Premium
Sense‐Think‐Act Framework for Intelligent Building Energy Management
Author(s) -
Katsigarakis K.I.,
Kontes G.D.,
Giannakis G.I.,
Rovas D.V.
Publication year - 2016
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12173
Subject(s) - component (thermodynamics) , computer science , process (computing) , building automation , retrofitting , realization (probability) , systems engineering , task (project management) , energy (signal processing) , efficient energy use , architectural engineering , engineering , statistics , physics , mathematics , electrical engineering , structural engineering , thermodynamics , operating system
The realization of smart and energetically efficient buildings is contingent upon the successful implementation of two tasks that occur on distinct phases of the building life cycle: in the design and subsequent retrofitting phases, the selection and implementation of an effective energy concept, and, during the operation phase, the actuation of energy systems to ensure parsimonious energy use while retaining acceptable end‐user thermal comfort. Operational efficiencies are achieved through the use of Building Energy Management Systems tasked to deliver core Sense, Think, Act (STA) functionalities: Sense, using sensing modalities installed in the building; Think, utilizing, typically a rule‐based decision system; and Act, by sending actuation commands to controllable building elements. Providing the intelligence in this STA process can be a formidable task due to the complex interplay of many systems and occurrence of disturbances. In this article, an architectural and algorithmic framework is presented to provide streamlined implementation of this process. Important ingredients in this framework are: (S) a data access component capable of collecting and aggregating information from a number of heterogeneous sources (sensors, weather stations, weather forecasts); (T) a model‐based optimization methodology to generate intelligent operational decisions; and (A) an assessment and actuation component. An illustrative application of the proposed methodology in an office building is provided.