• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1131-1138
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• 2019

The importance of coatings has been increasing for different purposes such as prevention of static electricity of auto parts or products, improvement of abrasion and corrosion resistance, and enhancement of esthetics. As a method for measuring the thickness of a coating film, a contact method with probe is commonly used. However, it is problematic that accuracy of the sensor is degraded due to sensor output distortion or load phenomenon, which is caused by a change in magnetic permeability of the core. In this study, we propose a method to reduce the measurement error of the coating film by applying the optimized circuit design and the thickness measurement algorithm to the problems caused by the nonlinear characteristics. The tests result which have been taken with different thickness coating samples show that the measurement accuracy is within ${\pm}2%$.

• Transactions of the Korean hydrogen and new energy society
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• v.30 no.2
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• pp.136-146
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• 2019

A solid oxide fuel cell (SOFC) based hybrid desiccant cooling system model is developed to study the effect of fuel utilization rate of the SOFC on the reduction of energy consumption and $CO_2$ emission. The SOFC-based hybrid desiccant cooling system consists of an SOFC system and a Hybrid desiccant cooling system (HDCS). The SOFC system includes a stack and balance of plant (BOP), and HDCS. The HDCS consists of desiccant rotor, indirect evaporative cooler, electric heat pump (EHP), and heat exchangers. In this study, using energy load data of a commercial office building and SOFC-based HDCS model, the amount of ton of oil equivalent (TOE) and ton of $CO_2$ ($tCO_2$) are calculated and compared with the TOE and $tCO_2$ generation of the EHP using grid electricity.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.87-92
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• 2019

This paper describes the pattern analysis for data of the factory energy consumption by using machine learning method. While usual statistical methods or approaches require specific equations to represent the physical characteristics of the plant, machine learning based approach uses historical data and calculate the result effectively. Although rule-based approach calculates energy usage with the physical equations, it is hard to identify the exact equations that represent the factory's characteristics and hidden variables affecting the results. Whereas the machine learning approach is relatively useful to find the relations quickly between the data. The factory has several components directly affecting to the electricity consumption which are machines, light, computers and indoor systems like HVAC (heating, ventilation and air conditioning). The energy loads from those components are generated in real-time and these data can be shown in time-series. The various sensors were installed in the factory to construct the database by collecting the energy usage data from the components. After preliminary statistical analysis for data mining, time-series clustering techniques are applied to extract the energy load pattern. This research can attributes to develop Factory Energy Management System (FEMS).

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1223-1230
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• 2021

Recently, energy resource management is a major concern around the world. Energy management activities minimize environmental impacts of the energy production. This paper presents design and prototyping of a home electric energy monitoring system that provides residential consumers with real time information about their electricity use. The developed system is composed of an in-house sensing system and a server system. The in-home sensing system is a set of wireless smart plug which have an AC power socket, a relay to switch the socket ON/OFF, a CT sensor to sense current of load appliance and a Kmote. The Kmote is a wireless communication interface based on TinyOS. Each sensing node sends its detection signal to a home gateway via wireless link. The home gateway stores the received signals into a remote database. The server system is composed of a database server and a web server, which provides web-based monitoring system to residential consumers. We analyzed and presented energy consumption data from electrical appliances for 3 months in home. The experimental results show the promising possibilities to estimate the energy consumption patterns and the current status.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.365-371
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• 2021

In this study, The Virtual Power Plant (VPP) solution platform considered in this study minimizes the cost and investment risk associated with the construction of power generation and transmission facilities. In addition, it includes a Demand Response (DR) program operation function to meet consumers' electricity demand. With the introduction of VPP, it is possible to provide more eco-friendly and efficient power by responding to changes in consumer load in real time through existing generators and DR programs without large-scale facility investment in power generation and transmission/distribution sectors. In order to link the communication device to the solar power and ESS linkage device, it is necessary to transmit data in the control/state between the device device and the edge system and develop an IoT device and interworking platform (OneM2M).

