• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.354-359
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• 2012

With the long-term use of fossil fuel, the whole world is suffering from serious abnormal changes in weather caused by global warming. For this reason, many countries are reducing greenhouse gas emissions out of obligation and the allowable emissions are assigned to each country. Korea is also putting much effort into reducing greenhouse gas emissions by 30 percent against BAU(Business As Usual) by 2020, and is pushing ahead with several projects such as 'Million Green Home' and 'Hatsal Gaduk Home' to expand the use of new renewable energy in house as part of its policy. This study was designed to come up with improvements and help to expand photovoltaic facilities, by investigating and analyzing the current state of photovoltaic facilities in the country and problems in installing them through an in-site reconnaissance and a survey in Jecheon area. As the result, it was found that residents in the area were inadequate to operate and install photovoltaic facilities, lacked awareness of them and felt burdened economically by managing and installing them, although they had a high awareness of solar energy and photovoltaic facilities are constantly increasing with governmental support. In conclusion, it is considered that as improvements, operational effects should be increased through development of techniques, factors to reduce the effects in operating them due to insufficient management and installation should be removed and awareness of residents need to be improved through long-term plans, political support and education of the government.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.97-115
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• 2022

Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.289-290
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• 2012

This paper proposes a new active snubber boost PFC converter to provide a zero-voltage-switching (ZVS) turn-on condition and reduce electromagnetic interference (EMI) noise in home appliances and renewable energy applications, including solar or fuel cell electric systems. The proposed active snubber circuit enables a main boost switch of the boost-type PFC or grid converter to turn on under a ZVS condition and reduce the switching losses of the main boost switch. Moreover, for the purpose of a specialized intelligent power module (IPM) fabrication, the proposed boost circuit is designed to satisfy some design aspects such as space saving, low cost, and easy fabrication. Simulation and experimental results of a 2kW IPM boost-type PFC converter are provided to verify the effectiveness of the proposed active snubber boost circuit.

• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.93-98
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• 2011

A photovoltaic/thermal(PVT)collector produces both thermal energy and electricity simultaneously. The heat from PV modules should be removed for better electrical performance, and can be converted into useful thermal energy. A PVT module is a combination of PV module with a solar thermal collector which forms one device that converts solar radiation into electricity and heat. In general, there are two different types of PVT module: glazed PVT module and unglazed PVT module. On the other hand, two types of the PVT module can be distinguished according to absorber on PV module rear side: the sheet-and-tube absorber PVT module and the fully wetted absorber PVT module. The absorber collector plays an important function in PVT system. It cools down the PV module, while collecting the thermal energy produced in the form of hot water. The aim of this study is to compare the electrical and thermal performance of two different PVT collectors, one with the rectangular tube and the other with fully wetted absorber PVT collectors. For this paper, the PVT collectors with two different types of thermal absorber were made, and both the thermal and electrical performance of them were measured in outdoor, and the results were compared. The experimental results were analyzed that the thermal efficiency of the fully wetted absorber PVT collector is about 8.7% higher than the sheet-and-tube absorber PVT collector, and for the electrical efficiency, the fully wetted absorber PVT collector had about 7% higher than the rectangular tube absorber.

• Journal of Energy Engineering
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• v.29 no.1
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• pp.44-51
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• 2020

The importance of ESS has been emphasized due to stabilization of power demand due to deterioration of network reliability and expansion of renewable energy sources. ESS (Energy Storage System) stores the remaining power and uses it when necessary to meet the power demand, and build the ESS system mainly in conjunction with solar and wind power. In this paper, we propose a home PV Charging Module using the Master-Slave method which is effective for low insolation. After designing the module, Fast MPPT algorithm is applied to generate the maximum output from the nonlinear output characteristics of the PV modules. The average power value for the input of PV Charging Module was 296.90 W and the output power was 289.60 W, which averaged 97.54%.

