Behavioral-alike model-driven for the power demand of battery swapping stations in supporting two and three-wheeled electrification in the new capital city of Indonesia

Abstract

An integrated transportation system envisages (near) zero-emission for public and private vehicles toward sustainable and accessible urban mobility as a committed strategy for Indonesia’s new capital city (INCC). Electric mobility (e-mobility) is therefore aligned with the government’s climate mitigation commitment. Proposing an evidence-based solution for the refueling approach, battery swapping technology is considered due to its modularity of ‘plug and play’ (PnP) and cost-effective upfront investment, i.e., modular battery swapping point (MBSP) for two|three-wheeled e-mobility. However, due to the uncertainty and insufficient preliminary data on the number of rolled-out units, intended location, and allocation, the planning process of the supporting infrastructure in the early stages of transition is mostly hampered. Meanwhile, using common assumptions or averaging measures may lead to substantial disparities, risking the initiatives for cost-shared infrastructure spending. Therefore, constructing a framework model of a behavior-alike of MBSP is imperative. The framework has a distinct advantage in generating the time series of power demand profiles over the unknown parameters, i.e., the battery pack (BP) properties, user tendencies of fetching and filling cycles, and tailor-made intentions exploiting the predictive Monte Carlo (PMC) method. This work aims to contribute insight to stakeholders, policymakers, and operators and disseminate relevant planning research.