Load Forecasting in the Context of Global Covid-19 Vaccination Using Facebook Prophet
Main Article Content
Keywords
Abstract
Forecasting the electrical energy load is a very important initial stage in the operation of the electricity system so that the system works reliably, stably, and economically. The load forecasting process is carried out in the range of hours to years. This study focuses on short-term load forecasting (STLF) where in general the effects of weather conditions and human activities are very influential. In this study, we will study further the effects of the Covid-19 pandemic, namely the number of vaccines and the level of community mobility on changes in electrical loads. The study of the effect of the vaccine is the new point of this research. In electrical load forecasting, the revised Facebook Prophet method will be used. This revision is intended so that the effects of the pandemic can be included in the model. To test the effectiveness of the proposed model, a case study of the Pennsylvania electrical load data was carried out. In 2021 with the addition of the vaccination variable, the MAPE value is 15.26%. The amount of data used could possibly affect the forecasting process and MAPE results. So, the MAPE value is quite good when compared to other studies.
References
U. Basaran Filik, O. N. Gerek and M. Kurban, "Hourly Forecasting of Long Term Electric Energy Demand Using a Novel Modeling Approach," in 2009 Fourth International Conference on Innovative Computing, Information and Control (ICICIC), 2009, Kaohsiung, Taiwan, China. [Online]. Available: IEEE Xplore, http://www.ieee.org. [Accessed: 6 Oct. 2010].
Alagoz, Oguzhan, et al. "The impact of vaccination to control COVID-19 burden in the United States: A simulation modeling approach." PloS one 16.7 (2021): e0254456.
Cem akmaklı, et al. 2021. “The Economic Case for Global Vaccinations: An Epidemiological Model with International Production Networks,” Koç University-TUSIAD Economic Research Forum Working Papers 2104.
Facebook.. "Forecasting at scale," facebook.github.io, 2019. [Online]. Available: https://facebook.github.io/prophet/. [Accessed: Sept. 9, 2021].
Ioannis Panapakidis. (2021). "Short-Term, Medium-Term and Long-Term Load Forecasting: Methods and Applications," 2021. [Online]. Available: https://www.mdpi.com/journal/forecasting/special_issues/load_forecasting#info. [Accessed: Oct. 29, 2021].
Ibrahim Salem Jahan, Vaclav Snasel, and Stanislav Misak. “Intelligent Systems for Power Load Forecasting: A Study Review,” Energies 2020, vol. 13, pp. 1-12. November 2020.
Almazrouee AI, Almeshal AM, Almutairi AS, Alenezi MR, Alhajeri SN, Alshammari FM. “Forecasting of Electrical Generation Using Prophet and Multiple Seasonality of Holt–Winters Models: A Case Study of Kuwait,” Applied Sciences, vol. 10, pp. 1-19, November 2020.
Liang Guo, Weiguo Fang, Qiuhong Zhao, Xu Wang. “The hybrid PROPHET-SVR approach for forecasting product time series demand with seasonality,” Computers & Industrial Engineering, vol. 161, pp. 1-14. August 2021.
Guo, Jianfeng, Chao Deng, and Fu Gu. "Vaccinations, Mobility and COVID-19 Transmission." International Journal of Environmental Research and Public Health 19.1 (2022): 97.
Mao, Liang, and Ling Bian. "Efficient vaccination strategies in a social network with individual mobility." UCGIS 2009 Summer Assembly (2009).
Apple. (2020). COVID-19 Mobility Trends Reports. [Data files]. Retrieved from https://covid19.apple.com/mobility.
Saldaña F and Velasco-Hernandez JX. “The trade-off between mobility and vaccination for COVID-19 control: a metapopulation modeling approach,” R. Soc. Open Science, vol. 8:, pp. 1-12. May 18, 2021.
Dave Turk and Laura Cozzi. “Digitalization and Energy,” 2017. [Online]. Available: https://www.iea.org/reports/digitalisation-and-energy. [Accessed: Oct. 29, 2021].
Daniella Seiler. “How COVID-19 has pushed companies over the technology tipping point—and transformed business forever,” mckinsey.com, 2020. [Online]. Available: https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/how-COVID-19-has-pushed-companies-over-the technology-tipping-point-and-transformed-business-forever. [Accessed: Nov 2, 2021]
Sean J. Taylor and Benjamin Letham. “Forecasting at Scale, The American Statistician,” vol. 72, pp. 37-45, April 2018.
PJM. (2021). Data Miner 2 Hourly Load: Metered. [Data files]. Retrieved from https://dataminer2.pjm.com/feed/hrl_ load_metered
Wunderground. (2021). Daily Observations. [Data files]. Retrieved from https://www.wunderground.com/ history/monthly/us/pa/middletown/KMDT/date/2019-1
Pennsylvania Government. "Process to Reopen Pennsylvania," governor.pa.gov, 2020. [Online]. Available: https://www.governor.pa.gov/process-to-reopen-pennsylva nia/. [Accessed: Oct 11, 2021].
CDC. (2021). COVID-19 Vaccination Trends in the United States,National and Jurisdictional. https://data.cdc.gov/Vaccinations/COVID-19-Vaccination-Trends-in-the-United-States-N/rh2h-3yt2, [Accessed: Oct. 20, 2021].
