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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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Exploring the adoption of photovoltaic cleaning robots: An institutional management approach
(2024-09-01)
Promvongsanon, Rubporn
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Sawmong, Sudaporn
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Khalid, Bilal
There is increased adoption of renewable energy, particularly photovoltaic (PV), as a major source of clean and environmentally friendly energy. With the wide application of PV technologies, commonly called solar panels, their appropriate maintenance and cleaning are vital for optimum PV energy generation. The research focuses on exploring the various factors attributed to influence the want, intention and need to use PV panel cleaning robots in Thailand from an institutional management perspective. The study adopted the extended C-TAM-TPB by adding three more variables-Trust in technology, awareness of renewable energy, and environmental concern. A quantitative approach was used, where primary data was collected from PV institutional users. A population sample of 411 respondents was used. The confirmatory factor analysis (CFA) came in handy in evaluating the performance model, with the study's hypotheses being evaluated by the structural equation modeling (SEM). Results indicated that most of the subjective behaviors, perceived behavioral controls, and trust in technology played a key role in determining the intention and need to use solar panel cleaning robots. Perceived usefulness was found to have significant influence towards PV panel adoption. The influence of attitude was mediated by several factors – environmental concern, renewable energy awareness, trust in technology. The study recommended that the institutional users of solar panels should consider investing in knowledge regarding perceived behavioral control, developing confidence in the use of renewable and sustainable energy, and developing trust of the renewable and sustainable energy technologies. This could be achieved through programs such as public awareness, sharing accurate information regarding solar panel cleaning robots, and providing support and after sales support. Educational initiatives to change users' attitudes toward renewable energy technologies were recommended.
1
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WO3:AgInS2 quantum dot electron transport layers in enhanced perovskite solar cells
(2023-04-14)
Seriwattanachai, Chaowaphat
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Kaewprajak, Anusit
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Sukgorn, Nuttaya
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Kumnorkaew, Pisist
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Nukeaw, Jiti
The development of the electron transport layers (ETL) was crucially important for the improvement of charge extraction and transportation in perovskite solar cells (PSCs). Here, dual electron transport layers of TiO<inf>2</inf> and WO<inf>3</inf> mixed with different sizes of AgInS<inf>2</inf> quantum dots (TiO<inf>2</inf>/WO<inf>3</inf>:AgInS<inf>2</inf> QDs) were fabricated for planar perovskite solar cells. The peak intensity of the photoluminescence (PL) of the synthesized AgInS<inf>2</inf> QDs were redshifted from 554 to 655 nm with an increased radius of AgInS<inf>2</inf> QDs from 3.82 ± 0.52 to 7.78 ± 1.37 nm. The PL intensity of the perovskite film on TiO<inf>2</inf>/WO<inf>3</inf>:AgInS<inf>2</inf> QDs was quenched by the addition of AgInS<inf>2</inf> QDs. The improved device stability was probably caused by the WO<inf>3</inf>:AgInS<inf>2</inf> QDs layer protecting the interface of perovskite layers from direct contact with TiO<inf>2</inf> to prevent UV decomposing. Therefore, the TiO<inf>2</inf>/WO<inf>3</inf>:AgInS<inf>2</inf> QDs as electron transport layers promoted the perovskite solar cell performance and enhanced the long-term stability. Graphical abstract: [Figure not available: see fulltext.].
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A method to improve the accuracy of simulation models: A case study on photovoltaic system modelling
(2021-01-02)
Bupi, Aekkawat
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Kittisontirak, Songkiate
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Chinnavornrungsee, Perawut
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Songtrai, Sasiwimon
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Manosukritkul, Phassapon
This research presents a method to improve data accuracy for the more efficient data management of the studied applications. The data accuracy was improved using the preciseness function learning model (PFL model). It contains a database in which the amount of data is more or less dependent on all of the possible behavior of the studied application. The proposed model improves data with functions obtained by optimizing curves to represent the data at each point, which estimate the database’s diffusion behavior, and functions can be built around all of the various forms of databases. The proposed model always updates its database after processing. It has been learning to optimize the processing precision. In order to verify the precision of the proposed model through its application to a PV system simulation model, the process’s database should contain at least one year. This is because the overall behavior of the PV power output in Thailand depends on the seasonal weather; Thailand has three seasons in a period of one year. The testing was performed by comparing the PV power output. The simulation results with the actual measurement data (12 MW PV system) can be divided into two conditions: the daily comparison and the seasonal PV power output. As a result, the proposed model can accurately simulate the PV power output despite the sudden daily climate change. The average nRMSE (normalized RMSE) of the proposed model is very low (1.23%), and ranges from 0.30% to 2.26%. Therefore, it has been proven that this model is very accurate.
