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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 overview of reinforcement learning-based approaches for smart home energy management systems with energy storages
(2024-09-01)
Pinthurat, Watcharakorn
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Surinkaew, Tossaporn
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Hredzak, Branislav
The paper's state-of-the-art review focuses on an in-depth evaluation of smart home energy management systems which employ reinforcement learning-based methods to integrate energy storages. In order to optimize energy consumption and improve overall sustainability while maintaining technical and economic constraints, the paper first investigates the multi-faceted aspects of integrating energy storages into smart homes. Second, an overview of a smart home system and a theoretical background of reinforcement learning-based algorithms are given and discussed. Consequently, this study delves into the challenges and benefits of integrating energy storage, specifically looking at ways to lessen the impact of renewable sources’ intermittency, improve grid stability, and streamline efficient energy storage management. Thirdly, the paper highlights the beneficial features of smart home energy storage integration, including reduced costs, increased system resilience, and improved energy efficiency. Therefore, cutting-edge reinforcement learning-based methods utilized in smart home energy management systems that incorporate energy storage are thoroughly examined by evaluating their effectiveness and adaptability, taking into account both multi-agent and single-agent reinforcement learning-based methods. Finally, the study identifies potential research directions, including the development of hybrid reinforcement learning algorithms, integration of demand-side management strategies, and addressing privacy and security concerns in reinforcement learning-based smart home energy management systems. While some research has made use of single-agent reinforcement learning, smart home energy storage systems that use energy storages seldom use multi-agent reinforcement learning techniques. Researchers, practitioners, and policymakers will be able to use this work as a foundation to build smart, sustainable home energy systems.
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An Intelligent Meter with Smart Home Ability for Intelligent Energy Management
(2024-01-01)
Hirankitti, Visit
Intelligent energy management is essential for alleviating global warming. For this purpose, we have developed a novel type of smart meter, the so-called “Intelligent Meter”, which combines both a smart meter and a smart home system into one single device. This intelligent meter is arguably more capable of energy management and more intelligent than a conventional smart meter. We first explain how this intelligent meter can be developed using an intelligent agent approach, and with this approach it allows the meter to be able to reason about states, actions, as well as causes and effects in real time; then we reveal how this meter adopts this agent ability to create load profiles for home energy usage and also perform other intelligent energy management for home resident. Interestingly, this intelligent meter is just an instance of a generic agent system, that is, an intelligent SCADA. This research therefore illustrates how our intelligent SCADA can be applied for intelligent energy management in the context of an intelligent meter.
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Energy and exergy analyses of a hybrid system containing solid oxide and molten carbonate fuel cells, a gas turbine, and a compressed air energy storage unit
(2021-10-11)
Jienkulsawad, Prathak
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Patcharavorachot, Yaneeporn
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Chen, Yong Song
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Arpornwichanop, Amornchai
Design of a hybrid system composed of a solid oxide fuel cell (SOFC), molten carbonate fuel cell (MCFC), gas turbine (GT), and an advanced adiabatic compressed air energy storage (AA-CAES) based on only energy analysis could not completely identify optimal operating conditions. In this study, the energy and exergy analyses of the hybrid fuel cell system are performed to determine suitable working conditions for stable system operation with load flexibility. Pressure ratios of the compressors and energy charging ratios are varied to investigate their effects on the performance of the hybrid system. The hybrid fuel cell system is found to produce electricity up to 60% of the variation in demand. A GT pressure ratio of 2 provides agreeable conditions for efficient operation of the hybrid system. An AA-CAES pressure ratio of 15 and charging ratio of 0.9 assist in lengthening the discharging time during a high load demand based on an electricity variation of 50%.
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Experimental Study and Modeling of Automatic Home Energy Management System Using AI
(2021-01-01)
Pranee, Piyanut
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Jirasuwankul, Nirudh
This paper proposes an experimental study and modeling of Fuzzy logic based-AI for home energy management system. The management model has been designed for home in the subtropical climate zone-like, i.e., Thailand, which having yearly and monthly average temperature of 28°c and 30-38°c in the hottest season respectively. The studied system model comprises of the grid-connected load of home appliances, air conditioner, type-1 EV charger and solar rooftop PV supply. The objective of energy management is to minimize grid power consuming as well as maximizing solar PV utilization with 24-hour load profile, principally running of air conditioner and EV charging load. By testing the proposed management system comparatively to the generic system without managing scheme, energy saving of 43.90% can be achieved under the same operating and environmental conditions. Those are illustrated by the simulation results.
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Demonstration tests of infrared peeling system with electrical emitters for tomatoes
(2016-01-01)
Pan, Zhongli
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El Mashad, H. M.
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Li, X.
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Khir, R.
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Atungulu, G.
Infrared (IR) dry-peeling is an emerging technology that could avoid the drawbacks of steam and lye peeling of tomatoes. The objectives of this research were to evaluate the performance of an IR peeling system at two tomato processing plants in California and to compare product quality, peelability, and energy consumption of IR and steam peeling. The system was continuously operated using tomatoes of different sizes and cultivars. High percentages (62% to 85%) of fully peeled tomatoes were obtained and varied depending on tomato cultivar and seasonality. IR dry-peeled tomatoes had a firmer texture than steam and lye peeled tomatoes. IR peeling achieved a peeling loss in the range of 17% to 42%, which was lower than typical loss in the industry. Small tomatoes had higher loss than large tomatoes in the late season. Thermal energy consumption of the proposed technology in full-scale production (10 ton h<sup>-1</sup>) is predicted to be 117.0 and 137.3 MJ ton<sup>-1</sup> for indoor and outdoor operation, respectively. The estimated energy savings of IR dry-peeling should be 22% and 28% compared to lye and steam peeling, respectively. The demonstration results showed that the IR dry-peeling technology could be a viable alternative to lye and steam peeling.
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Community monitoring and security using an intelligent camera in EAT smart grids
(2011-05-02)
Thananunsophon, Ketsupich
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Mangalabruks, Benja
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Fujii, Yusaku
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Yupapin, Preecha P.
The paper purposes the use of new energy management method for monitoring sub-electrical power station security, service and maintenance. A system consists of a close circuit television (CCTV) for surveillance system, in which the electrical system prevention and monitoring can also be operated by using the thermal viewer (sensor). The consumers confident for the electricity quality will be increased by EAT smart Grid. This equipment can be installed in the system of substation in order to create stability for Thailand electricity system throughout the Smart Grids.

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