, T., Khanam, S. N., Rahman, M. H., & Rahman, S. M. (2019). Determinants of microfinance facility for installing solar home system (SHS) in rural Bangladesh. Energy Policy, 132, 299-308. https://doi.org/10.1016/j.enpol.2019.05.047
  35. Krungkaew, S., Kingphadung, K., Kwonpongsagoon, S., & Mahayothee, B. (2020). Costs and benefits of using parabolic greenhouse solar dryers for dried herb products in Thailand. International Journal of GEOMATE, 18(67), 96-101. https://doi.org/10.21660/2020.67.5798
  36. Liang, J., Shirsat, A., & Tang, W. (2020). Sustainable community-based PV-storage planning using the Nash bargaining solution. International Journal of Electrical Power & Energy Systems, 118, 105759. https://doi.org/10.1016/j.ijepes.2019.105759
  37. Lin, B., & Chen, Y. (2019). Does electricity price matter for innovation in renewable energy technologies in China? Energy Economics, 78, 259-266. https://doi.org/10.1016/j.eneco.2018.11.014
  38. Matsuo, T. (2019). Fostering grid-connected solar energy in emerging markets: The role of learning spillovers. Energy Research & Social Science, 57, 101227. https://doi.org/10.1016/j.erss.2019.101227
  39. McKenna, E., Pless, J., & Darby, S. J. (2018). Solar photovoltaic self-consumption in the UK residential sector: New estimates from a smart grid demonstration project. Energy Policy, 118, 482-491. https://doi.org/10.1016/j.enpol.2018.04.006
  40. Mehta, P., Griego, D., Nunez-Jimenez, A., & Schlueter, A. (2019). The Impact of self-consumption regulation on individual and community solar PV adoption in Switzerland: an agent-based model. In Journal of Physics: Conference Series (Vol. 1343, No. 1, p. 012143). IOP Publishing. https://doi.org/10.1088/1742-6596/1343/1/012143
  41. Moon, Y., & Baran, M. (2018). Economic analysis of a residential PV system from the timing perspective: A real option model. Renewable energy, 125, 783-795. https://doi.org/10.1016/j.renene.2018.02.138
  42. Nemet, G. F., Lu, J., Rai, V., & Rao, R. (2020). Knowledge spillovers between PV installers can reduce the cost of installing solar PV. Energy Policy, 144, 111600. https://doi.org/10.1016/j.enpol.2020.111600
  43. O'Shaughnessy, E., Cutler, D., Ardani, K., & Margolis, R. (2018). Solar plus: A review of the end-user economics of solar PV integration with storage and load control in residential buildings. Applied energy, 228, 2165-2175. https://doi.org/10.1016/j.apenergy.2018.07.048
  44. Palm, J. (2018). Household installation of solar panels–Motives and barriers in a 10-year perspective. Energy Policy, 113, 1-8. https://doi.org/10.1016/j.enpol.2017.10.047
  45. Penizzotto, F., Pringles, R., & Olsina, F. (2019). Real options valuation of photovoltaic power investments in existing buildings. Renewable and Sustainable Energy Reviews, 114, 109308. https://doi.org/10.1016/j.rser.2019.109308
  46. Pode, R. (2013). Financing LED solar home systems in developing countries. Renewable and Sustainable Energy Reviews, 25, 596-629. https://doi.org/10.1016/j.rser.2013.04.004
  47. Purohit, I., Purohit, P., & Shekhar, S. (2013). Evaluating the potential of concentrating solar power generation in Northwestern India. Energy policy, 62, 157-175. https://doi.org/10.1016/j.enpol.2013.06.069
  48. Ren, M., Mitchell, C. R., & Mo, W. (2020). Dynamic life cycle economic and environmental assessment of residential solar photovoltaic systems. Science of The Total Environment, 137932. https://doi.org/10.1016/j.scitotenv.2020.137932
  49. Rodrigues, D. L., Ye, X., Xia, X., & Zhu, B. (2020). Battery energy storage sizing optimisation for different ownership structures in a peer-to-peer energy sharing community. Applied Energy, 262, 114498. https://doi.org/10.1016/j.apenergy.2020.114498
  50. Rodrigues, S., Chen, X., & Morgado-Dias, F. J. E. P. (2017). Economic analysis of photovoltaic systems for the residential market under China's new regulation. Energy Policy, 101, 467-472. https://doi.org/10.1016/j.enpol.2016.10.039
  51. Sagani, A., Mihelis, J., & Dedoussis, V. (2017). Techno-economic analysis and life-cycle environmental impacts of small-scale building-integrated PV systems in Greece. Energy and Buildings, 139, 277-290. https://doi.org/10.1016/j.enbuild.2017.01.022
  52. Schiel, C., Glöser-Chahoud, S., & Schultmann, F. (2019). A real option application for emission control measures. Journal of Business Economics, 89(3), 291-325. https://doi.org/10.1007/s11573-018-0913-9
