메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술대회자료
저자정보
Dongsu Kim (Hanbat National University) Gu Seomun (Hanbat National University) Jongho Yoon (Hanbat National University) Heejin Cho (Hanbat National University)
저널정보
대한설비공학회 대한설비공학회 학술발표대회논문집 대한설비공학회 2022년도 동계학술발표대회 논문집
발행연도
2022.11
수록면
150 - 153 (4page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
This study develops an optimized HVAC control framework using the whole building energy simulation program (i.e., EnerguPlus) and functional mock-up unit (FMU) in the Python environment. To develop and implement this framwork, a building energy model using EnergyPlus was developed based on the existing test facility. The model was initially validated using measured data (e.g., indoor air temperature comparison) before implementing the co-simulation framework. For the co-simulation framework using EnergyPlus and FMU, there are four (4) steps: 1) a real-time weather file modification by FMU, 2) an optimization process (i.e., GenOpt application) based on one hour ahead prediction weather data, 3) an optimized signal point application to EnergyPlus IDF file, and 4) output extraction from the completed simulation within the functional mock-up interface (FMI) with Python. The weather file modification was performed based on onsite measured and obtained weather data values. This study adopted some weather data from the public weather station API. The GenOpt application was also implemented within the Python environment under a developed GUI automated workflow by modifying the GenOpt source code. The PMV-based control scheme is considered in this study to determine the optimized signal point. Based on such framework development. This study identifies that the co-simulation environment can predict hour-ahead loads by considering optimized thermal comfort and real-time weather data. Such predicted outputs (e.g., thermal loads and setpoints) can be expected to use for further building energy management, such as BEMS, by applying an HVAC control scheme. Additionally, the developed framework techniques will help to be a key solution to implement the digital twins of smart homes and buildings.

목차

Abstract
1. Introduction
2. Methodology
3. Results and discussion
References

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0