EV mobility model to explore the possibility of using EVs as energy storage and prediction of EV charger location

• Main Author: Wong, Xiang Rui
• Other Authors: Lee Bu Sung, Francis
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science; EV; Electric vehicle; Energy
• Online Access: https://hdl.handle.net/10356/181129
• Institution: Nanyang Technological University

With EV adoption increasing, balancing and stabilizing power grids has become increasingly challenging. As Singapore suffers from limited land and resources, the surge in EV charging can lead to potential strain and overloads to the power grid, which could cause drastic problems such as reduced reserve margins and supply reliability issues. Thus, this report explores the strategies to mitigate those impacts by looking into areas such as vehicle-to-grid (V2G), smart charging, and solar photovoltaic (PV) while providing recommendations for possible future charger locations based on demand. This study aims to investigate the current state of EV adoption in Singapore, the current charging infrastructure, and the capacity of our power grid by utilising previously collected datasets obtained in 2019. Furthermore, by reviewing government reports and publications, this study aims to identify trends and patterns using a quantitative approach with the help of machine learning and routing algorithms, such as the Open-Source Routing Machine (OSRM), to ensure that Singapore’s current infrastructure is adequate to support the increasing demand. This study's approach is a multi-layered strategy combining clustering, classification models, and the Analytic Hierarchy Process (AHP) weighted scoring to address the challenges of increasing charging demand. The AHP scoring would evaluate factors such as peak energy demand, geographical distribution data, and traffic intensity before identifying an optimal location for new chargers. Additionally, this study considers Singapore’s unique space constraints and building infrastructure before making decisions to ensure a sustainable expansion. The analysis would reveal populated and high-demand locations for new charging stations and strategies for peak pressure management while providing opportunities to integrate renewable energy sources. These recommendations offer a path to enhancing the EV charging infrastructure while supposing grid stability.