  53. Spertino, F., Chicco, G., Ciocia, A., Corgnati, S., Di Leo, P., & Raimondo, D. (2015, June). Electricity consumption assessment and PV system integration in grid-connected office buildings. In 2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC) (pp. 255-260). IEEE. https://doi.org/10.1109/EEEIC.2015.7165548
  54. Stankuniene, G., Streimikiene, D., & Kyriakopoulos, G. L. (2020). Systematic Literature Review on Behavioral Barriers of Climate Change Mitigation in Households. Sustainability, 12(18), 7369. https://doi.org/10.3390/su12187369
  55. Streimikiene, D., Lekavičius, V., Baležentis, T., Kyriakopoulos, G. L., & Abrhám, J. (2020). Climate Change Mitigation Policies Targeting Households and Addressing Energy Poverty in European Union. Energies, 13(13), 3389. https://doi.org/10.3390/en13133389
  56. Stoyanov, L., Zarkov, Z., Notton, G., & Lazarov, V. (2020). Design Opportunities and Building Integration of PV systems. In Energy Efficient Building Design (pp. 21-40). Springer, Cham. https://doi.org/10.1007/978-3-030-40671-4_2
  57. Tantisattayakul, T., & Kanchanapiya, P. (2017). Financial measures for promoting residential rooftop photovoltaics under a feed-in tariff framework in Thailand. Energy policy, 109, 260-269. https://doi.org/10.1016/j.enpol.2017.06.061
  58. Tian, L., Pan, J., Du, R., Li, W., Zhen, Z., & Qibing, G. (2017). The valuation of photovoltaic power generation under carbon market linkage based on real options. Applied energy, 201, 354-362. https://doi.org/10.1016/j.apenergy.2016.12.092
  59. Torani, K., Rausser, G., & Zilberman, D. (2016). Innovation subsidies versus consumer subsidies: A real options analysis of solar energy. Energy Policy, 92, 255-269. https://doi.org/10.1016/j.enpol.2015.07.010
  60. Tracking Buildings. International Energy Agency, 2020. Available from: https://www.iea.org/reports/tracking-buildings-2020
  61. Trappey, A. J., Trappey, C. V., Tan, H., Liu, P. H., Li, S. J., & Lin, L. C. (2016). The determinants of photovoltaic system costs: an evaluation using a hierarchical learning curve model. Journal of Cleaner Production, 112, 1709-1716. https://doi.org/10.1016/j.jclepro.2015.08.095
  62. Yadav, P., Heynen, A. P., & Palit, D. (2019). Pay-As-You-Go financing: A model for viable and widespread deployment of solar home systems in rural India. Energy for sustainable development, 48, 139-153. https://doi.org/10.1016/j.esd.2018.12.005
  63. Zeng, Y., & Chen, W. (2020). The socially optimal energy storage incentives for microgrid: A real option game-theoretic approach. Science of The Total Environment, 710, 136199. https://doi.org/10.1016/j.scitotenv.2019.136199
  64. Zhang, M. M., Zhou, P., & Zhou, D. Q. (2016). A real options model for renewable energy investment with application to solar photovoltaic power generation in China. Energy Economics, 59, 213-226. https://doi.org/10.1016/j.eneco.2016.07.028
  65. Zhang, M. M., Wang, Q., Zhou, D., & Ding, H. (2019). Evaluating uncertain investment decisions in low-carbon transition toward renewable energy. Applied Energy, 240, 1049-1060. https://doi.org/10.1016/j.apenergy.2019.01.205
  66. Zhang, X., Shen, J., Adkins, D., Yang, T., Tang, L., Zhao, X., ... & Luo, H. (2015). The early design stage for building renovation with a novel loop-heat-pipe based solar thermal facade (LHP-STF) heat pump water heating system: Techno-economic analysis in three European climates. Energy Conversion and Management, 106, 964-986. https://doi.org/10.1016/j.enconman.2015.10.034

Last update: 2021-01-19 09:25:42

No citation recorded.

Last update: 2021-01-19 09:25:44

No citation recorded.
Copyright (c) 2021 The Authors. 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.

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. Articles are freely available to both subscribers and the wider public with permitted reuse.

All articles published Open Access will be immediately and permanently free for everyone to read and download. We are continuously working with our author communities to select the best choice of license options: Creative Commons Attribution-ShareAlike (CC BY-SA). Authors and readers can copy and redistribute the material in any medium or format, as well as remix, transform, and build upon the material for any purpose, even commercially, but they must give appropriate credit (cite to the article or content), provide a link to the license, and indicate if changes were made. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.