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Performance of the Module Temperature Model in Forecasting the Power Output of Photovoltaic Systems
(2018-07-02)
Dawan, Promphak
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Worranetsuttikul, Kaweepoj
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Kittisontirak, Songkiate
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Sriprapha, Kobsak
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Titiroongruang, Wisut
This paper is the study the performance of the temperature model in forecasting the power output of photovoltaic systems. The prominent point of the solar power forecasting model was to use only one input parameter (solar irradiance). Solar irradiance was injected into the temperature model using mathematic equations. The output of temperature model and the solar irradiance was used by the solar power forecasting model for forecasting the power output of the photovoltaic systems. The results shows that the effectiveness of the temperature model had a discrepancy at 4.03%, which is acceptable.
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Two-phase induction motor drive improvement for PV water pumping system
(2017-01-30)
Hayakwong, Ekkawid
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Kinnares, Vijit
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Bunlaksananusorn, Chanin
\n recent years, solar energy sources have been widely utilized, especially in PV water pumping system. Single-phase induction motors (SPIM) are the most common type of motor used in PV pumping application. Reliable operation, low cost and low maintenance are the main advantages of SPIM. However, SPIM have an inherent problem of low efficiency at low speeds, which can be overcome by the adoption of two-phase induction motors (TPIM). This paper proposes a new speed control method for the TPIM used in PV water pumping system. The TPIM is supplied with unbalanced two-phase voltages generated by the inverter that employs the carrier-based SVPWM switching strategy. The V/F control is incorporated to realize variable speed operation. The motor reference speed is set to be proportional to the power generated by the PV array. As a result, the motor speed always tracks power fluctuation of the PV array, leading to improved system efficiency. The validity of the proposed method is verified by simulation results.
1
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Zero energy consumption home based on utilization - Pricing ratio, using solar system in Bangkok
(2016-09-06)
Chandanachulaka, Nidchabendha
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Khan-Ngern, Werachet
This paper presents the design of zero energy consumption on a stand-alone photovoltaic (PV) system for a small residential house. The load requirement which is less than 1,500 Wh per day located in Bangkok. System structure composes of three main parts: 600 W PV system, 2880 Wh energy storage of battery and charging system, and the 1 kW inverter for AC use. The proposed design process starts with the 3 scenarios of load requirement on full sunshine, half day sunshine and no sunshine conditions including the proposed model on the appropriate proportion of generated energy: load energy: storage energy which becomes 2-1-1 while using the best scenario. Experimental results are remote monitored via a Web server application in real-time. The analysis of the zero energy consumption has been done all the solar conditions. The result from proposed model has been tested and found that it can be used successfully in stand-alone PV system for a small residential house in Bangkok.
1
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Bee colony optimization of battery capacity and location for alleviation of voltage rise by photovoltaic generation in power distribution system
(2013-03-28)
Chaiyatham, Theerawut
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Ngamroo, Issarachai
Recently, an installation of photovoltaic (PV) power generation in power distribution systems has been paid attention to around the world. Nevertheless, the PV generation may cause a reverse power flow which results in the voltage rise problem. To tackle this problem, the battery energy storage can be applied. However, the optimal placement and capacity of battery are very important issue to be considered due to the high cost of battery. This paper applies the bee colony optimization to determining the optimal location and size of battery. Simulation results with many scenarios confirm the control effect of battery optimized by the proposed method. © 2013 ICIC International.
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PSO-based Sugeno fuzzy logic controller of photovoltaic generator for frequency stabilization in stand-alone power system
(2013-01-01)
Sa-Ngawong, Nattapol
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Ngamroo, Issarachai
This paper proposes a particle swarm optimization-based Sugeno fuzzy logic controller (PSO-SFLC) of photovoltaic (PV) generator for frequency stabilization in a stand-alone power system. The PSO-SFLC is used to adjust the modulation ratio of the PV inverter so that the PV output power can be swiftly controlled to follow the load change and stabilize the system frequency fluctuation. The PSO is used to automatically tune membership functions and control rules of SFLC. The input signals of SFLC are solar insolation and frequency deviation signals while the output signal is the modulation ratio of the inverter. In the simulation study, the frequency stabilizing effect of PV with PSO-SFLC is compared with the PV with SFLC and the PV with maximum power point tracking under random load and solar insolation change. Simulation results show the superior effect of the PV with proposed PSO-SFLC over the PV with SFLC and the PV with maximum power point tracking. © 2013 IEEE.

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