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Experimental optimization of defrosting duration for enhanced energy efficiency in large-scale ammonia-based tube ice-making systems
(2026-08-01)
Ohnjaikla, Natcha
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Poungthong, Pongthep
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Kasayapanand, Nat
This study experimentally investigates the impact of defrosting duration on the operational performance and energy efficiency of an industrial-scale 80-ton-per-day ammonia (NH<inf>3</inf>)-based tube ice-making system with a tube diameter of 38 mm. Experiments were performed under controlled ambient conditions (28 °C dry bulb temperature and 80% relative humidity) with defrosting times of 5, 6, and 7 min. Key performance indicators, including suction and discharge pressures, temperatures, power consumption, cooling capacity, freezing time, ice weight per cycle, and the coefficient of performance (COP), were systematically monitored. Each experiment was repeated three times (n = 3), and the results are reported as mean ± standard deviation. Results indicate that extending defrosting time beyond 5 min increases discharge pressure by up to 9% and discharge temperature by up to 12 °C, leading to a 3.14–9.52% rise in compressor energy consumption. At the same time, cooling capacity decreased by 2.8% (6 min) and 7.1% (7 min), lengthening freezing cycles and reducing daily ice production by 4–10% compared with the 5-minute baseline. Although slightly more ice mass per cycle was achieved with longer defrosts, this advantage was offset by higher energy demand and lower cooling efficiency. The findings underscore the importance of optimizing defrosting duration to achieve an effective balance between energy consumption and production efficiency in industrial ice-making systems. Furthermore, thermo-hydraulic evaluation using SEC confirms that a 5-minute defrost duration optimally balances energy efficiency and production capacity, providing a validated experimental benchmark for defrost optimization in large-scale ammonia-based tube ice systems.
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Energy-Efficient Paddy Rice Dehumidification using a Thermosyphon System
(2025-07-01)
Poungthong, Pongthep
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Promprasansuk, Sookjai
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Tanaratchat, Vikorn
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Promchai, Anuruk
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Ritthong, Wirote
Efficient post-harvest drying is vital to maintain paddy rice quality, prevent spoilage, and extend storage life. This study presents a thermosyphon-based dehumidification system, tested with hot air and hot water heating at 60, 70, and 80 °C. The system includes a cylindrical drying chamber with automated controls for higher efficiency. Performance was evaluated using drying time, energy efficiency, and specific energy consumption (SEC). Results showed the system reduced paddy rice moisture from 26.65% to the target 14% (d.b.). Drying times with hot air were 128, 76, and 50 hours, while hot water required 104, 62, and 42 hours at 60, 70, and 80 °C, respectively. Hot water at 80°C achieved the fastest drying, completing the process in 42 hours. Energy performance analysis revealed the lowest SEC of 89.05 kWh/kg water for hot water at 80 °C, whereas hot air at 60 °C recorded the highest SEC of 1,204 kWh/kgwate. Overall, the thermosyphon system demonstrated strong potential for balancing drying speed and energy use. The study supports thermosyphon-based drying as a scalable, energy-efficient solution for post-harvest rice management, with hot water offering both rapid drying and efficiency
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Sustainable Practices and Environmental Impact Assessment in a Lifelong Learning Center
(2024-01-01)
Koiwanit, Jarotwan
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Areerob, Yonrapach
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Saepoo, Sakkarin
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Filimonau, Viachaslau
Climate change is a major environmental challenge that should be mitigated by all parties concerned. One such party is the KMITL Lifelong Learning Canter (KLLC) which has committed to reducing its environmental externalities, including the impact of its operations on climate change. The idea of a “green KLLC” seeks to reduce adverse effects on the environment and improve indoor environmental quality through the use of natural building materials and biodegradable products, resource conservation (water, energy, paper), responsible waste disposal, and eco-friendly practices (recycling). To reduce these environmental externalities, the environmental performance of the KLLC canter should first be examined to establish measures for improvement. However, accurate evaluations of the environmental impact of Lifelong Learning Centers (LLCs) are uncommon because of the lack of data and the immaturity of appraisal methodologies. With a case study of KLLC, the newest LLC in Thailand, this paper appraises the environmental effects, thus setting benchmarks for subsequent studies. The appraisal demonstrates that the KLLC community can significantly reduce the environmental consequences by using e-certificates, motion sensor light installation, banana leaf packaging, solar cell installation, and carpooling systems. Although e-certificates and banana leaf packaging are the most cost-effective methods of implementation, the adoption of carpooling systems and electric vehicles demonstrates the highest potential for Greenhouse Gas (GHG) emissions reduction. The paper showcases how KLLC can reduce its GHG emissions and wastes, thus turning into a more environmentally sustainable business.
