Knowledge management framework for monitoring systems improving building energy efficiency

Abstract

In the last decades scarcity of resources and global warming have led to a more and more efficient building design and usage aimed to reduce energy consumption and CO2 emission. For increasing energy efficiency of buildings over the whole life cycle monitoring systems became an important technology. Thereby, monitoring systems are usually applied in combination with controlling systems for providing building automation of HVAC (heating, ventilation and air conditioning) components in the usage phase. In this paper an approach will be presented describing a generic framework for efficiently using of monitoring in the design phase as well as in the usage phase. Based on certain building criteria a) the selection for an efficient, best cost-benefit, HVAC system and b) the efficient filtering, evaluating and prioritizing of energy performance values like cooling/heating consumption values will be supported. This will be done by considering only a small set of energy indicators representing and covering complex building designs and usage scenarios. As description method for the building criteria an ontology approach is considered comprising and consolidating the different input sources and creating the base for deriving and identifying these criteria. Furthermore, intelligent filtering methods are proposed operating on the origin source models and filtering and aggregating the elements for mapping them to the ontology descriptions. Altogether is embedded in a knowledge management framework forming the mediator for external software like simulation or CAD software. The use of the knowledge management framework is intended for a company applying it throughout several projects and storing the gained experience in the building criteria and the related functionalities.

Data Ontology Assessment To Support Smart And Ongoing Commissioning Of Buildings

“…On the basis of the reviewed ontologies an SOCx ontology should cover KPIs at various spatial and temporal scales for building performance assessment, contextual information for reasoning situations, and control and optimization rules for building performance improvement. Only 32% of papers included KPI semantic data in their ontologies [2,31,23,32,33,5,4,34,28,35].…”

A review of ontologies within the domain of smart and ongoing commissioning

“…Approach Reference Original ontology creation [61], [49], [14], [46], [52], [48], [37], [54], [29], [15], [67] Synthesis of existing ontologies [60], [62], [47], [24], [21], [50], [63], [51], [64], [53], [35], [55], [56], [57], [65], [66], [58], [68], [69], [59] Review and comparative analysis of existing ontologies [25], [22], [26], [27], [16], [28] The common building data types for which existing ontologies were reused included: indoor conditions and building systems/components, physical building information, simulation-based data, and other building data such as building location, as presented in Table 4. Since the extraction of some data types (e.g.…”

“…Application Reference KPI calculation [47], [57], [59] Building performance improvement [61], [21], [50], [51], [53], [54], [55], [56], [68], [58] Fault detection and diagnosis [35], [67], [69]…”

“…Analysis of existing ontologies with this application showed their main objectives as to improve building performance through engaging building users (e.g. facility manager and occupants) [21,50,53,56,58,68] or using automatic technologies such as building controls [55] and optimization process [61,54].…”

“…For instance, Han et al [21] proposed a context-aware ontology consisted of a context information aggregator (to collect information), a context reasoner (to extract inferences), and a service reasoner component (to provide a solution) to propose energy saving solutions to building managers based on a simulation-aided process. Similarly, Kadolsky et al [50] developed a monitoring system ontology comprised of a structure (to include building models), an environment (to contain simulation models), and a control module (to describe context) to recommend required changes in HVAC systems to facility managers. The EEPSA [56] and ESIM ontology [68] also gave facility managers insights into reducing energy use while maintaining occupants' comfort.…”