• Journal of KIBIM
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• v.4 no.1
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• pp.8-12
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• 2014

This research and project is going on the Korean government. The objective of project is that developing total energy management solution. So, this paper is going to introduce a proposal that energy total operating system development using spatial information visualization and energy monitoring. It could efficiently operate the building energy wirelessly controling cooling/heating, lighting, air-conditioning and geothermal system. The metering data is collected to total database. The data is linked to BAS gateway, which is connected the device by the standard protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2676-2689
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• 2013

Due to increased consumption of energy in the building environment, the building energy management systems (BEMS) solution has been developed to achieve energy saving and efficiency. However, because of the shortage of building energy management specialists and incompatibility among the energy management systems of different vendors, the BEMS solution can only be applied to limited buildings individually. To solve these problems, we propose a building cluster based remote energy monitoring and management (EMM) system and its functionalities and roles of each sub-system to simultaneously manage the energy problems of several buildings. We also introduce a novel energy demand forecasting algorithm by using past energy consumption data. Extensive performance evaluation study shows that the proposed regression based energy demand forecasting model is well fitted to the actual energy consumption model, and it also outperforms the artificial neural network (ANN) based forecasting model.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.4
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• pp.213-219
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• 2015

Real-time energy monitoring systems is a demand-response system which is reported to be effective in saving energy up to 12%. Real-time energy monitoring system is commonly composed of smart-plugs which sense how much electrical power is consumed and IHD(In-Home Display device) which displays power consumption patterns. Even though the monitoring system is effective, users should themselves match which smart plus is connected to which appliance. In order to make the matching work to be automatic, the monitoring system need to have appliance identification algorithm, and some works have made under the name of NILM(Non-Intrusive Load Monitoring). This paper proposed an algorithm which utilizes multiple classifiers to improve accuracy of appliance identification. The algorithm proposes to understand each classifiers performance, that is, when a classifier make a result how much the result is reliable, and utilize it in choosing the final result among result candidates from many classifiers. By using the proposed algorithm this paper make 4.5% of improved accuracy with respect to using single best classifier, and 2.9% of improved accuracy with respect to other method using multiple classifiers, so called CDM(Commitee Decision Mechanism) method.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.171-178
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• 2006

In advanced countries, state-of-the-art temperature monitoring technique is widely used for effective use of geothermal resources. But these kind of modern tools such as Thermal Line Sensor has not been applied to find geothermal characteristics of alluvium and riverbed in domestic area. In this research, state-of-the-art thermal line temperature sensor monitoring was introduced. And long term field test using this type of sensor was performed to find geothermal characteristics of alluvium and riverbed and evaluate the availability for heat energy source. As a result, temperature monitoring technique through thermal line sensor was very effective to obtain basic geothermal information of alluvium deposit and riverbed. Also, it was found that the groundwater temperature phase showed its potential of utilization as a energy source of heat pump. It is estimated that further study shows a specific corelation between temperature monitoring data and its availability as a energy source.

• Korean Journal of Computational Design and Engineering
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• v.18 no.6
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• pp.451-460
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• 2013

This paper presents the necessary elements and data flow in developing a monitoring system of energy usage for apartment houses with a Smart TV. Energy consumption data in each home are collected and analyzed in the HUB station by way of measuring instruments. And the amount of energy usage, such as electricity, gas, hot water, heating, water and other utilities are displayed through the Smart TV application. Energy consumption Database in the HUB station are processed and displayed in the browser of a Smart TV through XML, JAVASCRIPT and Flash. Smart TV users can get the energy consumption status through the energy consumption analysis display of the Smart TV application and improve the energy efficiency by comparing the usage patterns with neighboring houses. And the application display energy usage information, consumption ranking, rates to user as well. Furthermore, usage of last month or year can be compared to help to reduce the energy usage. The proposed system can provide the information about the amount of energy use to be reduced and the warning on the waste of energy.