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Feasibility study of a combined system of electricity generation and cooling from liquefied natural gas to reduce the electricity cost of data centres
(2022-09-01)
Sermsuk, Maytungkorn
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Sukjai, Yanin
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Wiboonrat, Montri
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Kiatkittipong, Kunlanan
Global data centre power demands would expand from 286 TWh in 2016 to around 321 TWh in 2030. The cooling system represents electricity consumption of approximately 40–50% of the total energy used. The global LNG trade has reached 356.1 MTPA. Cold energy equal to 89025 GW is released into the ocean. Therefore, this study focused on the technical and economic feasibility of an LNG receiving terminal combined with a data centre using a direct expansion cycle (DEC), a Rankine cycle (RC) and a combination of Rankine cycle and direct expansion cycle (RC + DEC) under different natural gas distribution pressures to produce a supply of cooling water and electricity to reduce electricity consumption and greenhouse gas emissions. According to the study, the RC + DEC produces the maximum cold water at 7 °C, with the total cold energy of 44.23 MW which is sufficient for cooling a data centre with a capacity of 5345 racks, to reduce the electricity for conventional cooling system is 13521 kWh and generated electricity form turbine is 9968 kWh. This research has the potential to reduce the operating costs of data centres by more than USD 23.87 million per annum as well as CO<inf>2</inf> emissions by 83859 t per annum with exergy efficiency of 78.94%. In an economic study, indicated a payback period of 1.60 years with an IRR of 62%.
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System Performance Enhancement with Energy Efficiency Based Sleep Control for 5G Heterogeneous Cellular Networks
(2022-04-01)
Dataesatu, Arif
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Sanada, Kosuke
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Hatano, Hiroyuki
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Mori, Kazuo
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Boonsrimuang, Pisit
This paper presents an improved sleep control algorithm for small base stations (SBSs) in 5G New Radio (NR) heterogeneous cellular networks (HetNets). HetNets consist of various base station tiers, including macro base stations (MBSs) and small base stations (SBSs), and have been suggested as a promising solution to enhance wireless coverage and network capacity, employing many SBSs into the MBS coverage. However, power consumption increases significantly as a result of an increase in the number of the SBSs. To solve this problem, the SBS sleep control has been proposed to reduce power consumption for the SBSs and improves energy efficiency, whereas it deteriorates system throughput compared with no sleep control system, consequently degrading the quality of service (QoS) performance at user equipments (UEs). This paper proposes an enhanced algorithm for SBS sleep control based on energy efficiency as a decision criterion for SBS operating state. From the evaluation results through computer simulation, the proposed scheme can provide improved performance for both energy efficiency and system throughput simultaneously, that is it can improve energy efficiency while maintaining almost the same system throughput as the no sleep control system. Concretely, the proposed scheme has the 14.89% improvement in energy efficiency while providing almost the same system throughput of over 99%, compared with no sleep control system
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ENERGY LOSS MODEL FOR TIER 2 AND TIER 3 DATA CENTERS
(2022-01-01)
Wiboonrat, Montri
Demand for energy for data centers has soared during the COVID-19 pandemic. In 2020, the demand for energy for data centers is around 1% of worldwide electricity consumption and will be 3-13% in 2030. Energy loss in data centers is the main focus of this research. An energy loss model has been constructed to investigate data center power distribution systems (PDS). The model found that the highest energy loss is from the power supply unit (PSU) of IT equipment and the uninterruptible power supply (UPS). A server upgrade to PSU 80 PLUS Titanium reduces energy loss by around 2.7 times when compared with a normal PSU. These amounts of energy loss affect long-term operatingexpenses over the course of the data center’s lifetime. Moreover, this research compares PDS of Tier II and Tier III data centers to measure energy loss. The research results demonstrate that Tier III data centers lost approximately 1.782 times more energy through PDS than Tier II data centers.
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Overview of biorefinery
(2022-01-01)
Thongchul, Nuttha
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Charoensuppanimit, Pongtorn
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Anantpinijwatna, Amata
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Gani, Rafiqul
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Assabumrungrat, Suttichai
A strong reliance on fossil resources gives rise to a depletion of nonrenewable resources and negative or harmful environmental impacts. Circumvention of this energy-environment nexus has been proposed through the application of the concept of biorefinery. In this concept, biomass, an alternative renewable feedstock containing C-rich chemicals, is utilized as a replacement of the fossil-based feedstock to produce bioenergy and bio-based chemicals. Originally, biorefinery was perceived as a platform of biomass processing, which would produce primarily fuels and chemicals. To date, biorefinery harnesses a variety of sustainable and synergetic technologies that converts biomass into a wide range of profitable products such as food-and-feed for the future, biopharmaceuticals, and nutraceuticals. Due to variability of feedstock and newly emerged technologies, classifications of biorefinery are diverse and depend on the basis (e.g., source of a biomass, the generation of a feedstock, etc.) taken in consideration. A comprehensive view of biorefinery requires the consideration of processing of biomass from different origins via diversified technology platforms. Since the concept of biorefinery also concerns social aspects and location-specific technologies, various aspects of stakeholders including academia, industry, economy, and society need also to be considered. Collaboration among the various actors is facilitated if necessary key information is easily accessible. Therefore, an overview of biorefinery should cover key information related to biorefinery, such as nature of biomass, current situation, available technologies, process design methods, associated tools, and analyses of processing routes along with case studies. In this chapter, the indices representing the key information related to biorefinery are arranged alphabetically and tabulated to enhance a good understanding of the concept of biorefinery.
