• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Journal of Bio-Environment Control
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• v.21 no.2
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• pp.79-87
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• 2012

This research was conducted to obtain basic data with regard to the heating performance that would be produced by installing an aluminum hot water pipe inside the greenhouse with the goal of reducing the heating energy in greenhouse. The research results are summarized as follows. The degree of difference in relation to the temperature by height within the greenhouse during the entire experiment was significant - within the range of 4.0~$7.0^{\circ}C$. The temperature difference between incoming and outgoing water was about $3.3^{\circ}C$ greater when FCU was activated compared to when it was not activated. Meanwhile, the amount of energy consumed increased about 36.2~40.1%. The amount of pyrexia per hour also increased by 44.6~52.0%. During the experiment period, circulated flux was within the range of 0.48~$0.49L{\cdot}s^{-1}$ while average fluid speed was 1.53~$1.56m{\cdot}s^{-1}$. The average temperature difference between incoming and outgoing water was 6.24~$11.50^{\circ}C$. The amount of heating value by each set temperature within the minimum outdoor temperature range of -14.0~$-0.6^{\circ}C$ was 135,930~307,150 kcal, and the range was within the 9,610~$19,630kcal{\cdot}h^{-1}$ per hour. This demonstrated that about 23~53% heating energy of the maximum heating load could be supplied. Total radiating value and amount of energy consumed were 2,548,306 kcal and 3,075.7 kWh, respectively. When heating takes place using oil, which is a fossil fuel, the total amount of light oil consumed was 281.6 L while the cost was 321,000 won. When the electricity cost for farms is applied, the total cost was about 110,730 won, which is about 33.5% of the cost required compared to oil consumption. The temperature at in the experiment area was about 8.3~$14.6^{\circ}C$ higher compared to that of the control area.

• Journal of Energy Engineering
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• v.28 no.3
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• pp.65-79
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• 2019

The study attempted to estimate the optimal facility capacity by combining renewable energy sources that can be connected with gas CHP in industrial complexes. In particular, we reviewed industrial complexes subject to energy use plan from 2013 to 2016. Although the regional designation was excluded, Sejong industrial complex, which has a fuel usage of 38 thousand TOE annually and a high heat density of $92.6Gcal/km^2{\cdot}h$, was selected for research. And we analyzed the optimal operation model of CHP Hybrid System linking fuel cell and photovoltaic power generation using HOMER Pro, a renewable energy hybrid system economic analysis program. In addition, in order to improve the reliability of the research by analyzing not only the heat demand but also the heat demand patterns for the dominant sectors in the thermal energy, the main supply energy source of CHP, the economic benefits were added to compare the relative benefits. As a result, the total indirect heat demand of Sejong industrial complex under construction was 378,282 Gcal per year, of which paper industry accounted for 77.7%, which is 293,754 Gcal per year. For the entire industrial complex indirect heat demand, a single CHP has an optimal capacity of 30,000 kW. In this case, CHP shares 275,707 Gcal and 72.8% of heat production, while peak load boiler PLB shares 103,240 Gcal and 27.2%. In the CHP, fuel cell, and photovoltaic combinations, the optimum capacity is 30,000 kW, 5,000 kW, and 1,980 kW, respectively. At this time, CHP shared 275,940 Gcal, 72.8%, fuel cell 12,390 Gcal, 3.3%, and PLB 90,620 Gcal, 23.9%. The CHP capacity was not reduced because an uneconomical alternative was found that required excessive operation of the PLB for insufficient heat production resulting from the CHP capacity reduction. On the other hand, in terms of indirect heat demand for the paper industry, which is the dominant industry, the optimal capacity of CHP, fuel cell, and photovoltaic combination is 25,000 kW, 5,000 kW, and 2,000 kW. The heat production was analyzed to be CHP 225,053 Gcal, 76.5%, fuel cell 11,215 Gcal, 3.8%, PLB 58,012 Gcal, 19.7%. However, the economic analysis results of the current electricity market and gas market confirm that the return on investment is impossible. However, we confirmed that the CHP Hybrid System, which combines CHP, fuel cell, and solar power, can improve management conditions of about KRW 9.3 billion annually for a single CHP system.

• FLOWER RESEARCH JOURNAL
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• v.18 no.3
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• pp.186-192
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• 2010

An infrared heating system, installed in a small venlo-type glasshouse ($280m^2$) in Gyeongsang National University, Jinju, Korea, was used to investigate its heating effect with potted Phalaenopsis, Schefflera arboricola 'Hongkong', Ficus elastica 'Variegata', and Rosa hybrida 'Yellow King' as the test plants. Temperature changes in test plants with the system turned 'On' and 'Off' were measured by using an infrared camera and the consumption of electricity by this infrared heating system was measured and analyzed. In potted Phalaenopsis, when the set air temperature of the greenhouse was $18^{\circ}C$, temperature of leaves and the growing medium were $22.8{\sim}27^{\circ}C$ and $21.3{\sim}24.3^{\circ}C$, respectively. In such tall plants as Schefflera arboricola 'Hongkong' and Ficus elastica 'Variegata', the upper part showed the highest temperature of 24.0 and $26.9^{\circ}C$, respectively. From the results of temperature change measurements, the plant temperatures were near or above the set point temperatures with some fluctuations depending on the position or distance from the infrared heating system. When air temperature between night and dawn dropped sharply, plant temperatures were maintained close to the set temperature ($18^{\circ}C$). There was a significant difference between 'On' and 'Off' states of the infrared heating system in average temperatures of root zone and leaf: 21.8 and $17.8^{\circ}C$ with the system 'On' and 20.4 and $15.5^{\circ}C$ with the system 'Off', respectively, in a cut rose Rosa hybrida 'Yellow King'. The heating load was about $24,850{\sim}35,830kcal{\cdot}h^{-1}$, which comes to about 27,000~40,000 won in Korean currency when calculated in terms of the cost of heating by a hot water heating system heated by petroleum. The cost for heating by the infrared heating system was about 35% of that of a hot water heating system. With the infrared heating system, the air temperature during the night was maintained slightly lower than the set point air temperature, probably due to the lack of air tightness of the glasshouse. Therefore, glasshouses with an infrared heating system requires further investigation including the installation space of the heat-emitting units, temperature sensor positions, and convection.