FORECASTING ANALYSIS ON ELECTRICITY DEMAND IN THE SPECIAL REGION OF YOGYAKARTA UNDER THE IMPACT OF THE COVID-19 PANDEMIC
Feikal Aprieza(1*), Mohammad Kholid Ridwan(2), Wahyu Wilopo(3)
(1) Department of Systems Engineering, Universitas Gadjah Mada
(2) Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada
(3) Department of Geological Engineering, Universitas Gadjah Mada
(*) Corresponding Author
Abstract
The COVID-19 pandemic as a global pandemic on 2020 has encouraged the Indonesian Government to establish pandemic response policies in many provinces. The policies that had been restricting mobility during the pandemic showed significant impacts in many aspects in the Special Region of Yogyakarta. A shifting pattern in electricity consumption can be seen as the growth of economic sectors in the GDP encountered contraction after the decline of community mobility. Electricity demand forecasting is required to analyze the impact of the COVID-19 pandemic by applying three scenarios, specifically an unlikely pandemic scenario or Business As Usual (BAU), moderate scenario (MOD), and optimistic scenario (OPT). Also, the household, industrial, business, social, and public sectors are analyzed in order to see the shifting pattern in electricity consumption through the scenarios that have been given. Energy modeling is conducted with Low Emission Analysis Platform (LEAP) software to analyze electricity demand forecasting from 2019 to 2030 based on the three scenarios. The results show that the electricity demand in 2030, according to BAU, MOD, and OPT scenarios, in the amount of 5,301.58 GWh, 4,489.11 GWh, and 4,648.12 GWh, respectively. According to the MOD and OPT scenarios, the electricity demands of the household and industrial sectors will increase relative to the BAU scenario. Meanwhile, according to both scenarios, the electricity demands of the business and social sectors will decrease. In the public sector, the MOD scenario shows the decline of electricity demand relative to the BAU scenario, while OPT scenario shows the opposite.
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PDFDOI: https://doi.org/10.22146/ajse.v6i1.75149
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