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Power Quality Improvement Based on Active Harmonic Filter in 24 kV Liquefied Natural Gas Industrial Plant’s Photovoltaic System
(2026-06-01)
Pothisarn, Chaichan
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Patcharoen, Theerasak
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Lothongkam, Chaiyaporn
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Ngaopitakkul, Atthapol
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Lertwanitrot, Praikanok
This paper presents a case study demonstrating the power quality improvements in a 24 kV distribution system at a liquefied natural gas (LNG) industrial plant with variable speed drives (VSDs), the conventional capacitor bank, and a rooftop solar photovoltaic system. Solar photovoltaic (PV) inverters can supply harmonic currents to the grid, potentially affecting the system and causing maloperation of sensitive equipment in both the utility systems and neighboring industries connected to it. Therefore, the installation of shunt active power filters (APFs) in a 400 V system was proposed in this study. The installed locations were varied, and the corresponding power qualities were analyzed. The results were examined in terms of design and harmonic elimination. Simulations were conducted using the PSCAD/EMTDC software version 4.5. The power quality simulation and field measurement results after the APF installation were compared to demonstrate the effectiveness of the proposed solutions. The addition of APFs was found to improve the power quality. In addition to the mechanism analysis, the economic feasibility of the proposed approach was investigated. The costs of APF installation in various locations were analyzed. The results show that the proposed method can improve the power supply at a reasonable price. This work contributes to sustainable industrial energy systems by improving the reliability and power quality of photovoltaic-integrated electrical networks, thereby supporting higher penetration of renewable energy resources and stable low-carbon industrial operation.
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SOC-Dependent Soft Current Limiting for Second-Life Lithium-Ion Batteries in Off-Grid Photovoltaic Battery Energy Storage Systems
(2026-04-01)
Wang, Hongyan
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Chiradeja, Pathomthat
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Ngaopitakkul, Atthapol
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Yoomak, Suntiti
The increasing deployment of off-grid photovoltaic–battery energy storage systems (PV–BESSs) has intensified operational demands on battery energy storage, particularly when second-life lithium-ion batteries are employed. Due to aging-induced increases in internal resistance and reduced thermal margins, second-life batteries are more vulnerable to high-current operation at a low state-of-charge (SOC), which aggravates heat generation and accelerates degradation. In this study, an SOC-dependent soft current limiting strategy is proposed that reshapes the discharge current reference under low-SOC conditions while maintaining fixed SOC limits, thereby targeting current-domain protection rather than SOC-boundary adaptation for reliable off-grid operation. The proposed method introduces two SOC thresholds to gradually derate the allowable discharge current, preventing abrupt current changes near the lower SOC bound. A unified MATLAB/Simulink-based framework is developed for a 24 h representative off-grid PV–BESS scenario using a second-order equivalent circuit model coupled with a lumped thermal model. Simulation results show that the proposed current shaping reduces low-SOC current stress and associated Joule heating, leading to moderated temperature rise, while only slightly affecting the unmet load under the tested conditions. These findings indicate that SOC-dependent current shaping can provide a control-oriented means to reduce low-SOC electro-thermal stress in second-life batteries within the studied off-grid PV–BESS framework.
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SOH- and Temperature-Aware Adaptive SOC Boundaries for Second-Life Li-Ion Batteries in Off-Grid PV–BESSs
(2026-02-01)
Wang, Hongyan
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Ngaopitakkul, Atthapol
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Yoomak, Suntiti
In this study, an adaptive state-of-charge (SOC) boundary strategy (ASBS) is proposed that dynamically adjusts the admissible upper and lower SOC limits of second-life lithium-ion batteries in off-grid photovoltaic battery energy storage systems (PV-BESSs) based on real-time state of health (SOH) and temperature feedback. The strategy is formulated using a unified electrical–thermal–aging model with an online state estimator and ensures both electrical safety and power feasibility while remaining fully compatible with standard energy management functions. Two representative simulations—a single-day operating profile and a continuous thirty-day sequence—demonstrate the effectiveness of the ASBS. In the twenty-four-hour case, the duration spent in high state-of-charge conditions is reduced by approximately 0.30–0.50 h, the abrupt end-of-charging transition is eliminated, and the temperature rise is slightly moderated, all without any loss of energy supply. Over thirty days, the difference between the ASBS and a fixed state-of-charge window remains effectively zero for almost all hours, with only a brief midday deviation of −4 to −5 percentage points and no cumulative drift. Indicators of electrical and thermal stress improve substantially, including an approximate 70% reduction in the root mean square charging current. These results confirm that the ASBS provides a practical and non-intrusive means of mitigating stress on second-life lithium-ion batteries while preserving full energy autonomy in off-grid photovoltaic systems.
