Barriers to Adoption of Photovoltaic System: A case study from Indonesia
Article Sidebar
Main Article Content
Abstract
The transition to renewable energy is increasingly important. Indonesia encourages the use of solar energy through photovoltaic (PV) technology on the roofs of houses and buildings to achieve the renewable energy mix target. However, the diffusion of PV systems has been slow even after the issuance of government regulations regarding PV systems. This research investigates barriers to PV adoption by Indonesian households. A survey was conducted, resulting in responses from 404 households in Indonesia that had yet to use PV. Only complete answers from respondents with the status of their own house and having the authority to make decisions are included in the analysis. Processing 376 data that met the requirements found that high investment costs were the main barrier to PV adoption, followed by access to installation service providers and lack of information available as the next obstacle. The affordability of distribution centers as information service providers, procurement, installation, and maintenance of PV systems is the most technical support respondents need to be willing to adopt PV systems. On the financial aspect, it is hoped that PV system equipment grants for households in remote areas and subsidies for the procurement of PV systems in the regions that have access to electricity from the State Electricity Company (PLN) are expected to be facilitated. Further research on the effect of financial and technical facilitation on PV adoption rates is needed to formulate effective policies.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Abbasi, T., & Abbasi, S.A. (2012). Is the use of renewable energy sources an answer to the problems of global warming and pollution?. Critical Reviews in Environmental Science and Technology, 42, 99–154. doi:10.1080/10643389.2010.498754.
Bawakyillenuo, S. (2012). Deconstructing the dichotomies of solar photovoltaic (PV) dissemination trajectories in Ghana, Kenya and Zimbabwe from the 1960s to 2007. Energy Policy, 49, 410–42. doi:10.1016/j.enpol.2012.06.042.
Curtius, H.C. (2018). The adoption of building-integrated photovoltaics: barriers and facilitators. Renewable Energy, 126, 783–790. doi:10.1016/j.renene.2018.04.001.
D’Agostino, A.L., Sovacool, B.K., & Bambawale, M.J. (2011). And then what happened? A retrospective appraisal of China’s Renewable Energy Development Project (REDP). Renewable Energy, 36, 3154–3165. doi:10.1016/j.renene.2011.03.017.
Dehghani, E., Jabalameli, M.S., & Jabbarzadeh, A. (2018). Robust design and optimization of solar photovoltaic supply chain in an uncertain environment. Energy, 142, 139–156, doi:10.1016/j.energy.2017.10.004.
Elmustapha, H., Hoppe, T., and Bressers, H. (2018). Consumer renewable energy technology adoption decision-making; comparing models on perceived attributes and attitudinal constructs in the case of solar water heaters in Lebanon. Journal of Cleaner Production, 172, 347–357. doi:10.1016/j.jclepro.2017.10.131.
Elmustapha, H., Hoppe, T., and Bressers, H. (2018). Consumer renewable energy technology adoption decision-making; comparing models on perceived attributes and attitudinal constructs in the case of solar water heaters in Lebanon. Journal of Cleaner Production, 172, 347–357, doi:10.1016/j.jclepro.2017.10.131.
IRENA (2019). Renewable Power Generation Cost in 2019.
Islam, T., & Meade, N. (2013). The impact of attribute preferences on adoption timing: The case of photo-voltaic (PV) solar cells for household electricity generation. Energy Policy, 55, 521–530. doi:10.1016/j.enpol.2012.12.041.
Jannuzzi, G. de M., & de Melo, C.A. (2013). Grid-connected photovoltaic in Brazil: Policies and potential impacts for 2030. Energy for Sustainable Development, 17, 40–46. doi:10.1016/j.esd.2012.10.010.
Joshi, L., & Kumar, P. (2019). Adoption of solar photovoltaic lighting in rural India: Role of localization strategy. Energy and Buildings, 202, 109370. doi:10.1016/j.enbuild.2019.109370.
Karakaya, E., Hidalgo, A., & Nuur, C. (2015). Motivators for adoption of photovoltaic systems at grid parity: A case study from Southern Germany. Renew. Renewable and Sustainable Energy Reviews, 43, 1090–1098. doi:10.1016/j.rser.2014.11.077.
Karakaya, E., & Sriwannawit, P. (2015). Barriers to the adoption of photovoltaic systems: The state of the art. Renewable and Sustainable Energy Reviews, 49, 60–66. doi:10.1016/j.rser.2015.04.058.