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Utilising cold energy from liquefied natural gas (LNG) to reduce the electricity cost of data centres
(2021-10-01)
Sermsuk, Maytungkorn
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Sukjai, Yanin
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Wiboonrat, Montri
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Kiatkittipong, Kunlanan
The Office of the National Broadcasting and Telecommunications Commission has reported that, from 2014 to 2018, Thailand’s internet usage has grown six‐fold to 3.3 million terabytes per annum. This market trend highlights one of the policies of Thailand 4.0, with the aim of making Thailand a hub for information transfer in ASEAN. As a result, there will be a massive demand growth for data storage facilities in the near future. Data centres are regarded as the brain and heart of the digital industry and are essential for facilitating businesses in organising, processing, storing and disseminating large amounts of data. As the energy demand for equipment cooling contributes to over 37% of the total energy consumption, the data centres of the world’s leading companies, such as Amazon, Google, Microsoft and Facebook, are generally located in cold climate zones, such as Iceland, in order to reduce operating costs for cooling. Due to this reason, the possibility of data centres in Thailand is limited. Beneficially, PTTLNG, as the first liquified natural gas (LNG) terminal in Thailand, has processed the import, receiving, storage and regasification of LNG. The high abundance of cold energy inherently presented in LNG is normally lost to the surroundings during regasification. Presently, PTTLNG’s LNG receiving terminal utilises a heat exchanger with propane as an intermediate fluid to transfer cold energy from LNG to water. This cold energy, in the form of cold water, is then used in several projects within the LNG receiving terminal: (1) production of electricity via an organic Rankine cycle capacity of 5 MWh; (2) cooling the air inlet of gas turbine generators to increase the generator efficiency; (3) replacing refrigerant heating, ventilation and air conditioning systems within buildings; (4) development of winter plantations with precision agriculture to replace imported products. Therefore, this study focuses on the potential and future use for LNG cold energy by performing a thermodynamic and economic analysis of the use of LNG cold energy as a source to produce cold water at 7 °C, with the total cold energy of 27.77 to 34.15 MW or 7934 t to 9757 t of refrigeration depending on the target pressure of the natural gas to replace the conventional cooling system of data centres. This research has the potential to reduce the cooling operation costs of data centres by more than USD 9.87 million per annum as well as CO2 emissions by 34,772 t per annum. In an economic study, this research could lead to a payback period of 7 years with IRR 13% for the LNG receiving terminal and a payback period of 2.21 years with IRR 45% for digital companies.
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Energy Efficiency Enhancement in 5G Heterogeneous Cellular Networks Using System Throughput Based Sleep Control Scheme
(2020-02-01)
Dataesatu, Arif
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Boonsrimuang, Pornpawit
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Mori, Kazuo
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Boonsrimuang, Pisit
Currently, Cellular architectures are designed with an efficient providing infrastructure is one of the critical challenges in 5G dense heterogeneous cellular networks (HetNets). By adding many small base stations (SBSs) in a macro base station (MBS) is one way to support the rapid growth of mobile data communication, high data rate services and to provide continuous coverage. The high number of network elements leads to a significant increase in power consumption. To solve the problem, the SBS on/off algorithm has been introduced to reduce power consumption but also reduced energy efficiency as we called the conventional schemes. This paper we proposed as the SBS switching to sleep state algorithm based on the system throughput (MBS cell throughput and SBS cell throughput) is used the decision criteria for SBS to be in the sleep state. The simulation results, The proposed scheme can reduce the total power consumption of the network and enhance energy efficiency more than the conventional schemes.
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Robot arm structure design using polyamide evaluated by finite element analysis
(2020-01-01)
Kaitwanidvilai, Somyot
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Buthgate, Siwawong
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Aoyama, Hisayuki
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Konghuayrob, Poom
Robots have increasingly replaced humans for many jobs, including 24 h work, routine tasks, and dangerous jobs. However, the robot operating system has high power consumption in many processes. This has led to energy efficiency being the main focus. We have opted to build a robot with high strength, light weight, and low power consumption by reducing the weight of its components. Presently, we know that the structure of most robots in the world is made of metals, plastics, and composite materials. In this research, we designed the mechanical structure of robot arms with three different materials (cast iron, polyamide, and aluminum) using the finite element method to analyze and evaluate the possibilities of these materials. The dynamic load, power consumption, and mechanical characteristics were compared. It was found that polyamide could help lighten the weight by 40% and increase energy efficiency along with cost effectiveness by 41%. Although polyamide is particularly easy to find, cast iron is stronger than polyamide.

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