• Environmental Engineering Research
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• v.22 no.2
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• pp.175-185
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• 2017

As the energy and environmental problems are increasingly severe, researches about carbon dioxide emissions has aroused widespread concern. The accurate prediction of carbon dioxide emissions is essential for carbon emissions controlling. In this paper, we analyze the relationship between carbon dioxide emissions and influencing factors in a comprehensive way through correlation analysis and regression analysis, achieving the effective screening of key factors from 16 preliminary selected factors including GDP, total population, total energy consumption, power generation, steel production coal consumption, private owned automobile quantity, etc. Then fruit fly algorithm is used to optimize the parameters of least squares support vector machine. And the optimized model is used for prediction, overcoming the blindness of parameter selection in least squares support vector machine and maximizing the training speed and global searching ability accordingly. The results show that the prediction accuracy of carbon dioxide emissions is improved effectively. Besides, we conclude economic and environmental policy implications on the basis of analysis and calculation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.1
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• pp.72-81
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• 2014

Recently, because of irregular power demand, we have suffered from an electric power shortage. The necessity of the adoption of smart grid which makes effective supply of power by using the two-way communication across the grid between the customers and electric energy providers is growing more and more. If smart grid set up in our country, the third-parties which provide services to customer using the information acquired from smart grid, might be revved up. In this paper, we suggest a methodology how classify the types of family by analysing an power consumption pattern using data mining technique. To make a classifier for categorizing the household types, we need power consumption data and their family type. However, it is hard to get both of them. Therefore we develop the simulator that generates power consumption patterns of the household and classify the types of family. Also, we present a potential for application services such as customized services for a specific family or goods marketing.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.235-237
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• 1996

This paper shows a reasonable power demand method and load characteristics in underground streets, that was made by the systematic and statistical way considering actual conditions, such as investigated electric equipment capacity, electric power consumption, load characteristics, etc for 13 underground streets.

• Journal of the Korean Society for Railway
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• v.14 no.2
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• pp.167-173
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• 2011

This paper considers the problem of revising train departure time to reduce electric power consumption of mass rapid transit (MRT) railways. The motion of a train running between stations is divided into three phases: traction, coasting, and deceleration phases. The traction phase requires high electric power to operate MRT railways. In the coasting phase, the train moves stably by consuming little or no power. The deceleration phase is a braking mode and produces some electric power called regenerated brake power owing to inertia force for the train generated In the traction and coasting phases. The regenerative energy can be used by other accelerating trains within a specific range from the train and thereby the power consumptions of train can be reduced. We developed a mixed integer programming model to solve the problem. To validate the suggested model, a computational experiment was conducted using real data from Korea Metropolitan Subway.

• Journal of Hydrogen and New Energy
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• v.31 no.3
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• pp.322-327
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• 2020

In this work, a study for the reduction of the electric power consumption has been estimated in main air compressors in the air separation unit through cryogenic distillation columns with PRO/II with PROVISION V10.2 at AVEVA company. Both required LNG mass flow rate and cold heat contained in 1 ton of LNG were also predicted using Peng-Robinson equation of state with Twu's new alpha function. Through this work, we concluded that 32.33-48.69% of electric power could be saved by using LNG cold heat.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.23-24
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• 2011

Recently, it is required EV(Electric Vehicles) charging infra construction for approaching to accelerate and to commercialize development of EV. In this study, it was introduced basic overview of EV and charging infra construction. and we're supposed rate of growth and reduction of the number of registered vehicles by considering about last 3 years and supposed automatic number. This paper was produced dissemination if demand of EV would constantly increase. We compared and analyzed the relationship of 5th power supply and power consumption.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.284-291
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• 2018

As environmental pollution has become worse green technologies to replace or reduce consumption of fossil fuel get spotlight from government, industry and academia globally. It is reported that 40% of carbon dioxide emission is caused by electricity power generation. And 37% of end user electricity power is used by residential costumer in US. Smart Grid is considered as one of promising technology to alleviate severe environmental problem. In residential environment, Home Energy Management System (HEMS) can play a key role for green smart home. The HEMS can give several benefits like aslowering electric utility bill, improvement of efficiency of electric power consumption and integration of generator using renewable energy resources. However just limited functions of HEMS can be used for residential customer in real life because of lack of smart function in home appliances and optimal managing software for HEMS. This study provides comprehensive analysis for Home Energy Management System for residential customer. Simple HEMS system with real products on the market are explained and limitation of current HEMS are also discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.378-379
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• 2012

Nowadays, great energy consumption in advanced electrical industry has called up the great y efficiency. Electric power IT industry such as intelligent electric power system is receiving great attention and being marked up as a new growth engine. Through Intelligent electric power system, the electric power supply can be balance optimized according to demand, giving huge cost savings advantage for energy imports, infrastructure construction and operation. Nevertheless, the intelligent system promotes better reliability in power supply. Manual electric power management using man power appears to be non-practical. Real time electric power management on all facilities and equipment can be done through an intelligent electric power system, any accident break out issue can be easily recorded and recognized. In this paper, a fully integrated intelligent switchgear electric management system is developed to monitor and remote control the electrical switch based on smart phone. The proposed system is superior than the existing switchgear management system's weakness and can sharply improve effectiveness and stability with low cost. In future, the proposed system is expected to be greatly contributed to the advancement of the IT industry in electric power management.

• JOURNAL OF ELECTRICAL WORLD
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• no.11 s.155
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• pp.31-34
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• 1989

• JOURNAL OF ELECTRICAL WORLD
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• no.8 s.152
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• pp.21-26
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• 1989