In order to tackle the COVID-19 pandemic, the government issued a large-scale social restriction policy (PSBB). The policy in the form of restrictions on social activities will limit economic activity which ultimately has an impact on decreasing energy demand. This PSBB policy is challenge in implementing a national energy management plan, and might causes some of the energy planning targets not to be achieved. To analyze the effect of the COVID-19 pandemic on national energy demand, an energy model was created using LEAP software. LEAP is a model for comprehensive energy planning from energy resources to energy use based on an accounting system. For the purposes of analysis, LEAP requires quite detailed data, in the form of socioeconomic data, energy data, and community activity data due to social restrictions. In this paper, the results of energy modeling simulation are discussed in terms of energy demand based on the scenario of no pandemic or bussiness as usual (BAU) and three pandemic scenarios, namely: optimistic (OPT), moderate (MOD), and pessimistic (PES) scenarios. Energy demand in 2020 is predicted to decrease by 10.7% (OPT scenario), 15.3% (MOD scenario), and 20.0% (PES scenario) compared to the BAU scenario. The model can still be further developed to analyze the impact, both on the overall of demand side and energy supply side and also environmental aspects.
The transportation sector is an important sector to support the national development. As most of the energy demand in the transportation sector is used for motor vehicles in the road transportation, estimating the energy demand for motor vehicles is an important task in energy management. One of the method to predict the energy demand for motor vehicles is based ontwo main parameters, i.e. the intensity and activities of energy utilization. While the activity reflected growth in the number of motor vehicles and the mileage per unit vehicle for a certain time. By knowing the energy demand forecasts for the motor vehicle, the opportunities to increase energy efficiency can be analyzed by switching transportation mode.
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