Ananwattanaporn, Santipont
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Ananwattanaporn, Santipont
Alternative Name
Ananwattanaporn, S.
Ananwattananporn, Santipont
Main Affiliation
Email
santipont.an@kmitl.ac.th
17 results
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Item type:Publication, Classification of Capacitor Bank Switching Using Fuzzy Interference Systems in 230 kV Substation(2024-01-01); ; ; Lertwanitrot, PraikanokFlexible AC transmission systems are used for enhancing the stability, transmission efficiency, and reliability of AC grids. Additionally, the most cost-effective devices for compensating reactive power are Mechanically Switched Capacitors (MSCs). This study proposes a novel algorithm for detection and capacitor bank switching transient signals in MSC, to prevent the protective relay maloperation by these transients. The Discrete wavelet transform (DWT) is used for effective time-frequency analysis and detection of measured three-phase current signals. DWT extracts the detailed wavelet coefficients of current signals at levels 1 to 30. In addition, the fuzzy inference system (FIS) has been used to determine the type of switching transient. The proposed combination of FIS and DWT has been tested on 230 kV substation and the result demonstrated precision for the identification and classification of both transient signals in MSC with 88% accuracy rate. - Some of the metrics are blocked by yourconsent 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); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Analysis of Investment Feasibility for EV Charging Stations in Residential Buildings(2025-09-01); ; Klomjit, JittiphongThis study investigates the financial and operational feasibility of deploying electric vehicle (EV) charging infrastructure within high-density residential buildings, utilizing empirical operational data combined with comprehensive financial modeling. A 14-day monitoring period conducted at a residential complex comprising 958 units revealed distinct charging behaviors, with demand peaking during weekday evenings between 19:00 and 22:00 and displaying more dispersed yet lower overall utilization during weekends. Energy efficiency emerged as a significant operational constraint, as standby power consumption contributed substantially to total energy losses. Specifically, while total energy consumption reached 248.342 kW, only 138.24 kW were directly delivered to users, underscoring the necessity for energy-efficient hardware and intelligent load management systems to minimize idle consumption. The financial analysis identified pricing as the most critical determinant of project viability. Under current cost structures, financial break-even was attainable only at a profit margin of 0.2286 USD (8 THB) per kWh, while lower margins resulted in persistent financial deficits. Sensitivity analysis further demonstrated the considerable vulnerability of the project’s financial performance to small fluctuations in profit share and utilization rate. A 10% reduction in either parameter entirely eliminated the project’s ability to reach payback, while variations in energy costs, capital expenditures (CAPEX), and operational expenditures (OPEX) exerted comparatively limited influence. These findings emphasize the importance of precise demand forecasting, adaptive pricing strategies, and proactive government intervention to mitigate financial risks associated with residential EV charging deployment. Policy measures such as capital subsidies, technical regulations, and transparent pricing frameworks are essential to incentivize private sector investment and support sustainable expansion of EV infrastructure in residential sectors. - 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, Impact of Wind Power Generation Sizing on the Characteristic of Distribution System Under Fault Condition(2022-01-01); ; ; Songsukthawan, PanapongIn the recent decade, there has been a rising concern in energy consumption and environmental issues. This trend has shifted the electric authority to focus from fossil fuel to renewable energy. The distributed generation (DG) using a renewable energy source has been raising. The presence of DG can cause using renewable energy sources to cause a technical issue on system protection and operation. This paper aims to study the impact of different DG size installations on the distribution system in terms of the system characteristics. The study is done in both normal conditions and in cases of fault occurrence. The system using in this research is a 22-kV distribution system consists of Wind Power Generation as the DG connected into the distribution line that modeled after part of the Provincial Electricity Authority (PEA) in the northern part of Thailand. The simulation was done using PSCAD software. The result from simulation reveals the impact of DG on the distribution system characteristics in terms of significant change in the measured current and voltage signal. Thus, the analysis of the impact of DG on the system must be done to ensure the reliability of the power system. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The Design and Evaluation of Nanogrid-Based Solar Photovoltaic Light-Emitting Diode Street Lighting Systems: A Techno-Economic and Voltage Drop Analysis for Secondary Roads in Thailand(2026-05-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Combining Fuzzy Logic and Discrete Wavelet Transform for Accurate Fault and Inrush Current Classification in High Voltage Capacitor Banks(2024-01-01); ; The high voltage capacitor bank is a critical component in substations, essential for maintaining power quality and system stability. However, these banks are susceptible to faults and inrush currents, posing significant operational challenges. This paper presents a method for accurately classifying fault and inrush currents in high voltage capacitor banks using Fuzzy Logic and Discrete Wavelet Transform (DWT). The DWT decomposes current waveforms into frequency components, enabling the extraction of features that characterize faults and inrush currents. These features are processed by a Fuzzy Inference System (FIS), which classifies the events based on predefined rules and membership functions. The integration of DWT and FIS provides a robust framework for distinguishing between different types of faults and inrush currents with high accuracy. Simulation results demonstrate the proposed method's efficacy, showing improved performance in classification accuracy and noise robustness compared to traditional techniques. This research enhances monitoring and protection systems in power networks, ensuring more reliable operation of high voltage capacitor banks. Implementing this method allows for better fault management and minimized downtime, leading to improved overall system efficiency and stability. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An Approach for Voltage Drop Improvement in Distribution Line Using High-Voltage Capacitor Bank(2025-01-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Application of probabilistic neural networks using high-frequency components’ differential current for transformer protection schemes to discriminate between external faults and internal winding faults in power transformers(2021-11-01); ; Leelajindakrairerk, MonthonInternal and external faults in a power transformer are discriminated in this paper using an algorithm based on a combination of a discrete wavelet transform (DWT) and a probabilistic neural network (PNN). DWT decomposes high-frequency fault components using the maximum coefficients of a 1/4 cycle DWT as input patterns for the training process in a decision algorithm. A division algorithm between a zero sequence of post-fault differential current waveforms and the differential current coefficient in the 1/4 cycle DWT is used to detect the maximum ratio and faults. The simulation system uses various study cases based on Thailand’s electricity transmission and distribution systems. The simulation results demonstrated that the PNN and BPNN are effectively implemented and perform fault detection with satisfactory accuracy. However, the PNN method is most suitable for detecting internal and external faults, and the maximum coefficient algorithm is the most effective in detecting the fault. This study will be useful in differential protection for power transformers. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evaluation of the Climate Influence on the Thermal Characteristics of Residential Buildings in Thailand(2026-01-01); ; An increasing population causes more energy demand, resulting in an increased rate of electricity production. Thus, increasing the electricity production rate wastes more fuel resources. These limited resources are depleted if not used properly. Therefore, energy conservation is an essential point that we should be aware of. In addition, weather and geography are significant factors that directly affect the energy consumption rate. Fundamentally, cold regions use more energy for heating, while tropical areas use more energy for air conditioning. Therefore, if the energy used for these fundamental needs can be saved, it will effectively reduce the overall rate of energy use. Consequently, environmental factors that affect energy consumption, such as wind flow direction, building orientation, and pressure, were observed. The observation was done by simulating in a Computational Fluid Dynamics (CFD) program. At the same time, an energy-saving method is also proposed in this paper. The results showed that the proposed method can reduce the energy consumption rate, which is beneficial for the development of energy management systems in the future.