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An Evaluation Study on Electric Appliance Characteristics and Load Patterns in Residential Buildings
(2026-01-01)
Thongsuk, Surakit
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Songsukthawan, Panapong
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Ananwattanaporn, Santipont
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Sottiyaphai, Chayanut
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Ngaopitakkul, Atthapol
Energy usage in residential buildings has been constantly increasing as work-from-home trends continue to maintain popularity. To improve energy efficiency, the load profile and electric appliances in households need to be established and analyzed. This study aims to evaluate the characteristics of electric appliances that are commonly used in residential buildings under various operating conditions. An experimental setup with household electric appliances was built, and power quality meters were installed to assess the patterns under various operating conditions. In addition, the usage patterns were used to construct the daily load profile and analyze the energy consumption in residential buildings. The results demonstrate that load patterns constructed from actual measurements can achieve an accurate depiction of energy usage in residential buildings. The obtained load profile can be used in load control to improve energy efficiency and the application of renewable energy in demand reduction.
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Comparative Study between On- and Off-Grid Photovoltaic to Reduce Peak Demand in Residential Houses
(2026-01-01)
Jettanasen, Chaiyan
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Sottiyaphai, Chayanut
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Bunjongjit, Sulee
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Songsukthawan, Panapong
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Phannil, Natthanon
This study proposes a programmable logic controller (PLC)-based energy management system integrated with an off-grid photovoltaic (PV) system and battery storage to reduce residential peak demand. The proposed system dynamically manages power supply between the distribution grid, PV generation, and battery storage based on real-time power demand measurements. When the measured power exceeds a predefined threshold, stored renewable energy is utilized to support high-load conditions and mitigate peak demand. Experimental results obtained from a residential-scale test system demonstrate that the proposed off-grid PV system with PLC control can reduce peak demand by up to 29.68% and 15.57% under office-working and work-from-home scenarios, respectively, compared with conventional grid supply and on-grid PV systems without storage. In addition, the system achieves electricity cost reductions of up to 13.63% under Time-of-Use tariffs and up to 11.42% under normal electricity rates, depending on load behavior. These results indicate that integrating PLC-based control with off-grid PV and battery storage can effectively mitigate residential peak demand and reduce electricity expenses under realistic operating conditions.
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Charging pile fault prediction method combining whale optimization algorithm and long short-term memory network
(2025-12-01)
Huang, Yansheng
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Ngaopitakkul, Atthapol
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Yoomak, Suntiti
As the world’s energy structure is gradually changing, the automotive industry is shifting its focus to new energy vehicles in an effort to improve the performance and service life of the charging pile. To solve the problem that traditional models tend to fall into locally optimal solutions (i.e., the model optimization process stays in the non-optimal regional minimum) in complex parameter space, the study innovatively proposes a hybrid prediction model that combines the whale optimization algorithm with the gated recurrent unit-long short-term memory neural network. By introducing the whale optimization mechanism to globally optimize the key parameters of the neural network, the method improved the model’s ability to model complex time series data. Moreover, the method also effectively avoided the problem of traditional methods falling into local optimal solutions, thus improving the training efficiency and generalization ability while maintaining the model accuracy. It took only 21 s to complete the training of 600 samples, and the prediction accuracy was as high as 91%. In the four classes of fault classification experiments, the proposed model performs well in classification accuracy in all classes, showing strong multi-class fault recognition capability. Therefore, the fault prediction model developed in this study can accurately and effectively identify and predict charging pile faults, and shows high performance. This not only provides a strong theoretical foundation for the application of deep learning in charging pile fault prediction, but is also of great significance in terms of reducing operation and maintenance costs, supporting energy structure transformation, and promoting green development.
