• Title/Summary/Keyword: 공장 에너지 관리

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A study on the development of the factory energy management system through energy consumption monitoring (에너지 사용량 모니터링을 통한 공장에너지관리시스템 개발에 관한 연구)

  • Kim, Beom-Joo;Kim, Dae-Hwan;Kim, Yong-Bae;Han, Jeong-Hoon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.11a
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    • pp.523-525
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    • 2020
  • 본 논문에서는 공장에너지관리를 위한 에너지관리시스템 개발에 대한 연구를 다루고 있다. 특히, 설비 교체나 고성능 또는 고가의 입출력 장비를 활용하는 것이 아닌, 공장에너지 사용량 모니터링에 대한 네트워크 구축을 통해 공장관리자에게 에너지를 효율적으로 사용하고 있는지를 알려주고, 이를 활용하여 에너지를 효율적으로 사용할 수 있는 서비스를 제공하고자 한다. 본 시스템은 서버를 구축하기 위한 별도 공간을 보유하고 있지 않은 중소형 공장을 대상으로 하기 위해 클라우드 서비스를 적용하여 제공한다.

Proposal of a Factory Energy Management Method Using Electric Vehicle Batteries (전기자동차 배터리를 활용한 공장의 에너지 관리 방안 제안)

  • Nam-Gi Park;Seok-Ju Lee;Byeong-Soo Go;Minh-Chau Dinh;Jun-Yeop Lee;Minwon Park
    • Journal of Korea Society of Industrial Information Systems
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    • v.29 no.3
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    • pp.67-77
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    • 2024
  • Increasing energy efficiency in factories is an activity aimed at optimizing resource allocation in manufacturing processes to establish production plans. However, this strategy may not apply effectively when night shifts are unavoidable. Additionally, continuous fluctuations in production requirements pose challenges for its implementation in the factory. Recently, with the rapid proliferation of electric vehicles (EVs), technology utilizing electric vehicle batteries as energy storage systems has gained attention. Technology using these batteries can be an alternative for factory energy management. In this paper, a factory energy management method using EV batteries is proposed. The proposed method is analyzed using PSCAD/EMTDC software, considering the state of charge of EV batteries and Time-of-Use (TOU) rates. The proposed method was compared with production scheduling established considering predicted power usage and TOU rates. As a result, production scheduling saved 4,152 KRW per day, while the proposed method saved 7,286 KRW in electricity costs. Through this paper, the possibility of utilizing EV batteries for factory energy management has been demonstrated.

Energy-Efficient Operation Simulation of Factory HVAC System based on Machine Learning (머신러닝 기반 공장 HVAC 시스템의 에너지 효율화 운영 시뮬레이션)

  • Seok-Ju Lee;Van Quan Dao
    • Journal of Korea Society of Industrial Information Systems
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    • v.29 no.2
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    • pp.47-54
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    • 2024
  • The global decrease in traditional energy resources has prompted increasing energy demand, necessitating efforts to replace and optimize energy sources. This study focuses on enhancing energy efficiency in manufacturing plants, known for their high energy consumption. Through simulations and analyses, the study proposes a temperature-based control system for HVAC (Heating, Ventilating, and Air Conditioning) operations, utilizing machine learning algorithms to predict and optimize factory temperatures. The results indicate that this approach, particularly the prediction-based free cooling algorithm, can achieve over 10% energy savings compared to existing systems. This paper presents that implementing an efficient HVAC control system can significantly reduce overall factory energy consumption, with plans to apply it to real factories in the future.

자동제어시리즈 (2) - 빌딩 에너지관리 시스템(BEMS) 보급과 활성화 방안

  • Sin, Yeong-Gi
    • 월간 기계설비
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    • s.228
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    • pp.55-63
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    • 2009
  • 본지는 자동제어실비협의회(위원장 최전남) 제공으로 지난 호부터 자동제어 시리즈를 게재하고 있다. 이번 호에는 빌딩 에너지관리 시스템으로 세종대학교 신영기 교수의 '빌딩 에너지관리 시스템 보급과 활성화 방안'을 게재한다. 빌딩 에너지관리 시스템은 실내환경과 에너지 성능의 최적화를 도모하기 위한 시스템으로 업무용 빌딩이나 공장, 지역 냉난방의 에너지설비에 대한 에너지절약, 감시, 제어를 자동화 일원화 하는 시스템이다.

