An ontology-based tool for automated configuration and deployment of technical building management services

In this work we present the architecture and a reference implementation of a software tool to automate the configuration and deployment of services for fault detection and diagnosis which can assist to improve operational building performance. We use an ontology as an intermediate meta-data layer to integrate the BIM information and the static BMS data required to automate this process. The contribution aspect resides in the demonstration of the approach which is based on the core concept of a tailored pairing of a fault detection and diagnosis service and an ontology query specifically designed by experts. Suggestions for the architecture are provided on how to embed the ontology in the overall framework. We present results from a first prototype to detect faults in real trend data of an air handling unit using rule-based analytics

Design of knowledge-based systems for automated deployment of building management services

Despite its high potential, the building's sector lags behind in reducing its energy demand. Tremendous savings can be achieved by deploying building management services during operation, however, the manual deployment of these services needs to be undertaken by experts and it is a tedious, time and cost consuming task. It requires detailed expert knowledge to match the diverse requirements of services with the present constellation of envelope, equipment and automation system in a target building. To enable the widespread deployment of these services, this knowledge-intensive task needs to be automated. Knowledge-based methods solve this task, however, their widespread adoption is hampered and solutions proposed in the past do not stick to basic principles of state of the art knowledge engineering methods. To fill this gap we present a novel methodological approach for the design of knowledge-based systems for the automated deployment of building management services. The approach covers the essential steps and best practices: (1) representation of terminological knowledge of a building and its systems based on well-established knowledge engineering methods; (2) representation and capturing of assertional knowledge on a real building portfolio based on open standards; and (3) use of the acquired knowledge for the automated deployment of building management services to increase the energy efficiency of buildings during operation. We validate the methodological approach by deploying it in a real-world large-scale European pilot on a diverse portfolio of buildings and a novel set of building management services. In addition, a novel ontology, which reuses and extends existing ontologies is presented.The authors would like to gratefully acknowledge the generous funding provided by the European Union’s Horizon 2020 research and innovation programme through the MOEEBIUS project under grant agreement No. 680517

An Integrated Method for Information and Communication Technology (ICT) Supported Energy Efficiency Evaluation and Optimization in Manufacturing: Knowledge-based Approach and Energy Performance Indicators (EnPI) to Support Evaluation and Optimization of Energy Efficiency

This thesis develops a holistic evaluation and optimization of energy efficiency in manufacturing. The innovation of this thesis consists in the integrated method applying an expressive and adaptive ontology knowledge base capable of learning, and sector-independent, straightforward energy performance indicator for evaluating different processes and units within a company. This thesis also develops a hyper-heuristics-based energy-optimized and flexible production scheduling