• Smart Media Journal
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• v.8 no.4
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• pp.72-79
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• 2019

The automated demand response (DR) program encourages consumers to participate in grid operation by reducing power consumption or deferring electricity usage at peak time automatically. However, successful deployment of the automated DR program sphere needs careful assessment of appliances load profile (ALP). To this end, the recent method estimates frequency, consistency, and peak time consumption parameters of the daily ALP to compute their potential score to be involved in the DR event. Nonetheless, as the daily ALP is subject to varying with respect to the DR time ALP, the existing method could lead to an inappropriate estimation; in such a case, inappropriate appliances would be selected at the automated DR operation that effected a consumer comfort level. To address this challenge, we propose a more proper method, in which all the three parameters are calculated using ALP that overlaps with DR time, not the total daily profile. Furthermore, evaluation of our method using two public residential electricity consumption data sets, i.e., REDD and REFIT, shows that our energy management systems (EMS) could properly match a DR target. A more optimal selection of appliances for the DR event achieves a power consumption decreasing target with minimum comfort level reduction. We believe that our approach could prevent the loss of both utility and consumers. It helps the successful automated DR deployment by maintaining the consumers' willingness to participate in the program.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1516-1529
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• 2016

While global manufacturing is becoming more competitive due to variety of customer demand, increase in production cost and uncertainty in resource availability, the future ability of manufacturing industries depends upon the implementation of Smart Factory. With the convergence of new information and communication technology, Smart Factory enables manufacturers to respond quickly to customer demand and minimize resource usage while maximizing productivity performance. This paper presents the development of a big data analytics platform architecture for Smart Factory. As this platform represents a conceptual software structure needed to implement data-driven decision-making mechanism in shop floors, it enables the creation and use of diagnosis, prediction and optimization models through the use of data analytics and big data. The completion of implementing the platform will help manufacturers: 1) acquire an advanced technology towards manufacturing intelligence, 2) implement a cost-effective analytics environment through the use of standardized data interfaces and open-source solutions, 3) obtain a technical reference for time-efficiently implementing an analytics modeling environment, and 4) eventually improve productivity performance in manufacturing systems. This paper also presents a technical architecture for big data infrastructure, which we are implementing, and a case study to demonstrate energy-predictive analytics in a machine tool system.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.838-840
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• 1998

The power demand has increased the groth of industry and improvement of life. Otherwise the power supply is more difficult. because of regional egoism, reinforcement for environment, and investment of money. The load installation should be promoted to rational power management, according to the network, inteligent, and high-function. Therefore, this paper is made a study for the method of energy saving and for energy saving of medium-small type small type-below 500kW medium type-between $500{\sim}1.000kW$.

• Journal of Industrial Technology
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• v.30 no.A
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• pp.9-15
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• 2010

Recently, Smart Grid is a emerging topic in power and communication industry. Smart Grid refers to a evolution of the electricity supply infrastructure that monitors, protects, and intelligently optimize the operation of the interconnected elements including various type of generators, power grid, building/home automation system and end-use consumers. In order to successful implementation of Smart Grid, energy management function will be the key factor that coordinates and optimally controls the various loads according to the operating condition and environments, and the load patterns in residential and commercial building will be required as fundamental element for load management. In this study, we collects many types of energy usage data of electric appliances, analyze their load curves, and make the general load patterns for electrical appliance.

• Journal of Korea Society of Waste Management
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• v.35 no.7
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• pp.571-586
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• 2018

The Malaysian biogas upgrading technologies and policies were examined. In Malaysia, the regulation of palm oil mill effluent (POME) has been enforced to reduce the biochemical oxygen demand to 20 ppm and the biogas capture in the palm oil mills have been recently enforced for renewable energy. A huge amount of organic waste is produced from POME, and 80 million tons from palm oil trees, every year. Due to the renewable energy trends, the Malaysian government is modifying the use of biogases as fuels in favor of their conversion into compressed natural gas (CNG) and other chemicals; various green policies are being promoted because of many advantages of the organic substances. The Korean policies for biogas are a good model for exporting environmental plants after upgrading the digestion and purification technologies. Therefore, this article introduces the current status of POME and biogas production in Malaysia, it could encourage creating a new market for biomethane.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.49-67
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• 2014

This paper proposes a real time pricing model for smart grid considering consumers' behavior, real time price elasticity, and exogenous price. Based on the proposed model, we found the weight of utility over cost is the most sensitive factor compared to other factors. Also, if the electricity price is set to be changed too sensitively to energy consumption, it is warned that real time pricing sometimes can cause increment of peak-time demand and volatility. Finally, real time pricing could be less efficient when the difference between the maximum and the minimum consumption level is small.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.9
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• pp.535-541
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• 2003

Demand Side Management (DSM) activities have been designed to encourage customers to modify their patterns of electricity consumption including the timing and level of electricity demand. The role of DSM has been more and more important in the point of social energy utilization on the limited resources. The objectives of DSM are generally related to load reductions and generation cost savings. This paper presents an approach to B/C analysis to evaluate the impact of DSM programs especially on the strategic conservation and the load management programs. The proposed approach embedding the existing B/C analyses is applicable to the new electricity market. Case studies show the B/C ratio and the avoided cost due to the impact of DSM programs.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.201-211
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• 2001

The most general treatment method of municipal solid waste is a landfill. The LFG (landfill gas) migration is a serious problem in environmental aspect. The object of this study is to present the possibility of LFG utilization as a replacement or supplementary fuel for local energy -demand. We have developed the EXCEL program for the economic analysis.

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.147-155
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• 2011

For an effective energy management in intelligent buildings it is necessary to gather information about position/absence of people and the level of population. In this paper the smart occupancy detection system based on the active RFID is developed to satisfy such a demand. The performance of the developed system is tested and verified through various experiments. Furthermore the feasibility test of the active RFID tag is performed to verify whether it can be used as a location-based occupancy sensor. The developed core technology can be also applied to other fields such as security, healthcare, smart home, etc.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.182-184
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• 2005

The human beings have Increased concern about Energy saving and alternative energy. The power demand has increased the growth of industry and the improvement of life We have to explore alternate energy sources and utilize effectively domestic resources. The lighting equipments developed Energy saving by using an electric ballast. The load installation should be promoted to rational power management, according to the network, intelligent, and high-function. Therefore, this paper has studied the method of energy saving and consulting.