Date of Publication
2-4-2022
Document Type
Master's Thesis
Degree Name
Master of Science in Mechanical Engineering
Subject Categories
Mechanical Engineering
College
Gokongwei College of Engineering
Department/Unit
Mechanical Engineering
Thesis Advisor
Neil Stephen A. Lopez
Defense Panel Chair
Jose Bienvenido Manuel B. Biona
Defense Panel Member
Aristotle T. Ubando
Laurence A. Gan Lim
Abstract/Summary
The Philippines is currently facing debilitating issues regarding extreme traffic conditions and excessive greenhouse gas emissions, both of which are mainly caused by its outdated transportation sector. As a result, the country is currently enacting laws and programs that involve the modernization of this sector, most of which are involved with the advocacy and support for electric vehicle (EV) technology. However, given the integration of EVs into the country, there must exist a reliable and efficient ecosystem that could help support the successful proliferation of the technology. Therefore, this thesis aims to propose a spatiotemporal methodology for the optimal allocation of EV charging stations within the National Capital Region (NCR). The data to be used will be empirical ridesharing traces, given that they provide a clear picture of human day-to-day movement. A combination of K-means clustering and clustering by fast search and find of density peaks (CFS) will then be used on the traces in order to determine areas of interest. After which, the proposed clusters will be put through a Discrete Event Simulation (DES) in order to estimate and model the charging demand given a configuration of charging stations. Then, the charging demand will be distributed based on the number of traces in each cluster. Additionally, the resulting demand will be projected and cross-referenced between Business-As-Usual and Tax Incentivized scenarios. This will be done to ensure the optimal location and number of the stations, while taking into consideration the number of charging slots per station. The main novelty of this study is that it aims to address the research gap between EV user behavior, charging station location, and charging demand, by further solidifying their relationship with respect to the geography of the NCR in the Philippines.
Abstract Format
html
Language
English
Format
Electronic
Keywords
Electric vehicles—Philippines; Battery charging stations (Electric vehicles)—Philippines
Recommended Citation
Lisaba, E. F. (2022). Spatiotemporal modeling of electric vehicle charging demand for strategic EV charger deployment in Metro Manila. Retrieved from https://animorepository.dlsu.edu.ph/etdm_mecheng/9
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Embargo Period
2-15-2022