Energy Semantic Network for Building Energy Management

This paper proposes an engineering design framework and methodology for building an energy semantic network (ESN) which helps to create and evaluate possible scenarios of energy system structure of buildings (energy generation, conversion, and conservation measures). The developed ESN does not only focus on building thermal performance (i.e. insulation materials, geometry, and dynamic behavior of building occupants) but also integrates energy resources, Hybrid Energy Supply Unit, and source-load interconnection. In other words, the developed ESN supports the design and evaluation of micro energy grid for building with various options of energy generation and conversion. Parameters identification of building energy system and their range is an important step to successfully develop energy optimization within buildings. The developed ESN generates the possible scenarios of energy generation and conversion for evaluation and optimization purposes. The structure of the ESN provides heterogeneous presentation of the classes with flexible architecture to modify, add, or delete significant energy classes. In addition, the ESN structure is designed to avoid non-realistic computational burden during simulations and evaluation. The methodology of generating the minimal possible scenarios is introduced. For validation purposes, the proposed algorithm is examined using case study of a mid-size house with different energy sources and thermal zones. The ESN of this case study is discussed, the possible scenarios of energy generation, conversion and load type are produced and their simulation and evaluation using five key performance indicators (KPIs) are introduced.