Kunakorn, Anantawat
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Preferred name
Kunakorn, Anantawat
Alternative Name
Kunakorn, A.
Kunakorn, Anatawat
Main Affiliation
Email
anantawat.ku@kmitl.ac.th
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Item type:Publication, Comparative Fault Detection Between DWT and STFT in Overcurrent Relays(2024-01-01); ; This study proposes a protection relay using a microcontroller to detect and classify faults in transmission lines based on the Wavelet transform. An experimental model was constructed from an actual 115 kV transmission system prototype. The current signal was observed based on the fault type, phase, and position. Clark's transform and the discrete Wavelet transform (DWT) were applied to transform signals for analysis. The positive and zero sequences obtained from Clark's transform were used for fault detection and fault classification, respectively. Moreover, the performances between the DWT and the short-time Fourier Transform (STFT) were compared in terms of accuracy and processing time. In addition, the double-detection technique was used to confirm the accuracy of fault detection. Results show that the proposed method is efficient for fault detection and classification. This finding allows the researcher to choose the appropriate analytical method. Moreover, it can also be used as the basis for overcurrent relay algorithm design in the effort to develop more advanced technologies. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Transient Analysis to Distinguish Mechanically Switched Capacitors Using Discrete Wavelet Transform and Artificial Intelligence(2026-01-01); ; Capacitor banks are widely used in modern power systems for reactive power compensation and voltage regulation. However, switching operations of mechanically switched capacitors (MSCs) can generate transient phenomena, such as inrush currents, which may resemble fault currents and lead to misoperation of protection systems. Therefore, accurate detection and classification of transient events are essential for reliable system operation. This study proposes a hybrid approach for transient signal analysis and classification by integrating the discrete wavelet transform (DWT) with artificial intelligence (AI) techniques, including probabilistic neural networks and fuzzy inference systems (FIS). The DWT performs time–frequency analysis to extract multi-scale wavelet features from three-phase current signals. The proposed method enables both discrimination between inrush and fault currents and multi-class classification of transient events among six capacitor switching conditions, namely base case, pre-insertion resistor, pre-insertion inductor, current limiting reactor, 6% reactor, and synchronous closing. The methodology is validated using PSCAD/EMTDC simulations under isolated and back-to-back capacitor switching scenarios. The results demonstrate that the proposed DWT–AI approach achieves high classification accuracy exceeding 95%, outperforming conventional methods based on DWT alone and DWT combined with FIS. Furthermore, the proposed method improves protection system performance by reducing false tripping caused by transient inrush currents, while maintaining reliable fault detection capability. The findings confirm that integrating time–frequency signal processing with AI-based classification provides an effective and practical solution for transient event discrimination in MSC capacitor bank systems. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Application of Neutral Grounding Resistor in High Voltage Photovoltaic Solar Substation System(2025-01-01); Faults in a distribution system with additional renewable energy sources can lead to unnecessary operation of protection devices due to higher detected fault currents compared to conventional systems. In addition, the voltage at the point of interconnection may temporarily drop to a low level, causing inverter-based generators to disconnect from the system. This study, therefore, proposes an investigation into the use of neutral grounding resistors in a 115 kV high-voltage (HV) substation unit located within a solar power generation system. The approach aims to limit ground fault current and reduce temporary voltage sags to maintain the connection status of inverter and ensure compliance with low voltage fault ride-through (LVRT) capability. The case study is modeled after an actual grid network consisting of two feeders, with one feeder connected to a solar power plant. PowerFactory DIgSILENT software is used to simulate the system and analyze the impact of various neutral grounding resistance values. The results of this study can be applied to the selection of neutral grounding resistors for system, helping to reduce fault current, extend relay operating time within the allowable delay range, and minimize unnecessary tripping of overcurrent protection relays in the system.