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Comparison and Evaluation of Data Collection System Database for Edge-Based Lightweight Platform (엣지 기반 경량화 플랫폼을 위한 데이터 수집 시스템의 데이터베이스 비교 및 평가)

  • Woojin Cho;Chae-young Lim;Jae-hoi Gu
    • Journal of Platform Technology
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    • v.11 no.5
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    • pp.49-58
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    • 2023
  • Factory energy management system is rapidly growing and evolving due to factors such as the 3rd Basic Energy Plan and global energy cost increases, as well as environmental issues. However, implementing an essential data collection system for energy management in factory settings, which have limited space and unique characteristics, presents spatial, environmental, and energy-related challenges. This paper endeavors to mitigate these challenges by devising a data collection system implemented through an edge-based lightweight platform. A comparison and evaluation of database operation on edge devices are conducted. To conduct the evaluation, a benchmarking tool called CDI Benchmark is developed, utilizing the characteristics of existing factories involved in practical applications. The evaluation results revealed that RDBMS systems like MySQL encountered errors in the database due to high data insertion loads, making them inoperable. On the other hand, InfluxDB, thanks to its highly efficient compression algorithm, demonstrated compression rates about 6 times higher than MyRocks according to the evaluation. However, it was observed that MyRocks outperformed InfluxDB by a significant margin, recording a maximum processing time approximately 80 times faster compared to InfluxDB.

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The Development of a Energy Monitoring System based on Data Collected from Food Factories (식품공장 수집 데이터 기반 에너지 모니터링 시스템 개발)

  • Chae-Eun Yeo;Woo-jin Cho;Jae-Hoi Gu
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.1001-1006
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    • 2023
  • Globally, rising energy costs and increased energy demand are important issues for the food processing and manufacturing industries, which consume significant amounts of energy throughout the supply chain. Accordingly, there is a need for the development of a real-time energy monitoring and analysis system that can optimize energy use. In this study, a food factory energy monitoring system was proposed based on IoT installed in a food factory, including monitoring of each facility, energy supply and usage monitoring for the heat treatment process, and search functions. The system is based on the IoT sensor of the food processing plant and consists of PLC, database server, OPC-UA server, UI server, API server, and CIMON's HMI. The proposed system builds big data for food factories and provides facility-specific monitoring through collection functions, as well as energy supply and usage monitoring and search service functions for the heat treatment process. This data collection-based energy monitoring system will serve as a guide for the development of a small and medium-sized factory energy monitoring and management system for energy savings. In the future, this system can be used to identify and analyze energy usage to create quantitative energy saving measures that optimize process work.

주거 공간 에너지 관리 ICT 기술

  • Gang, Seong-Cheol;Choe, Jin-Sik
    • Information and Communications Magazine
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    • v.34 no.5
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    • pp.45-52
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    • 2017
  • 전체 전력 사용량 중 주거공간에서의 전력사용 비율이 점차적으로 증가하고 있으며 이로 인한 화석연료 사용의 증가는 기후 변화 및 환경오염에 두 번째로 큰 밀접한 관계를 보이고 있다. 이를 개선하기 위하여 현재의 빌딩과 공장 중심의 에너지 관리에서 더 나아가 주거공간을 위한 에너지 관리 기술의 발전이 필요한 상황이다. 주거 공간의 에너지 관리 솔루션을 찾기 위하여 수용가를 위한 국내외 에너지 관리 표준화 현황을 살펴본 후 이와 관련되어 있는 요소기술들과 통신기술을 중심으로 주거 공간 에너지 관리 ICT 기술들에 대하여 정리해 보았다.