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Design and techno-economic evaluation of a nanogrid system for a small-scale public railway station building in Thailand
(2025-12-01)
Ngaopitakkul, Atthapol
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Songsukthawan, Panapong
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Bunjongjit, Sulee
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Sreewirote, Bancha
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Yoomak, Suntiti
In Thailand, numerous small-scale public facilities continue to rely on the electrical grid. The integration of renewable energy sources such as photovoltaic (PV) and wind power offers a sustainable alternative; however, their inherent intermittency necessitates advanced solutions such as nanogrid systems, which enable localized energy generation, storage, and management to enhance reliability and autonomy. This study develops a nanogrid-based energy management system for Hua Takhe train station, Thailand, by integrating photovoltaic (PV) panels, wind turbines, and battery energy storage systems (BESS). Using HOMER Pro, multiple configurations were simulated and evaluated across key financial indicators, including Payback Period (PB), Internal Rate of Return (IRR), Return on Investment (ROI), Net Present Value (NPV), and Levelized Cost of Electricity (LCOE). The analysis framework further incorporates economic feasibility evaluation, sensitivity and scenario analysis, and long-term performance and life cycle evaluation, thereby ensuring that both short-term financial viability and long-term sustainability are comprehensively assessed. Results show that PV-dominant nanogrid systems, particularly at larger scales, represent the most practical and cost-effective pathway for sustainable electrification of public facilities in Thailand. The 30PV Nanogrid achieves the most favorable balance between cost and performance, with a NPV of 23,925 USD, a LCOE of 0.04 USD/kWh, a PB of 7 years, an IRR of 13 %, and a ROI of 215 % under long-term life-cycle evaluation. In comparison, the 15PV Nanogrid proves economically marginal, with NPV falling to –9117 USD, PB extending beyond 20 years, IRR turning negative (–5 %), and ROI declining to –40 %, confirming that small-scale nanogrids cannot offset the costs of ESS and hybrid inverters.
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An approach to energy conservation in lighting systems using luminaire-based sensor for automatic dimming
(2025-12-01)
Jettanasen, Chaiyan
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Thongsuk, Surakit
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Sottiyaphai, Chayanut
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Songsukthawan, Panapong
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Chiradeja, Pathomthat
Lighting systems account for a significant proportion of energy consumption in buildings. Therefore, energy conservation within these systems can greatly enhance overall building energy efficiency. This study proposes a control strategy for LED lamps by adjusting lighting intensity and improving the performance of electric luminaires. The approach involves implementing an automated dimming system that adapts lighting intensity based on surrounding light levels. A system comprising an ambient light sensor, microcontroller, power supply module, dimming controller, and lamp was developed. The sensors measure brightness within a specified range in real time, and the microcontroller analyzes and compares this data against the brightness settings for specific areas. The designed control system was tested in a laboratory setup to demonstrate its effectiveness in a controlled environment. Results showed a 75.65% reduction in power consumption compared to standard lamps in a simulated environment, highlighting its potential for significant energy savings in buildings and its contribution to environmental sustainability.
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Analysis of Investment Feasibility for EV Charging Stations in Residential Buildings
(2025-09-01)
Chiradeja, Pathomthat
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Yoomak, Suntiti
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Sottiyaphai, Chayanut
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Ngaopitakkul, Atthapol
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Klomjit, Jittiphong
This 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.
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Development and Analysis of a Fast-Charge EV-Charging Station Model for Power Quality Assessment in Distribution Systems
(2025-09-01)
Chiradeja, Pathomthat
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Yoomak, Suntiti
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Srisuksai, Panu
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Klomjit, Jittiphong
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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.

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