Ananwattanaporn, Santipont

Loading...
Thumbnail Image
Preferred name
Ananwattanaporn, Santipont
Alternative Name
Ananwattanaporn, S.
Ananwattananporn, Santipont
Main Affiliation
Email
santipont.an@kmitl.ac.th

Settings

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Development and Analysis of a Fast-Charge EV-Charging Station Model for Power Quality Assessment in Distribution Systems
    (2025-09-01)
    Chiradeja, Pathomthat
    ;
    Yoomak, Suntiti
    ;
    Srisuksai, Panu
    ;
    Klomjit, Jittiphong
    ;
    Ngaopitakkul, Atthapol
    With the rapid rise in electric vehicle (EV) adoption, the deployment of EV charging infrastructure—particularly fast-charging stations—has expanded significantly to meet growing energy demands. While fast charging offers the advantage of reduced charging time and improved user convenience, it imposes considerable stress on existing power distribution systems due to its high power and current requirements. This study investigated the impact of EV fast charging on power quality within Thailand’s distribution network, emphasizing compliance with accepted standards such as IEEE Std 519-2014. We developed a control-oriented EV-charging station model in power systems computer-aided design and electromagnetic transients, including DC (PSCAD/EMTDC), which integrates grid-side vector control with DC fast-charging (CC/CV) behavior. Active/reactive power setpoints were mapped onto (Formula presented.) current references via Park’s transformation and regulated by proportional integral (PI) controllers with sinusoidal pulse-width modulation (SPWM) to command the voltage source converter (VSC) switches. The model enabled dynamic studies across battery state-of-charge and staggered charging schedules while monitoring voltage, current, and total harmonic distortion (THD) at both transformer sides, charger AC terminals, and DC adapters. Across all scenarios, the developed control achieved grid-current THDi of <5% and voltage THD of <1.5%, thereby meeting IEEE 519-2014 limits. These quantitative results show that the proposed, implementation-ready approach maintains acceptable power quality under diverse fast-charging patterns and provides actionable guidance for planning and scaling EV fast-charging infrastructure in Thailand’s urban networks.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Evaluating the Financial Dynamics of Electric Vehicle Charging Stations in Thailand: Implications of Energy Cost Variability
    (2025-01-01)
    Chiradeja, Pathomthat
    ;
    Sottiyaphai, Chayanut
    ;
    Ananwattanaporn, Santipont
    ;
    Ngaopitakkul, Atthapol
    This study examines the financial impact of energy costs on electric vehicle charging stations by comparing financial models with fixed and variable energy pricing structures. Through an in-depth financial simulation, key metrics such as Internal Rate of Return, Net Present Value, and payback period were calculated to evaluate the profitability and risk associated with each model. Findings reveal that charging stations with fixed energy costs generally experience a higher Internal Rate of Return at 14.55% and a Net Present Value of 1,711,781, with a payback period of four years. In comparison, stations with variable energy costs exhibit a lower Internal Rate of Return at 7.28% and a Net Present Value of 1,347,781, although the payback period remains consistent at four years. These results demonstrate that fixed energy costs enhance investment predictability and profitability, while variable costs increase exposure to energy price fluctuations, which raises financial risk but may capture greater returns under favorable market conditions. The analysis highlights the critical importance of accounting for energy cost variability in financial planning to maintain sustainable, profitable operations. This research provides essential insights for investors and policymakers to optimize electric vehicle charging infrastructure investments, supporting effective and profitable operations.