• Title/Summary/Keyword: BEMS

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Developing Optimal Pre-Cooling Model Based on Statistical Analysis of BEMS Data in Air Handling Unit (BEMS 데이터의 통계적 분석에 기반한 공조기 최적 예냉운전 모델 개발)

  • Choi, Sun-Kyu;Kwak, Ro-Yeul;Goo, Sang-Heon
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.26 no.10
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    • pp.467-473
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    • 2014

  • Since the operating conditions of HVAC systems are different from those for which they are designed, on-going commissioning is required to optimize the energy consumed and the environment in the building. This study presents a methodology to analyze operational data and its applications. A predicted operation model is to be produced through a statistical data analysis using multiple regressions in SPSS. In this model, the dependent variable is the pre-cooling time, and the independent variables include the power output of the supply air inverter during pre-cooling, the supply air set temperature during pre-cooling, the indoor temperature-indoor set temperature just before pre-cooling, supply heat capacity, and the lowest outdoor air temperature during non-cooling/non-heating hours. The correlation coefficient R2 of the multiple regression model between the pre-cooling hour and the internal/external factors is of 0.612, and this could be used to provide information related to energy conservation and operating guidance.

  • https://doi.org/10.6110/KJACR.2014.26.10.467 인용 PDF KSCI

Design of Remote Building Energy Management System Based-on Data Warehouse (데이터 웨어하우스 기반의 원격 건물에너지 통합 관리 시스템 설계)

  • Kim, Tae-Hyung;Jeong, Yeon-Kwae;Lee, Il-Woo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.1110-1112
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    • 2015

  • 에너지 절감을 위해 다양한 분야에서 노력을 기울이고 있지만 전체 에너지 사용량의 약 20% 이상을 차지하는 건물 분야는 정부의 정책과 제도적인 지원 하에 에너지 절감활동을 활발하게 진행하고 있다. 특히 $3000m^2$ 이상의 중대형 건물의 경우 BEMS(Building Energy Management System)기반의 건물에너지 관리가 의무화 될 예정이다. 하지만 기존 BEMS의 경우 특정 기업에 의한 단독 솔루션 형태로 제공되고 있어 BEMS간 데이터 상호호환성을 보장하지 않고, 단순 모니터링 기능에 의존하여 저장/관리 되지 않고 버려지는 데이터들이 많아 차후 문제가 발생한 경우 과거 데이터를 통한 분석 작업에 어려움이 있다. 따라서 본 논문에서는 건물에너지 통합관리 측면에서 원격지에 설치된 다양한 BEMS들의 센서/미터 데이터들을 웹을 통해 수집하고 데이터 웨어하우스에 저장/관리되며 건물에너지 통계, 분석 및 진단을 가능하도록 하는 데이터 웨어하우스 기반의 원격 건물에너지 통합 관리 시스템 설계에 대해 서술한다.

  • https://doi.org/10.3745/PKIPS.y2015m10a.1110 인용 PDF

Artificial Neural Network Models for Optimal Start and Stop of Chiller and AHU (인공신경망 모델을 이용한 냉동기 및 공조기 최적 기동/정지 제어)

  • Park, SungHo;Ahn, Ki Uhn;Hwang, Aaron;Choi, Sunkyu;Park, Cheol Soo
    • Journal of the Architectural Institute of Korea Structure & Construction
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    • v.35 no.2
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    • pp.45-52
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    • 2019

  • BEMS(Building Energy Management Systems) have been applied to office buildings and collect relevant building energy data, e.g. temperatures, mass flow rates and energy consumptions of building mechanical systems and indoor spaces. The aforementioned measured data can be beneficially utilized for developing data-driven machine learning models which can be then used as part of MPC(Model Predictive Control) and/or optimal control strategies. In this study, the authors developed ANN(Artificial Neural Network) models of an AHU (Air Handling Unit) and a chiller for a real-life office building using BEMS data. Based on the ANN models, the authors developed optimal control strategies, e.g. daily operation schedule with regard to optimal start and stop of the AHU and the chiller (500 RT). It was found that due to the optimal start and stop of the AHU and the chiller, 4.5% and 16.4% of operation hours of the AHU and the chiller could be saved, compared to an existing operation.

  • https://doi.org/10.5659/JAIK_SC.2019.35.2.45 인용 KSCI