P. M. Swamidass. Mean Absolute Percentage Error (MAPE). Encyclopedia of Production and Manufacturing Management. Boston, Springer, 2000.
Alagoz, Oguzhan, et al. "The impact of vaccination to control COVID-19 burden in the United States: A simulation modeling approach." PloS one 16.7 (2021): e0254456.
Cem akmaklı, et al. 2021. “The Economic Case for Global Vaccinations: An Epidemiological Model with International Production Networks,” Koç University-TUSIAD Economic Research Forum Working Papers 2104.
Facebook.. "Forecasting at scale," facebook.github.io, 2019. [Online]. Available: https://facebook.github.io/prophet/. [Accessed: Sept. 9, 2021].
Ioannis Panapakidis. (2021). "Short-Term, Medium-Term and Long-Term Load Forecasting: Methods and Applications," 2021. [Online]. Available: https://www.mdpi.com/journal/forecasting/special_issues/load_forecasting#info. [Accessed: Oct. 29, 2021].
Ibrahim Salem Jahan, Vaclav Snasel, and Stanislav Misak. “Intelligent Systems for Power Load Forecasting: A Study Review,” Energies 2020, vol. 13, pp. 1-12. November 2020.
Almazrouee AI, Almeshal AM, Almutairi AS, Alenezi MR, Alhajeri SN, Alshammari FM. “Forecasting of Electrical Generation Using Prophet and Multiple Seasonality of Holt–Winters Models: A Case Study of Kuwait,” Applied Sciences, vol. 10, pp. 1-19, November 2020.
Liang Guo, Weiguo Fang, Qiuhong Zhao, Xu Wang. “The hybrid PROPHET-SVR approach for forecasting product time series demand with seasonality,” Computers & Industrial Engineering, vol. 161, pp. 1-14. August 2021.
Guo, Jianfeng, Chao Deng, and Fu Gu. "Vaccinations, Mobility and COVID-19 Transmission." International Journal of Environmental Research and Public Health 19.1 (2022): 97.
Mao, Liang, and Ling Bian. "Efficient vaccination strategies in a social network with individual mobility." UCGIS 2009 Summer Assembly (2009).
Apple. (2020). COVID-19 Mobility Trends Reports. [Data files]. Retrieved from https://covid19.apple.com/mobility.
Saldaña F and Velasco-Hernandez JX. “The trade-off between mobility and vaccination for COVID-19 control: a metapopulation modeling approach,” R. Soc. Open Science, vol. 8:, pp. 1-12. May 18, 2021.
Dave Turk and Laura Cozzi. “Digitalization and Energy,” 2017. [Online]. Available: https://www.iea.org/reports/digitalisation-and-energy. [Accessed: Oct. 29, 2021].
Daniella Seiler. “How COVID-19 has pushed companies over the technology tipping point—and transformed business forever,” mckinsey.com, 2020. [Online]. Available: https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/how-COVID-19-has-pushed-companies-over-the technology-tipping-point-and-transformed-business-forever. [Accessed: Nov 2, 2021]
Sean J. Taylor and Benjamin Letham. “Forecasting at Scale, The American Statistician,” vol. 72, pp. 37-45, April 2018.
PJM. (2021). Data Miner 2 Hourly Load: Metered. [Data files]. Retrieved from https://dataminer2.pjm.com/feed/hrl_ load_metered
Wunderground. (2021). Daily Observations. [Data files]. Retrieved from https://www.wunderground.com/ history/monthly/us/pa/middletown/KMDT/date/2019-1
Pennsylvania Government. "Process to Reopen Pennsylvania," governor.pa.gov, 2020. [Online]. Available: https://www.governor.pa.gov/process-to-reopen-pennsylva nia/. [Accessed: Oct 11, 2021].
CDC. (2021). COVID-19 Vaccination Trends in the United States,National and Jurisdictional. https://data.cdc.gov/Vaccinations/COVID-19-Vaccination-Trends-in-the-United-States-N/rh2h-3yt2, [Accessed: Oct. 20, 2021].
P. M. Swamidass. Mean Absolute Percentage Error (MAPE). Encyclopedia of Production and Manufacturing Management. Boston, Springer, 2000.
Article Sidebar
Published
Mar 29, 2022
Article Details
How to Cite
Barevan, K., & Halim, A. (2022). Load Forecasting in the Context of Global Covid-19 Vaccination Using Facebook Prophet. Jurnal Nasional Teknik Elektro, 11(1), 14–20. https://doi.org/10.25077/jnte.v11n1.992.2022
Issue
Section
Electrical Power and Energy
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
The authors declare that:
1. This paper has not been published in the same form elsewhere.
2. It will not be submitted anywhere else for publication prior to acceptance/rejection by this Journal.
3. A copyright permission is obtained for materials published elsewhere and which require this permission for reproduction.
Author Biography
Kevinaldo Barevan, Universitas Indonesia
Kevinaldo Barevan
He earned a Bachelor of Engineering from Universitas Jember (UNEJ) in 2019. Then he continues his study as a postgraduate student of Electrical Engineering with a specialization in Data Engineering and Business Intelligence from Universitas Indonesia.