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Energy assessment of a near zero energy building (nZEB) using knowledge graphs

Lygerakis Filippos

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Summary

The main goal of this thesis is to create a KG for a near Zero Energy Building (nZEB), which will include a variety of different sensors, and then apply a data discovering and retrieval query on the KG, in order to make an energy performance and thermal comfort assessment. The nZEB that was chosen as a case study is the Leaf House, a residential state of the art building of six apartments that was built by Loccioni Group. The methodology that was followed included first, the research of the state of the art about KGs in nZEB, BIM, AEC-KGs and some uses and applications of them in the Built Environment industry. Next, follows the creation of Leaf House KG, as well as a data discovering and extraction query as an example of KG’s usage. After that an energy performance assessment for the Leaf House takes place, in addition to a thermal comfort assessment, using the Discomfort Index (DI), and lastly the conclusions of KGs in nZEB. The data from the different sensors and setpoints that the building is accommodating will be available by MyLeaf database, in order to feed this KG. The KG will be depicted with Brick Viewer and Brick Studio, in order to present the connection between the nodes of this KG. It was calculated that the annual energy consumption was 32.8MWh or 69.8kWh/m2, 64% of which originating from HVAC system consumption and 36% from the apartments’ consumption. What is more, the total net annual electrical energy consumption in 2020 was 9,801 kWh and total net normalized annual electrical energy consumption in 2020 was 20.9kWh/m2. The conclusions that come up from the results’ assessment for the data discovering and extraction query, are that is a simple and quick procedure that provides the user, coming from any background, with data analysis results without the use of a BIM and with information about the building. The thermal comfort assessment, which examined the Discomfort Index in all six apartments, showed that there was time in 2020, mainly in Summer time period, when under 50% of the population felt discomfort. This time period, which the discomfort lasted varied between the apartments. The apartments which are on middle storey had the shortest time period with thermal discomfort, in comparison to the bottom and top floor, which had longer time period of thermal discomfort, with top floor having the longest. What is more, the KG in a nZEB provides a hierarchical representation of the building’s entities, which is used as a base for many querying ideas and it nullifies the heterogeneity coming from different building representation models, as well as it gives to data more meaning and usefulness, due to the imported ontologies. Furthermore, it is important to be mentioned that the same KG manages in a single simple way, multiple different databases and sensors, in addition to giving easy access to up-to-date information that the user can discover and extract, according to the current agenda. Continuing, the KG allows users to perform queries and obtain information about the building’s entities and data in a common procedure. At last, the KG is used for complex systems correlation and data analysis without BIM usage.

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