• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.45 no.10
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• pp.62-68
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• 2016

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.334-335
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• 2011

국내에는 다양한 스마트 전력기기들이 충분히 개발되어 있는 상황으로 빌딩의 전력 관리 시스템(이하 BEMS)를 구축하고 효율적으로 사용하기 위한 인프라가 충분히 갖추어 있다. 하지만 기존 건물 내배선의 유연성 부족으로, 효율적인 운영을 위해서는 상태 정보를 취득하고 이를 바탕으로 전기 설비 구조 변경 공사를 통할 수밖에 없는 상황이다. 그리고 빌딩의 대형화에 따라 전력 사용량이 커짐으로, 운영을 통한 효율성 관리 여지가 커지고 있다. 따라서 본 문에서는 빌딩 내 전력 배분의 유연성을 가질 수 있는 전력 설비를 투자하고 이를 운영하기 위해 취득 데이터를 바탕으로 3상 급전 해석 코어를 설계하고 BEMS에 추가적으로 운영을 지원하는 시스템을 설계한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.7
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• pp.787-792
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• 2015

In this paper, We described the implementation of the Smart Gateway for heterogeneous interface integrated, Web Server and Building Energy Management System(: BEMS). The proposed system introduces the reduction of peak power and electric power usage with service model and operating algorithm for energy saving in building.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.5
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• pp.86-93
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• 2015

Recently, ESS became efficient device to stabilize electric power supply system with the development SG related technology. In fact. there are some constraints to supply ESS, because of the high cost and required space, but rapid technology development for ESS will make it more useful soon. So, through this paper, we analyzed the benefit and demand effect when the battery is applied the building based on the measured energy consumption. After that, we got the conclusion that there is a volume limit in ESS application, in a benefit view point. And we realized that there is a demand violation, and the Cost-based BEMS is the best solution to enhance the effect of ESS application.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.82-86
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• 2019

We aim to use public data different from the remote BEMS energy diagnostics technology and already established and then switch the conventional operation environment to a big-data-based integrated management environment to operate and build a building energy management environment of maximized efficiency. In Step 1, various network management environments of the system integrated with a big data platform and the BEMS management system are used to collect logs created in various types of data by means of the big data platform. In Step 2, the collected data are stored in the HDFS (Hadoop Distributed File System) to manage the data in real time about internal and external changes on the basis of integration analysis, for example, relations and interrelation for automatic efficient management.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.45 no.10
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• pp.26-36
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• 2016

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.45 no.10
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• pp.40-48
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• 2016

• Smart Media Journal
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• v.12 no.11
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• pp.18-26
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• 2023

The building energy management system (BEMS), a system designed to efficiently manage energy production and consumption, aims to address the variable nature of power consumption within buildings due to their physical characteristics, necessitating stable power supply. In this context, accurate prediction of building energy consumption becomes crucial for ensuring reliable power delivery. Recent research has explored various approaches, including time series analysis, statistical analysis, and artificial intelligence, to predict power consumption. This paper analyzes the strengths and weaknesses of the Prophet model, choosing to utilize its advantages such as growth, seasonality, and holiday patterns, while also addressing its limitations related to data complexity and external variables like climatic data. To overcome these challenges, the paper proposes an algorithm that combines the Prophet model's strengths with the gated recurrent unit (GRU) to forecast short-term (2 days) and medium-term (7 days, 15 days, 30 days) building energy consumption. Experimental results demonstrate the superior performance of the proposed approach compared to conventional GRU and Prophet models.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.515-522
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• 2024

Energy consumption is steadily increasing, and buildings in particular account for more than 20% of the total energy consumption around the world. As an effort to cost-effectively manage the energy consumption of buildings, many research groups have recently focused on Smart Building Energy Management Systems (BEMS), which are deepening the research depth by applying artificial intelligence(AI). In this paper, we propose a reinforcement learning-based energy control method for smart energy buildings integrated with V2G station, which aims to reduce the total energy cost of the building. The results of performance evaluation based on the energy consumption data measured in the real-world building shows that the proposed method can gradually reduce the total energy costs of the building as the learning process progresses.

• The Magazine for Energy Service Companies
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• s.81
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• pp.28-29
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• 2013

본 문서는 정보통신산업진흥원에서 실시한 2012년 IT기반 ESCO 시범사업의 수행결과를 활용한 것이다. 향후 IT기술을 활용한 에너지 절감 사업을 수행하게 될 에너지 사용자 및 사업자에게 IT기술을 활용한 에너지 절감 방법과 시스템 구축 및 운영 노하우를 공유하도록 제작되었다.