skip to main content

Renewable Energy Cost Estimation on Smart On Grid Actuator Innovation for the Development of Alternative Rural Electricity

*Andjar Prasetyo  -  Badan Penelitian dan Pengembangan Kota Magelang, Indonesia
Received: 23 Dec 2018; Published: 31 Oct 2019.
Editor(s): Tubagus Furqon Sofhani, Ph.D
Open Access Copyright (c) 2019 The Indonesian Journal of Planning and Development under http://creativecommons.org/licenses/by-nc-sa/4.0.

Citation Format:
Abstract
Indonesia's target for using the energy mix through Renewable Energy (RE) is 22.5 percent in 2025. The steps taken are to optimize local energy use for electricity generation and select more efficient technologies that can reduce the cost of electricity supply. One of the pioneers carried out in the city of Magelang is the Smart on Grid Actuator (SOGA) system that converts sunlight into electrical energy. This study aims to calculate and analyze estimated costs by using the sun using SOGA System innovations. The research location in the Research and Development Agency of the City of Magelang focused on cost efficiency testing based on solar energy harvesting with SOGA. The survey on the use of SOGA innovation was conducted during October 2018 to obtain primary data. The approach to the results of previous research and theoretical approaches is intended as a reference, and secondary data complete the analysis of this study. Study analysis uses the Financial and Economic Benefits Photovoltaic Grid-Tied System projection (Utility-Based Rebate Formula). As a result, the SOGA system can reduce installed electricity costs by ± 330 USD per year and can be used for alternative rural energy development.
Fulltext View|Download
Keywords: cost; innovation; rural; smart on-grid actuator
Funding: Research and Development Agency

Article Metrics:

  1. Anindhita, M. S. (2018). Ooutlook energi Indonesia 2018. Development (First, Vol. 134). BPPT, Jakarta: Pusat Pengkajian Industri Proses dan Energi (PPIPE)
  2. Bager, S., & Mundaca, L. (2017). Making ‘Smart Meters’ smarter? Insights from a behavioural economics pilot field experiment in Copenhagen, Denmark. Energy Research and Social Science, 28, 68–76. doi: 10.1016/j.erss.2017.04.008
  3. Balta-Ozkan, N., Amerighi, O., & Boteler, B. (2014). A comparison of consumer perceptions towards smart homes in the UK, Germany and Italy: reflections for policy and future research. Technology Analysis and Strategic Management, 26(10), 1176–1195. doi: 10.1080/09537325.2014.975788
  4. Blanco, M. I., & Rodrigues, G. (2009). Direct employment in the wind energy sector: An EU study. Energy Policy, 37, 2847–2857. doi: 10.1016/j.enpol.2009.02.049
  5. Cedrick, B. Z. E., & Long, P. W. (2017). Investment motivation in renewable energy: A PPP approach. Energy Procedia, 115, 229–238. doi: 10.1016/j.egypro.2017.05.021
  6. Colak, I., Fulli, G., Sagiroglu, S., Yesilbudak, M., & Covrig, C. F. (2015). Smart grid projects in Europe: Current status, maturity and future scenarios. Applied Energy, 152, 58–70. doi: 10.1016/j.apenergy.2015.04.098
  7. Del Rio, P., & Burguillo, M. (2009). Assessing the impact of renewable energy deployment on local sustainability: Towards a theoretical framework. Renewable and Sustainable Energy Reviews, 12(5), 1325–1344. doi: 10.1016/j.rser.2007.03.004
  8. Goulden, M., Bedwell, B., Rennick-Egglestone, S., Rodden, T., & Spence, A. (2014). Smart grids, smart users? the role of the user in demand side management. Energy Research and Social Science, 2, 21–29. doi: 10.1016/j.erss.2014.04.008
  9. Mazzucato, M., & Semieniuk, G. (2018). Financing renewable energy: Who is financing what and why it matters. Technological Forecasting and Social Change, 127(May 2016), 8–22. doi: 10.1016/j.techfore.2017.05.021
  10. Michaels, L., & Parag, Y. (2016). Motivations and barriers to integrating ‘prosuming’ services into the future decentralized electricity grid: Findings from Israel. Energy Research and Social Science, 21, 70–83. doi: 10.1016/j.erss.2016.06.023
  11. Milchram, C., Hillerbrand, R., van de Kaa, G., Doorn, N., & Künneke, R. (2018). Energy justice and smart grid systems: Evidence from the Netherlands and the United Kingdom. Applied Energy, 229(September 2017), 1244–1259. doi: 10.1016/j.apenergy.2018.08.053
  12. Miller, C. A., Iles, A., & Jones, C. F. (2013). The social dimensions of energy transitions. Science as Culture, 22(2), 135–148. doi: 10.1080/09505431.2013.786989
  13. North, D. C. (1991). Institutions. Journal of Economic Perspectives, 5(1), 97–112
  14. Raimi, K. T., & Carrico, A. R. (2016). Understanding and beliefs about smart energy technology. Energy Research and Social Science, 12, 68–74. doi: 10.1016/j.erss.2015.12.018
  15. Sovacool, B. K., & Dworkin, M. H. (2015). Energy justice: Conceptual insights and practical applications. Applied Energy, 142, 435–444. doi: 10.1016/j.apenergy.2015.01.002
  16. Sovacool, B. K., Heffron, R. J., McCauley, D., & Goldthau, A. (2016). Energy decisions reframed as justice and ethical concerns. Nature Energy, 1(May). doi: 10.1038/nenergy.2016.24
  17. Taebi, B., & Kadak, A. C. (2010). Intergenerational considerations affecting the future of nuclear power: Equity as a framework for assessing fuel cycles. Risk Analysis, 30(9), 1341–1362. doi: 10.1111/j.1539-6924.2010.01434.x
  18. Tuballa, M. L., & Abundo, M. L. (2016). A review of the development of Smart Grid technologies. Renewable and Sustainable Energy Reviews, 59, 710–725. doi: 10.1016/j.rser.2016.01.011
  19. Vassileva, I., Dahlquist, E., Wallin, F., & Campillo, J. (2013). Energy consumption feedback devices’ impact evaluation on domestic energy use. Applied Energy, 106, 314–320. doi: 10.1016/j.apenergy.2013.01.059

Last update:

No citation recorded.

Last update:

No citation recorded.