• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.215-220
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• 2007

최근 센서 네트워크에서 에너지 효율성을 위한 다양한 연구가 진행 중이다. 특히 센서 노드의 저전력을 위해서는 센서 네트워크에서 전송되는 데이터의 횟수나 전송량을 최소한으로 줄이면서 효율적이면서 신뢰성을 가지는 질의에 대한 결과를 얻을 수 있어야 한다. 본 연구에서는 해양 센서 네트워크 상에서 데이터의 전송량을 줄일 수 있는 SDMTree(Sensing Data Management Tree)를 제안한다. 제안된 SDMTree는 질의 최적화를 위해 질의 처리기 구성 요소로 도입 가능하다. 해양 센서 네트워크에서 in-network 각 4레벨에서 하위 노드로부터 받은 데이터를 병합, 관리하기 위한 방법으로 데이터를 속성별로 구분하여 중복된 데이터를 제거하여 트리형태로 구성되기 때문에 질의에 대한 응답에 해당하는 데이터 검색시 정확하고 신속하게 처리할 수 있으며, 트리 구성 또한 중복 데이터 및 중복 영역을 배제하여 구성되므로, 상위노드가 하위 노드로부터 센싱 데이터를 수집하여 저장하기 위한 에너지와 상위 노드에서 하위 노드로 질의를 전송시 질의에 해당하는 특정 영역에만 질의를 전송할 수 있기 때문에 데이터 저장 및 통신에 소모되는 불필요한 에너지를 최대한 줄일 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.343-345
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• 2018

전력 발전사들은 해안을 중심으로 운영되고 있는데, 이는 발전하는 과정에서 회전기기 터빈과 발전기 열을 냉각시키기 위해 해수를 사용한 후, 발생한 온배수는 해안으로 방출되고 있다. 양식장에는 수온 관리를 하는데 큰 비용이 발생하기 때문에 수열에너지를 공급하는데는 경제적으로 매우 중요하다. 따라서 효율적인 스마트 양식장을 운용하기 위해서는 발전소에서 폐수로 방출되는 온배수 에너지원을 재생에너지로 활용하여 이 열을 저장하고 양식수조에 공급하는 온배수 히트펌프의 수온 제어시스템과 양식수조의 최적화 설계를 위하여 새로운 형태의 육상수조 양식구조와 수질과 수온을 제어하는 IoT(Internet of Things)기반의 스마트 양식장이 필요하다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.8-15
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• 2020

A forecasting method using deep learning does not have consistent results due to the differences in the characteristics of the dataset, even though they have the same forecasting models and parameters. For example, the forecasting model X optimized with dataset A would not produce the optimized result with another dataset B. The forecasting model with the characteristics of the dataset needs to be optimized to increase the accuracy of the forecasting model. Therefore, this paper proposes novel optimization steps for outlier removal, dataset classification, and a CNN-LSTM-based hyperparameter tuning process to forecast the daily power usage of a university campus based on the hourly interval. The proposing model produces high forecasting accuracy with a 2% of MAPE with a single power input variable. The proposing model can be used in EMS to suggest improved strategies to users and consequently to improve the power efficiency.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.149-160
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• 2011

Smart Grid is the next-generation intelligent power grid that maximizes energy efficiency with the convergence of IT technologies and the existing power grid. It enables consumers to check power rates in real time for active power consumption. It also enables suppliers to measure their expected power generation load, which stabilizes the operation of the power system. However, there are high possibility that various kinds of security threats such as data exposure, data theft, and privacy invasion may occur in interactive communication with intelligent devices. Therefore, to establish a secure environment for responding to such security threat with the smart grid, the key management technique, which is the core of the development of a security mechanism, is required. Using a hash chain, this paper suggests a group key management mechanism that is efficiently applicable to the smart grid environment with its hierarchical structure, and analyzes the security and efficiency of the suggested group key management mechanism.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2063-2072
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• 2013

Smart Grid is the next-generation intelligent power grid that maximizes energy efficiency with the convergence of IT technologies and the existing power grid. It enables consumers to check power rates in real time for active power consumption. It also enables suppliers to measure their expected power generation load, which stabilizes the operation of the power system. However, there are high possibility that various kinds of security threats such as data exposure, data theft, and privacy invasion may occur in interactive communication with intelligent devices. Therefore, to establish a secure environment for responding to such security threat with the smart grid, the key management technique, which is the core of the development of a security mechanism, is required. Using a hash chain, this paper suggests a group key management mechanism that is efficiently applicable to the smart grid environment with its hierarchical structure, and analyzes the security and efficiency of the suggested group key management framework.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.157-163
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• 2019

