KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/kmitl/1

Browse

Settings

Author: search.filters.author.Bi, Chenxing

Search Results

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Comparative Analysis of ANN and ANFIS-Based MPPT for Photovoltaic System
    (2025-01-01)
    Bi, Chenxing
    ;
    Jiriwibhakorn, Somchat
    Eco-friendly and sustainable energy sources, such as solar and wind power, have rapidly integrated into the grid in recent years. Solar power generation is influenced by factors such as radiation intensity and temperature. However, the intermittent nature of solar energy poses challenges for consistent power generation. Intelligent techniques are essential for maximizing power extraction. This study focuses on developing Artificial Intelligence-based Maximum Power Point Tracking (MPPT) methods in solar photovoltaic (PV) systems. Two AI techniques were implemented, and their performance was compared to achieve more efficient results. Real-time data from micro-nano grids in China were utilized to design a feed-forward neural network and an adaptive neural network-based MPPT system. These systems aim to optimize solar energy harvesting and enable integration into nano-grid systems, offering affordable and eco-friendly energy solutions for families in Thailand. The algorithms were developed using MATLAB/Simulink, and both techniques demonstrated excellent performance. Notably, the ANFIS-based MPPT system outperformed, achieving a tracking efficiency of 93% in PV systems.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Design of DC/AC Unidirectional Inverter Based on DSP with Second-Order Switching Sequence Control in Photovoltaic DC Nano-Grids
    (2025-01-01)
    Bi, Chenxing
    ;
    Jiriwibhakorn, Somchat
    Conventional inverters predominantly utilize Pulse-Width Modulation (PWM) control, operating in an intermediate state between the averaged and actual switching models. However, this approach often results in suboptimal output power quality and limited dynamic performance, which can compromise the operational stability of AC load systems. To address these limitations, this paper proposes a second-order Switching Sequence Control (SSC) strategy based on sliding mode theory, offering discrete-time control with enhanced robustness and precision. A comprehensive mathematical model of a single-phase LC inverter is developed and discretized. The SSC control algorithm is implemented using a TMS320F28335 Digital Signal Processor (DSP), with code generated via MATLAB/Simulink to streamline development and ensure real-time execution. Extensive simulations under various conditions demonstrate that the proposed inverter achieves excellent tracking accuracy, strong dynamic response, and reduced Total Harmonic Distortion (THD) is only 0.48%. Compared with conventional PWM, Selective Harmonic Elimination (SHE), and FPGA-based control methods, the SSC strategy significantly improves waveform fidelity and transient performance. These results confirm its suitability for high-performance applications in photovoltaic DC nanogrids, smart energy systems, and critical load support scenarios.
      1