• Steel and Composite Structures
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• v.41 no.5
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• pp.681-695
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• 2021

Many existing transmission or communication towers designed several decades ago have undergone nonreversible performance degradation, making it hardly meet the additional requirements from upgrades in wind load design codes and extra services of electricity and communication. Therefore, a new-type non-destructive reinforcement method was proposed to reduce the on-site operation of drilling and welding for improving the quality and efficiency of reinforcement. Six built-up steel angle members were tested under compression to examine the reinforcement performance. Subsequently, the cyclic loading test was conducted on a pair of steel angle tower sub-structures to investigate the reinforcement effect, and a simplified prediction method was finally established for calculating the buckling bearing capacity of those new-type retrofitted built-up steel angles. The results indicates that: no apparent difference exists in the initial stiffness for the built-up specimens compared to the unreinforced steel angles; retrofitting the steel angles by single-bolt clamps can guarantee a relatively reasonable reinforcement effect and is suggested for the reduced additional weight and higher construction efficiency; for the substructure test, the latticed substructure retrofitted by the proposed reinforcement method significantly improves the lateral stiffness, the non-deformability and energy dissipation capacity; moreover, an apparent pinching behavior exists in the hysteretic loops, and there is no obvious yield plateau in the skeleton curves; finally, the accuracy validation result indicates that the proposed theoretical model achieves a reasonable agreement with the test results. Accordingly, this study can provide valuable references for the design and application of the non-destructive upgrading project of steel angle towers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• Environmental and Resource Economics Review
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• v.15 no.4
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• pp.693-712
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• 2006

A pre-feasibility test is done for renewable energy hybrid power systems at off~grid islands in which the current power supply is provided only by diesel generation. We apply Homer (Hybrid Optimization Model for Electric Renewables) which was developed by the National Renewable Energy Laboratory (NREL) for the analysis to identify the cost-minimizing combination of power generating facilities for the given load profiles. Chuja-Do, Geomun-Do and Youngsan-Do have been selected for our analysis considering the wind resources data of the Korea Institute of Energy Research (KIER). Information on wind speed, solar radiation and temperature is also used for the analysis. System component cost information from overseas market has been used due to the lack of domestic information. Site specific Load profile for electricity demand for those islands are reconstructed based on the partial survey results obtained form other sources. The LCOE of the least cost hybrid power systems for Chuja-Do, Geomun-Do and Youngsan-Do are $0.278/kWh, $0.234/kWh and $0.353/kWh, respectively Considering the fact that diesel generation is being subsidized at the price of $0.300/kWh by the government, first 2 cases are economically feasible for the introduction of renewable energy hybrid systems to those islands. But the third case of Youngsan-Do does not meet the criteria. The basic differences of these pre-feasibility test results are from the differences of the site specific renewable energy conditions, especially wind resources. In summary, promoting hybrid systems in the off-grid remote island should be based on the economic feasibility test results. Not all the off-grid islands are feasible for introducing this renewable energy hybrid system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.817-825
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• 2017

The AC-common bus microgrid system can overcome several weaknesses of the DC microgrid system by interconnecting the DC/AC inverters used for renewable energy with an AC network. Nevertheless, the unbalanced loads inherent in the electric power systems of island and small communities can deteriorate the performance of the AC microgrid system. This is because of the limited voltage regulation capability and mixed power flow in the voltage source inverter. In order to overcome the unbalanced load condition, this paper proposes a voltage and current control algorithm for the 4-leg inverter based on the single phase d-q control method, as well as the modeling of the voltage controller using Matlab/Simulink S/W. From the S/W simulation and experiment of the 250KW proto-type inverter, it is confirmed that the proposed algorithm is a useful tool for the design and operation of the AC microgrid system.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.107-114
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• 2017

In this paper, a novel power factor compensation system based on voltage-controlled method is proposed for 3-phase 4-wire power system. The proposed voltage-controlled power factor compensation system generates a reactive power required for compensation by applying a variable output voltage by a slidac to a capacitor. In conventional power factor compensation system using the capacitor bank method, the power factor compensation error occurs depending on the load condition due to the limited capacity of the capacitors. However, the proposed system compensates the power factor up to 100% without error. In this paper, we have developed a voltage-controlled power factor compensation system and a control algorithm for 3-phase 4-wire power system, and verify its performance through simulation and experiments. If the proposed power factor compensation system is applied to an industrial field, a power factor compensation performance can be maximized. As a result, it is possible to reduce of electricity prices, reduce of line loss, increase of load capacity, ensure the transmission margin capacity, and reduce the amount of power generation.