کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6684316 501864 2016 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Development of a probabilistic graphical model for predicting building energy performance
ترجمه فارسی عنوان
توسعه یک مدل گرافیکی احتمالی برای پیش بینی عملکرد انرژی ساختمان
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی مهندسی انرژی و فناوری های برق
چکیده انگلیسی
This paper presents the development of a data driven probabilistic graphic model to predict building energy performance. A directed graphical model, namely, a Bayesian Networks (BNs) model is created. Each node in the BNs represents a random variable such as outside air temperature and energy end use. The links between the nodes are probabilistic dependencies among these corresponding variables. These dependencies are statistically learned and/or estimated by using measured data and augmented by domain expert knowledge. BNs models became popular models in the last decade and only recently received attention for HVAC (Heating, Ventilation and Air-conditioning) applications. A case study of using a BNs model to predict HVAC hot water energy consumption in an office building is presented. The energy estimation results meet with the criteria recommended by ASHRAE Guideline 14. This case study also shown that the discretized Bayesian Network model is sensitive to the discretization policy (i.e., bin size selection) employed. The applicability of a BNs model becomes questionable outside the range in which the model is learned.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Energy - Volume 164, 15 February 2016, Pages 650-658
نویسندگان
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