• Transactions on Electrical and Electronic Materials
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• v.13 no.5
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• pp.256-261
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• 2012

Recently, many photovoltaic systems (PV systems) including solar parks and PV farms have been built to prepare for the post fossil fuel era. To investigate the degradation process of the PV systems and thus, efficiently operate PV systems, there is a need to visually monitor PV systems in the range of infrared ray through the Internet. For efficient visual monitoring, this paper explores a multithreaded implementation of a recently developed HEVC standard whose compression efficiency is almost two times higher than H.264. For an efficient parallel implementation under a meshbased 64 multicore system, this work takes into account various design choices which can solve potential problems of a two-dimensional interconnects-based 64 multicore system. These problems may have not occurred in a small-scale multicore system based on a simple bus network. Through extensive evaluation, this paper shows that, for an efficient multithreaded implementation of HEVC intra prediction in a mesh-based multicore system, much effort needs to be made to optimize communications among processing cores. Thus, this work provides three design choices regarding communications, i.e., main thread core location, cache home policy, and maximum coding unit size. These design choices are shown to improve the overall parallel performance of the HEVC intra prediction algorithm by up to 42%, achieving a 7 times higher speed-up.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.21-28
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• 2021

In this study, we propose a deep learning-based NILM technique using actual measured power data for 5 kinds of home appliances and verify its effectiveness. For about 3 weeks, the active power of the central power measuring device and five kinds of home appliances (refrigerator, induction, TV, washing machine, air cleaner) was individually measured. The preprocessing method of the measured data was introduced, and characteristics of each household appliance were analyzed through spectogram analysis. The characteristics of each household appliance are organized into a learning data set. All the power data measured by the central power measuring device and 5 kinds of home appliances were time-series mapping, and training was performed using a LSTM neural network, which is excellent for time series data prediction. An algorithm that can disaggregate five types of energies using only the power data of the main central power measuring device is proposed.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1183-1194
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• 2021

Traditionally, electric power systems have been known as the centralized structures, which is organized into placing customers at the end of the supply chain. However, recent decades have witnessed the emergence of distributed energy resources(:DERs) such as rooftop solar, farming PV system, small wind turbines, battery energy storage systems and smart home appliances. With the emergence of distributed energy resources, the role of distributed system operators(:DSOs) will expand. The increasing penetration of DERs could lead to a less predictable and reverse flow of power in the system, which can affect the traditional planning and operation of distribution and transmission networks. This raises the need for a change in the role of the DSOs that have conventionally planned, maintained and managed networks and supply outages. The objective of this research is to designed the future distribution operation system with multi-DERs and the proposed distribution system model is implemented by hardware-in-the-loop simulation(HILS). The test results show the normal operation domain and reduction of distribution line loss.

• 한국태양에너지학회:학술대회논문집
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• 2011.04a
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• pp.179-184
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• 2011

The development of new energy has attracted consideration attention due to the high oil price and environmental problems. In advanced country, they have tried to carry out a long range plan for energy. We need to develop new energy for Low Carbon Green Growth in Korea. The building is 30% among ratio of energy consumption in Korea. And in the past, heating energy was high ratio for energy using at home. But recently, the demand for cooling energy keeps growing due to rising average temperature on the earth and improvement of life quality. In this situation, the energy of lake water and ocean water has studied to utilize in advanced country because of low temperature at underwater. But the study for deep water is still a lot left to do. In this study, we analyzed district cooling system and the present condition. Analyzing the deep lake water cooling system in Toronto, we found an application of district cooling system using deep ocean water. Deep lake water uses heat source for district cooling and water source for city in Toronto. So reducing the initial cost, this city had economic effect. When DLWC was applied at existing building, the heat exchanger was installed instead of cooling tower and refrigerator. And the heat exchanger used to connect main pipe with cool water on city. System using deep ocean water can be applied as a similar way to supply cool water from lake to building.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.871-874
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• 2010

Needs for Smart Grid development are increasing all over the world as a solution to its problem according to depletion of energy resources, climatic and environmental rapidly change and growing demand for electrical power. Especially decentralized power is attracting world's attention. In this mood a new era for a unit scale of decentralized power environment is on its way in building. However there is a problem to have to be solved in the uniformity of power quality because the amount of power generated from renewable energy resources such as wind power and solar light is very sensitive to climate fluctuation. And thus this paper tries to suggest an energy management method on basis of real time monitoring for meteorological data. In the current situation of lacking in USN-based killer application in Smart Grid field, this paper proposes the USN-based DER management system which collects the meteorological data and control power system througout utilizing wireless sensor network technique this business. This communication technique is regarded to be efficient in aspects of installation cost and tits maintenance cost. The proposed EMS model embodies the method for predicting the power generation by monitoring and analyzing the climatic data and controling the efficient power distribution between the renewable energy and the existing power. The ultimate goal of this paper is to provide the technological basis for achieving zero-energy house.