Korcaj, L., Hahnel, U.J.J., & Spada, H. (2015). Intentions to adopt photovoltaic systems depend on homeowners’ expected personal gains and behavior of peers. Renewable Energy, 75, 407–415. doi:10.1016/j.renene.2014.10.007.
Ministry of Energy and Mineral Resources. (2019). Kebijakan, regulasi dan inisiatif pengembangan energi surya di Indonesia.
Ministry of Energy and Mineral Resources. (2021). Laporan Kinerja DitJen EBTKE Tahun 2021.
Ministry of Energy and Mineral Resources. (2021). Rencana Usaha Penyediaan Tenaga Listrik (RUPTL) PT PLN (Persero) 2021-2030. Rencana Usaha Penyediaan Tenaga List. 2021-2030 2021, 2019–2028.
Mundaca, L., & Samahita, M. (2020). What drives home solar PV uptake? Subsidies, peer effects and visibility in Sweden. Energy Research & Social Science, 60, 101319. doi:10.1016/j.erss.2019.101319.
Nurwidiana, N., Sopha, B.M., & Widyaparaga, A. (2021). A Behavioral Factors Underlying Households ’ Intention Toward Solar Photovoltaic Adoption. In Proceedings of the Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management; IEOM: Surakarta.
Palmer, J., Sorda, G., & Madlener, R. (2015). Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation. Technological Forecasting and Social Change, 99, 106–131. doi:10.1016/j.techfore.2015.06.011.
Rai, V., Reeves &, D.C., & Margolis, R. (2015). Overcoming barriers and uncertainties in the adoption of residential solar PV. Renewable Energy, 89, 498–505. doi:10.1016/j.renene.2015.11.080.
Reeves, D.C., & Rai, V. (2018) Strike while the rebate is hot: Savvy consumers and strategic technology adoption timing. Energy Policy, 121, 325–335. doi:10.1016/j.enpol.2018.06.045.
Sarzynski, A., Larrieu, J., & Shrimali, G. (2012). The impact of state financial incentives on market deployment of solar technology. Energy Policy, 46, 550–557. doi:10.1016/j.enpol.2012.04.032.
Schelly, C. (2014). Residential solar electricity adoption: What motivates, and what matters? A case study of early adopters. Energy Research & Social Science, 2, 183–191. doi:10.1016/j.erss.2014.01.001.
Schelly, C. (2010). Testing residential solar thermal adoption. Environment and Behavior, 42, 151–170. doi:10.1177/0013916508327867.
Setyawati, D. (2020). Analysis of perceptions towards the rooftop photovoltaic solar system policy in Indonesia. Energy Policy, 144, 111569, doi:10.1016/j.enpol.2020.111569.
Sommerfeld, J., Buys, L., & Vine, D. (2017). Residential consumers’ experiences in the adoption and use of solar PV. Energy Policy, 105, 10–16. doi:10.1016/j.enpol.2017.02.021.
Sovacool, B.K. (2018). Success and failure in the political economy of solar electrification: Lessons from World Bank Solar Home System (SHS) projects in Sri Lanka and Indonesia. Energy Policy, 123, 482–493. doi:10.1016/j.enpol.2018.09.024.
Vasseur, V., & Kemp, R. (2015). The adoption of PV in the Netherlands: A statistical analysis of adoption factors. Renewable and Sustainable Energy Reviews, 41, 483–494. doi:10.1016/j.rser.2014.08.020.
Willis, K., Scarpa, R., Gilroy, R., & Hamza, N. (2011). Renewable energy adoption in an ageing population: Heterogeneity in preferences for micro-generation technology adoption. Energy Policy, 39, 6021–6029. doi:10.1016/j.enpol.2011.06.066.
Wolske, K.S. (2020). More alike than different: Profiles of high-income and low-income rooftop solar adopters in the United States. Energy Research & Social Science, 63, 101399. doi:10.1016/j.erss.2019.101399.
Yang, D., & Timmermans, H. (2017). Households transport-home energy conservation strategies in response to energy price policies: A stated adaptation experiment based on portfolio choices and cross effects designs. International Journal of Sustainable Transportation, 11, 133–147. doi:10.1080/15568318.2016.1212442.
Zhao, J., Mazhari, E., Celik, N., & Son, Y.J. (2011). Hybrid agent-based simulation for policy evaluation of solar power generation systems. Simulation Modelling Practice and Theory, 19, 2189–2205. doi:10.1016/j.simpat.2011.07.005.