K-BEMS System was introduced to reduce peak load and to save total energy of the 120 buildings that KEPCO headquarter and branch offices use. K-BEMS system is composed of PV, battery, and hybrid PCS. In this system, ESS, PV, lighting is used to save building energy based on demand prediction. Currently, neural network technique for short past data is applied to demand prediction, and fixed scheduling method by operator for ESS charging/discharging is used. To enhance this system, KEPCO research institute has carried out this K-BEMS research project for 3 years since January 2016. As the result of this project, we developed new real-time highly reliable building demand prediction technique with error free and optimized automatic ESS charging/discharging technique. Through several field test, we can certify the developed algorithm performance successfully. So we will describe the details in this paper.

• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.745-754
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• 2013

The systematic analysis and evaluation of required energy in the processes of drinking water production and supply have attracted considerable interest considering the need to overcome electricity shortage and control greenhouse gas emissions. On the basis of a review of existing research results, a practical method is developed in this study for evaluating energy in water supply networks. The proposed method can be applied to real water supply systems. A model based on the proposed method is developed by combining the hydraulic analysis results that are obtained using the EPANET2 software with a mathematical energy model on the MATLAB platform. It is suggested that performance indicators can evaluate the inherent efficiency of water supply facilities as well as their operational efficiency depending on the pipeline layout, pipe condition, and leakage level. The developed model is validated by applying it to virtual and real water supply systems. It is expected that the management of electric power demand on the peak time of water supply and the planning of an energy-efficient water supply system can be effectively achieved by the optimal management of energy by the proposed method in this study.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.205-212
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• 2023

In the modern society, the extreme weather caused by climate change has brought about exceptional damage in succession over the world due to the use of fossil fuels, and infectious diseases such as COVID-19 worsen the quality of human life. It is urgently necessary to reduce green-house gas and use new renewable energy. The global environmental pollution should be decreased by reducing the use of fossil fuels and using new renewable energy. This paper suggests a system which can function for the environment of four seasons, safety and communication, through the photovoltaic power-based intelligent CCTV, internet and WiFi, and cooling and heating systems, and can optimally manage power, through the real-time monitoring of the production and the consumption of the photovoltaic power. It suggests a hybrid generation system supporting diesel generation without discontinuation in the case of emergency such as system power outage caused by cold waves, typhoons and natural disasters in which the photovoltaic power generating system cannot be used.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.867-878
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• 2006

In the past few years, the research of sensor networks is forced dramatically. Specially, while the research for maintaining the power of a sensor is focused, we are also concerned nth query processing related with the optimization of multiple continuous queries for decreasing in unnecessary energy consumption of sensor networks. We present the fragmentation algorithm to solve the redundancy problem in multiple continuous queries that increases in the count or the amount of transmitting data in sensor networks. The fragmentation algorithm splits one query into more than two queries using the query index (QR-4ree) in order to reduce the redundant query region between a newly created query and the existing queries. The R*-tree should be reorganized to the QR-tree right to the structure suggested. In the result, we preserve 20 percentage of the total energy in the sensor networks.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.87-95
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• 2018

Due to global warming and increased energy costs around the world, interests of energy saving and efficiency have been increased. In particular, forging factories need methods to save energy and increase productivity because of needing amounts of energy uses. To solve the problem, we propose a system, which includes collection, monitoring, and analysis process, to monitor energy uses each facility in realtime based on the IoT devices. This system insists of worksheets management, facility/energy management, realtime monitoring, history search, data analysis through connecting with existed ERP/MES Systems in manufacturing factories. The energy monitoring process is to present used energy collected from IoT devices connected with installed gasmeter and wattmeter each facility. This system provide the change of energy uses, usage fee, energy conversion, and green gas information in realtime on Web and mobile devices. This system will be enhanced with energy saving technology by analyzing constructed big data of energy uses. We can also propose a method to increase productivity by integrating this system with functions of digitalized worksheets and optimized models for production process.