• KIEAE Journal
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• v.14 no.5
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• pp.59-65
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• 2014

Nowadays, reduction of energy use in buildings is a big issue, especially in public buildings like schools. The building structure is very simple in that, the room size, schedule and user number is similar across different schools. There are many policies which are suitable for this kind of buildings. Investigation of energy consumption pattern in primary school, middle school and high school in different cities of Korea has been done in this paper using statistical data from national organization and the data from IBM and Gyeonggi Provincial Office of Education, aimed at providing the basic data for the development of energy efficiency improvement policies of educational facilities. The study was divided according to climate, energy source type and public or private school, as different cities have different climates and accordingly different amount of energy sources are used. It was observed that, the average energy consumption in primary school is $36.9kWh/m^2$, in middle school is $20.5kWh/m^2$ and in high school $27.4kWh/m^2$. As further analysis, monthly energy consumption pattern has been analyzed for one city.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1079-1080
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• 2006

This paper presents the methods to save energy by using load consumption pattern analysis. Base on the substation annual power usage data, the characteristic of the substation power consumption have investigated. With this investigation effective electrical billing condition and the control target load has been determined. Most of power usage comes from the motor car, so power system and load table of motor car were reviewed. And in the metropolitan area the peak power consumption occurs at summer or winter rush hours because of its typical characteristics. From this data control point of time are determined. Through the whole study the methode to control the power Peak consumption are proposed and prototype was designed.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.414-424
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• 2015

In this research, we consider a smart grid network of electricity with multiple consumers connected to a monopolistic provider. Each consumer can be informed the real time price changes through the smart meter and updates his consumption schedule to minimize the energy consumption expenditures by which the required power demand should be satisfied under the given real time pricing scheme. This real-time decision making problem has been recently studied through game-theoretic approach. The present paper contributes to the existing literature by incorporating storage appliance into the set of available household appliances which has somewhat distinctive functions compared to other types of appliances and would be regarded to play a significant role in energy consumption scheduling for the future smart grid. We propose a game-theoretic algorithm which could draw the optimal energy consumption scheduling for each household appliances including storage. Results on simulation data showed that the storage contributed to increase the efficiency of energy consumption pattern in the viewpoint of not only individual consumer but also whole system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1451-1459
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• 2011

Recently, low energy houses have become an essential issue globally and various subsidy programs are ongoing to penetrate. All-electric houses which are another type of low energy houses or zero carbon houses are being developed. These houses consider new & renewable energy and demand side management programs in the construction and the diffusion process because these programs are essential policies to use energy resources reasonably. This paper shows a simulation methodology to control home appliances in all-electric houses considering the electricity consumption pattern of residents. The simulation is a first step to estimate energy saving of the house in a practical manner.

• YAKHAK HOEJI
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• v.57 no.2
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• pp.110-118
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• 2013

High-caffeine energy drink consumption has been increasing in young adults, frequently causing the most common symptoms such as tremor, insomnia, anxiety, and nervousness and rarely leading to serious adverse effects like seizure, acute mania, and stroke due to caffeine overdose. There have been little current studies regarding analysis of high-caffeine energy drink consumption and its adverse effects in Korea. This study was to examine high-caffeine consumption patterns, associated factors, and adverse effects based on responses from 231 college students in a University through survey. About 88.3% (n=204) of total respondents reported that they had energy drinks. College students mostly consumed energy drinks to keep awake (46%) when studying and to recover fatigue (27%). Approximately 44% respondents mainly reported palpitation (73.9%) and insomnia (72.8%) regarding adverse effect questionnaire. Current reports on the risk of recreational use, co-ingestion of alcohol and energy drink as well as energy drink consumption among children and adolescents are increasing, requiring further long-term research and awareness of these issues.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.9
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• pp.1368-1373
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• 2012

In this paper, we propose an efficient driving pattern which consumes less energy for driving from one station to next. Three driving patterns for four sections in the No. 5 subway line of Seoul Metropolitan Rapid Transit Corp. are compared for the energy consumption, the maximum speed, and the powering time. It turns out that the powering time and the maximum speed should be decreased as much as possible in order to achieve the efficient driving.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.3
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• pp.151-160
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• 2018

NAND flash memories have the advantages of fast access speed, high density and low power consumption, thus they have increasing demand in embedded system and mobile environment. Despite the low power and fast speed gains of NAND flash memory, DRAM disk buffers were used because of the performance load and limited durability of NAND flash cell. However, DRAM disk buffers are not suitable for limited energy environments due to their high static energy consumption. In this paper, we propose WAP-LRU (Write pattern Analysis based Placement by LRU) hybrid disk buffer management policy. Our policy designates the buffer location in the hybrid memory by analyzing write pattern of the workloads to check the continuity of the page operations. In our simulation, WAP-LRU increased the lifetime of NAND flash memory by reducing the number of garbage collections by 63.1% on average. In addition, energy consumption is reduced by an average of 53.4% compared to DRAM disk buffers.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.285-304
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• 2017

Big data information and pattern analysis have applications in many industrial sectors. To reduce energy consumption effectively, the eco-driving method that reduces the fuel consumption of vehicles has recently come under scrutiny. Using big data on commercial vehicles obtained from digital tachographs (DTGs), it is possible not only to aid traffic safety but also improve eco-driving. In this study, we estimate fuel consumption efficiency by processing and analyzing DTG big data for commercial vehicles using parallel processing with the MapReduce mechanism. Compared to the conventional measurement of fuel consumption using the On-Board Diagnostics II (OBD-II) device, in this paper, we use actual DTG data and OBD-II fuel consumption data to identify meaningful relationships to calculate fuel efficiency rates. Based on the driving pattern extracted from DTG data, estimating fuel consumption is possible by analyzing driving patterns obtained only from DTG big data.

• Proceedings of the KSR Conference
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• 2002.05a
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• pp.431-436
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• 2002

Train driving should be satisfied to run fixed distance within given time, and it is desirable to minimize energy consumption. Minimizing energy consumption depends on the train operation modes by driver or automatic operation. In this article, an optimal operation to minimize energy consumption by changing modes of train operation by a driver is investigated. First, powering model, braking model and consumed energy calculation model are introduced by using Matlab software. The accuracy of the model established by simulation is compared with the real experimental data, which is obtained from an authorized institution. Second, several simulations under a variety of operations in the ideal track are executed, and then the optimal pattern of train driving is found.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1546-1564
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• 2012

Pattern-based query processing has not attracted much attention in wireless sensor network though its counterpart has been studied extensively in data stream. The methods used for data stream usually consume large memory and much energy. This conflicts with the fact that wireless sensor networks are heavily constrained by their hardware resources. In this paper, we use piece wise representation to represent sensor nodes' collected data to save sensor nodes' memory and to reduce the energy consumption for query. After getting data stream's and patterns' approximated line segments, we record each line's slope. We do similar matching on slope sequences. We compute the dynamic time warping distance between slope sequences. If the distance is less than user defined threshold, we say that the subsequence is similar to the pattern. We do experiments on STM32W108 processor to evaluate our strategy's performance compared with naive method. The results show that our strategy's matching precision is less than that of naive method, but our method's energy consumption is much better than that of naive approach. The strategy proposed in this paper can be used in wireless sensor network to process pattern-based queries.