• Advances in Energy Research
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• v.7 no.2
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• pp.123-134
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• 2020

Photovoltaic systems are progressively attached importance and their installed capacity increases day by day because of their reliability, decremented installation and operating cost and simple construction structure. Generated power obtained from a photovoltaic system changes depending upon regional distinctness, and It can be estimated approximately by taking into consideration mean global radiation amount, temperature and humidity. However, there may be different regional negative or positive factors like dust, air pollution, desert powder which affect generated power. The best reliable data for a region can be obtained from the existing photovoltaic system in the region. For this purpose, a monitoring system for 1000W monocrystalline photovoltaic system constructed at Kocaeli University Uzunciftlik Nuh Cimento Vocational High Scholl is prepared. The installed monitoring system shows and records real values generated from the photovoltaic system and environmental data. In the study, Instantaneous data obtained from the monitoring system for October 2018 and 7th October 2018 is given within figures. Additionally, daily and monthly total energy productions of the photovoltaic system are given for October 2018 and date interval between July 2018 and March 2018, respectively.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.1
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• pp.69-74
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• 1998

In order to monitor the tool wear in milling operation, cutting force is measured as the tool wear increased. The digital signal processing methods are used to detect the tool wear . As AR parameter extract the feature of tool wear , it can be used as input parameter of pattern classifier. The FFT monitor the tool wear exactly , but it can not do real time signal processing. The band energy method can be used to real time monitoring of tool wear ,but int can degrade the exact monitoring.

• Journal of Wind Energy
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• v.14 no.4
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• pp.43-49
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• 2023

We have studied biofouling in Korea's offshore wind farms by using image analysis through monitoring and surface energy analysis. To observe the biofouling characteristics, samples were fabricated using Micron extra 2 and PropOne, which have a self-polishing property, and Hempathane HS 55610, which is used in substructure coatings. The manufactured samples were installed at the bottom of a ladder in a substructure, and monitored for 10 months. The most biofouling occurred in the sample without the self-polishing property, and algae, barnacles and corallinales were observed. The surface energy analysis used the Owens-Wendt-Rabel and Kaelble (OWRK) model, which uses the contact angles of two standard fluids. As a result of calculating the surface energy using contact angle measurement, the sample without the self-polishing property showed the highest value. This result was consistent with the biofouling incidence observed through monitoring.

• Applied Science and Convergence Technology
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• v.23 no.6
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• pp.357-365
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• 2014

A non-invasive method for ion energy distribution measurement at a RF biased surface is proposed for monitoring the property of ion bombardments in capacitively coupled plasma sources. To obtain the ion energy distribution, the measured electrode voltage is analyzed based on the circuit model which is developed with the linearized sheath capacitance on the assumption that the RF driven sheath behaves like a simple diode for a bias power whose frequency is much lower than the ion plasma frequency. The method is verified by comparing the ion energy distribution function obtained from the proposed model with the experimental result taken from the ion energy analyzer in a dual cathode capacitively coupled plasma source driven by a 100 MHz source power and a 400 kHz bias power.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.127-135
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• 2022

With the advent of high technologies such as the 4th Industrial Revolution and artificial intelligence and big data, efforts are being made to solve urban problems and improve the quality of life by applying new technologies in the smart city field. In addition, as carbon neutrality has emerged as an important issue due to global warming, smart city energy platform technologies such as urban energy management, efficiency improvement, and carbon reduction are in the spotlight. In order to effectively manage urban energy, energy resource information such as electricity, water, gas, hot water, heating, etc. must be collected from the management system of various energy utilities and managed on the central platform. The centrally integrated data is delivered to external city management systems that require city energy information through an energy platform. This study developed a CIM profile for smart city energy monitoring required to provide energy data to external systems. Electric data model were designed using the CIM class of IEC 61970, and water, gas, and heat data model were designed in compliance with the UML-based design ideas of IEC 61970.